Conference 

ind Shear 

Detection an 

Third Combined Manufacturers’ 

and Technologists’ Conference 

Compiled by 

Dan D. Vieroy 

and Roland L. Bowles 

NASA Langley Research Center 

Hampton, Virginia 

Herbert Schlickenmaier 

Federal Aviation Administration 

Washington, D.C. 

Proceedings of a conference sponsored by the 

National Aeronautics and Space Administration 

and the Federal Aviation Administration 

and held in Harnpton, Virginia 

October 16-18. 1990 

January 1991 

National Aeronautics and 

Space Administration 

Langley Research Center 

Hampton, Virginia 23665-5225 
FOREWORD 

The Third Combined Manufacturers' and Technologists' Conference was hosted 

jointly by NASA Langley Research Center (LaRC) and the Federal Aviation Administration 

(FAA) in Hampton, Virginia on October 16-18, 1990. The meeting was co-chaired by 

Dr. Roland Bowles of LaRC and Herbert Schlickenmaier of the FAA. Dan Vicroy of 

LaRC served as the Technical Program Chairperson and Carol Lightner of the Bionetics 

Corporation was the Administrative Chairperson. 

The purpose of the meeting was to transfer significant ongoing results of the 

NASAFAA joint Airborne Wind Shear Program to the technical industry and to pose 

problems of current concern to the combined group. It also provided a forum for 

manufacturers to review forward-look technology concepts and for technologists to gain an 

understanding of the problems encountered by the manufacturers during the development 

of airborne equipment and the FAA certification requirements. 

The present document has been compiled to record the essence of the technology 

updates and discussions which followed each. Updates are represented here through the 

unedited duplication of the vugraphs, which were generously provided by the respective 

speakers. When time was available questions were taken form the floor; if time was not 

available questions were requested in writing. The questions and answers are included at 

the end of each presentation. A general question and answer session was conducted at the 

end of each day and is included at the end of report along with closing remarks. 

i 

TABLE OF CONTENTS 

Part 1" 

FOREWORD .............................................................................................................. i 

TABLE OF CONTENTS ............................................................................................ iii 

SESSION I. -- Terms of Reference 

A. Airline Industry Intentions .................................................................................... 3 

B. Wind Shear Program in France 

Frank Tullo, Air Transport Association 

1) Overview ..................................................................................................... 19 

2) LIDAR Studies on Microburs ts ........................................................................ 29 

3) RADAR Performance Experiments ................................................................... 37 

4) MEGASODAR Experiment ............................................................................ 57 

Bernard Ades, DGACISFACT 

Y. Aurenche and JL. Boulay, ONERA 

C. Le Roux, DGACISTNA 

Alain Donzier, REMTECH 

SESSION 11. -- Case Study 

A. 63 

B. Model Comparison of July 7, 1990 Microburs ......................................................... 81 

Integrated Data Analysis of July 7, 1990 Microburst .................................................. Dave Hinton, NASA langley 

Dr. Fred Proctor, MESO 

SESSION III. -- Flight Management 

A. Microburst Avoidance Simulation Tes .................................................................... 107 

Dr. John Hansman. MIT 

Capt. Ed Arbon, Flight Sdety Fowrdation 

Herb Schlickenmaier, FAA 

Dr. Robert Stengel. Princeton University 

Alex Stratton. Princeton University 

B. Wind Shear Training Applications for 91/135 ........................................................... 143 

C. Determining Target Pitch Angle ............................................................................. 153 

D. probabilistic Reasoning for Wind Shear Avoidance .................................................... 161 

SESSION IV. -- Sensor Fusion & Flight Evaluation 

A. Integration of Weathex sensing Devices ................................................................... 177 

Jim Daily, Honeywell Sperry 

Mike Lewis, NASA Langley 

SESSION V. -0 TDWR Data Link / Display 

B. NASA Langley Flight Test .............................................................................. 201 

A. TDWR Information on the Flight Deck ................................................................... 227 

B. orlanQExperiment ............................................................................................. 243 

Dave Hinton, NASA Lungley 

Dr. Stew Campbell, MIT Lincoln Laboratory 

Published & separate cover. 

* 

iii 
C. 

D. 

E. 

Integration ofthe TDWR andLLWAS Wid Shear Detection System ........................... 263 

A Status Report on the TDWR Efforts in the Denver Area. ......................................... 299 

Thermodynamic Alerter for Microbursts ................................................................... 351 

Larry Cornman, Natwnal Center for Amspheric Research 

Wayne Sand, National Center for Atmospheric Research 

Dr. Peter Eccles, MITRE 

SESSION VI. -- Heavy Rain Aerodynamics 

A. Status of Heavy Rain Tests ................................................................................... 367 

B. 

C. 

Gaudy Bezos, NASA tangley 

Ed Melson, NASA Wallops 

Dan Vicroy, NASA hngley 

Heavy Rain Field Measurements ............................................................................ 395 

Estimate of Heavy Rain Performance Effect. ............................................................. 425 

SESSION VII. -- 2nd Generation Reactive Systems 

A. Status of Sundstrand Reseatch ................................................................................ 453 

B. 

Don Bateman, Sundstrd 

Terry Zweijil, Honeywell Sperry 

Temperature Lapse Rare as an Adjunct to Wind Shear Detection ................................... 479 

Part 2 

SESSION VIII. -- Airborne LIDAR 

A. NASA Langley / Lockheed Research Status .............................................................. 509 

B. Continuous Wave Laser.. ...................................................................................... 527 

C . Status of 2 Micron Laser Technology Program ......................................................... 555 

D. Avionic Laser Multisensor Program at Litton Am) Products ....................................... 577 

Russel Targ, Lockheed 

Dr. Loren Nelson, OPHIR Corporation 

Mark Storm, NASA hngley 

Rod Benoist. Litton 

SESSION IX. -- Airborne Passive Infrared 

A. Status of NASA's IR Wind Shear Detection Research ................................................. 589 

B. Status of Turbulence Prediction Systems' AWAS III .................................................. 609 

C. Status of Color& State Universities' IR Research .................................................... 637 

Dr. Burnell McKissick. NASA hgley 

Pat Adamson, Turbulence Prediction Systems 

Dr. Pete Sinciair, Colorado Sm University 

SESSION X. - Airborne Doppler Radar I Industry 

A. Status of General Motors Hughes Electronics Research ............................................... 681 

Sakrliner Flight Test .......................................................................................... 714 

Dr. Btian Gallagkr, Delco 

Mark Selogk. Hughes 

Bruce Mathews, Westinghouse 

Dqal Kuntman, Bendix 

Roy Robertson, Collins 

B. 

C. SratusofBendixRemmch ..................................................................................... 755 

D. Status of Collins Research .................................................................................... 767 

iv 
SESSION XI. -- Airborne Doppler Radar I NASA 

A. Cluaer Modeling of the Denver Aqort and Surrounding Areas .................................... 785 

Steve Harrah. NASA Langley 

V. Delnore, Lockheed 

R. Onstott, ERIM 

Charles Britt. RTI 

Dr. Ernest Baxa, Clemson University 

M. Deshpande, VIGYAN Corp. 

Charles Britt, RTI 

E. M. Bracalente, NASA Langley 

W. R. Jones, NASA Langley 

0. Altiz, Rockwell International 

P. Sc!u#ner, NASA Langley 

J. H. Schrader, RTI 

H. J. C. Blume, NASA Langley 

B. Radar Simulation F’rograrn Up-grade & Algorithm Development .................................. 837 

Signal Processing Techniques for Clutter Filtering & Wind Shear Detection ................... 

Airborne Radar Simulation Studies of the Denver July 11, 1988 Microburst ................... 

Description, Characteristics, & Testing of the NASA Airborne Radar ............................ 937 

C. 869 

D. 913 

E. 

GENERAL QUESTIONS AND ANSWERS .............................................................. 981 

CLOSING REMARKS ............................................................................................... 987 

APPENDIX - List of Attendees ................................................................................ 991 

V 
Session VIII. Airborne LIDAR 

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Session VIII. Airborne LIDAR 

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NASA Langley / Lockheed Research Status 

Russel Tag, Lockheed 
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CLASS LASER W~~DS~EAR DETECTOR BLOCK 

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OPTICAL 

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DIGITAL EXABYTE 

UCR TAPE RECORDER 

(2.3 616ABYTES) 

(Lassen) RACK 

laser Q 

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Control Unit 

SIGNAL 

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RF-IF Board 

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NASA Langley / Lockheed Research Status - Questions and Answers 

Q: JAMES MEGAS (Northwest Air Lines) - What do you feel the cost of an operational 

coherent pulsed LIDAR would be? What are the trade offs that you feel could be made to 

reduce the cost? 

A: RUSSEL TARG (Lockheed) - The price will be negotiated between our assessment of 

what it takes to make it and what the airlines find a conceivably acceptable price. I think 

that's probably the way the price of everything is determined. From our initial inquiries, 

what it appears is that there's a minimum price under which we think it can't be made and a 

maximum price above which the airlines wouldn't c 

thing some place within there assuming that that's possible. To be serious, for the thing to 

be ready to be installed into an airplane, it has to be manufactured and installed for about 

$lOO,OOO or less. That's going to be a high price for the airlines and a challenging price 

for the manufacturer. At that price it seems to cause equal pain for everybody so it's 

probably the right price. The big systems that go into the airborne LIDAR are the laser, the 

photo detector, the scanner and the signal processor. We're going to have to take 

appropriately big bites out of each of those systems in accordance with what they presently 

cost to produce. Consequently, in order to even think about putting a LIDAR system into 

an airplane, the price of the laser has to be greatly reduced from the one of a kind system 

that we're presently using. We're so late in the day I think this is probably not a good time 

to go into the kinds of trades that we would do. I can say that choosing between a Co;! 

system and a 2 micron system is not a big effect in the ultimate price of the system. There 

are several different components which I enumerated before in addition to the electronics to 

hold them all together. So I think that a lOOk target is what we'll be looking at and that will 

be a challenge for any manufacturer in my opinion. 

Q: BRUCE MATTHEWS (Westinghouse) - What are the impacts on range and 

perfoImance of things other than rain? (Rain was already addressed). What are the 

impacts from fog, dust, smog and other aerosols? 

A: RUSSEL TARG (Lockheed) - For the ten micron system the impact of fog is minimal. 

There have been experiments at Bell Labs measuring the performance of a lighthouse 

system in fog such as would attenuate a visible beam by l@ attenuation and the attenuation 

for the fog was essentially nil. So I would say that although you could create a fog 

situation presumably, and I have not seen more detailed data than Bell Labs had, but fog is 

not a significant problem for the 10 micron LIDAR system. Somebody else is going to 

have to comment about the 2 micron because I'm ignorant of that. Dirt and dust in the air 

enhances a performance of all the LIDAR systems so all things being equal this system will 

work better in Los Angeles than it would in Boulder. Dirty air is a friend of the Co;! 

system. 

Q: JOE YOUSSEFI (Honeywell) - Will the landing gear be in the way? Will it be a 

problem for the LIDAR as installed on the NASA aircraft? Are you going to compensate 

for aircraft attitude, pitch and roll? 

A: RUSSEL TARG (Lockheed) - Yes, the landing gear will be a problem, it's right in our 

field of view. Luckily during the experimental phase of the program we're always going to 

conduct our experiment wheels up. So during the course of the experiment the landing 

gear will not be a problem. Presumably on a commercial aircraft we will be located up 

front, forward of the landing gear, so our scan will not be interfered with by landing gear. 

And the answer to the second question is affirmative. We will compensate for pitch and 

ably pay. We will price this 

525 
roll in real time as the information is given to us by the DATAC. Our two axis ball scanner 

is all programmed and has the capability to compensate for pitch and roll. 

Q: ED LOCKE (Therm0 Electron Technologies) - What's the frequency stability of the 

c@ laser? 

A: RUSSEL TARG (Lockheed) - It is 200 kilohertz, which is just what you would require 

in order to maintain the measurement capability that we're looking for which is a meter per 

second. 

Q: TERRY ZWEIFEL, (Honeywell Sperry) - Do you anticipate any problems with the 

optical alignment with the wild temperature swings the airplane might see in G loadings 

during landing and stuff? Is that going to be a problem? 

A: RUSSEL TARG (Lockheed) - The laser that we're building is actively frequency 

stabilized and is bolted down to a very rugged frame which I showed in the illustration. 

It's also actively water cooled to provide additional frequency stabilization. I don't 

anticipate any temperam fluctuations to cause a problem for the system. It's built so that 

it has a very high frequency loop, that is, we're feeding back at greater than a kilohertz rate 

so we think that any motion of the airplane will be very small indeed compared to the speed 

of the feed back loop controlling the laser frequency stability. 

ROLAND BOWS (NASA Langley) - That airplane is carrying so much equipment that 

we are really having some air conditioner burdens on it. That system will be basically 

cabin ambient down there and we may very well bit the bullet on that airplane and really 

upgrade the air conditioning system on it. You must remember, we're not building product 

runs for consumption in a civil system. The NASA role in this program is to prove the 

feasibility of the technology. We leave it to you airlines and manufacturers to work out the 

market place dynamics. 
Session VIII. Airborne LIDAR 

Continuous Wave Laser 

Dr. Loren Nelson, OPHIR Corporation 

527 

THIRD ANNUAL MANUFACTURER'S AND TECHNOLOGISTS' 

AIRBORNE WIND SHEAR REVIEW BRIEFING 

NASA LANGLEY RESEARCH CENTER 

October 17,1990 

CONTINUOUS WAVE LASER FOR WIND SHEAR DETECTION 

Dr. Loren Nelson 

OPHIR Corporation 

3 190 S. Wadsworth Blvd. 

Lakewood, CO 80227 

(303) 9861512 

ABSTRACT 

We present results of our development of a continuous-wave heterodyne carbon dioxide laser which has 

wind-shear detection capabilities. This development was sponsored by the FAA under their SBIR program 

under contract number DTRS-57-87-C-00111. 

The goal of the development was to investigate the lower cost CW (rather than pulsed) lidar option for 

look-ahead wind shear detection hm aircraft. The device also has potential utility for ground based 

wind-shear detection at secondary airports where the high cost ($6,OOO,OOO) of a Terminal Doppler 

Wearher Radar (TDWR) system is not justifiable. The CW-Lidar system presented here was fabricated for 

a hardware cost of less than Sl00,OOO. 

Details of the design and fabrication of the OPHIR CW 1O.w heterodyne doppler lidar wind shear detector 

are presented. Shot noise limited heterodyne signal detection has been attained. Field wind observations 

hm the CW-Lidar are presented. The OPHIR CW-Lidar was operated at Stapleton Airport (Denver, CO) 

on an intermittent basis during the months of August and September 1990. The look angle of the device 

was up the landing glide-slope of an active runway. No wind shear events occured during our observation 

period. The 3.5 watt CW output power of our propotype sem is shown to be marginal for achieving 

reliable sensor echo returns during clear air at Stapleton. When the air is filled with blowing dust or 

precipitation particles, echo spectra peaks of 10 to 30 db can be observed and velocity resolved. The bese 

way to increase sensitivity of our ~f-ofcoclcept ProtMYpe furtha is by changing from our singlechannel scanning spectral analyzer to a FFT or multichannel spectral analyzer. A multiplex advantage of 

5OOX should result, improving Sensitivity by 13.5 db with the same integration time. The proof-ofconcept 

prototype is difficult to maintain in optical alignment, and would require significant redesign to become 

airworthy. A more practical near-rem utilization may be in ground based use at secondary airports to 

monitor possible wind shear hazards. 

The finai two viewgqhs, presented for related general interest, illushate a new commercial capability to 

monitor supercooled water aircraft icing conditions above airports. Our subsidiary (Radiometrics 

Corporation) markers a millimeter wave device which can be used to remotely monitor aircraft icing 

conditions. We de- and quantified such conditions at the time of the Stapleton Ap icing related crash 

of the Federal Express Cam 208 N80FE at 02402 on Feb 27.1990. Our data set has been presented to 

the NTSB far use in their investigation. 

NK NOT FlL 529 
I. DISCUSSION - VIEWGWH I 

This viewgraph briefing will discuss the development and field testing of a cost-effective heterodyne 

continuous wave (CW) wind-shear doppler lidar. The CW output power is 3.5 watts at 10.6~ through an 8" 

telescope. 

This research was sponsored by the FAA under their SBIR Contract Number DTRS-57-87-C-00111. 

We will discuss proof-of-concept prototype hardware design, field testing at Stapleton Ap, and conclusions 

drawn from the research. 
AIRBORNE WIND SHEAR REVIEW 

NASA LANGLEY RESEARCH CENTER 

OCTOBER 17,1990 

CW LASER FOR WIND SHEAR DETECTION 

0 Dr. Loren Nelson 

OPHIR Corporation 

3190 S. Wadsworth Blvd. 

0 Lakewood, CO 80227 

0 (303) 986-1512 

FAA SBIR CONTRACT NO. DTRS-57-87-C-00111 

Prototype Hardware Design 

e Field Testing (Stapleton AP) 

0 Conclusions 

531 
2. DISCUSSION - VIEWGRAPH 2 

A functional diagram of the CW heterodyne lidar is shown. By using an acousto-optic modulator at 27.1 

Mhz offset, we can see wind both toward and away from the lidar in this heterodyne system. The detector 

is a liquid nitrogen cooled Mercury Cadmium Telluride photovoltiac sensor. Th uum analyzer is a 

commercial single-scanning channel spectrum analyzer. Sweep time is 0.2 s and 5 sweeps are 

averaged before display. There are 500 digitized data records written to disk during each sweep. Sweep 

length is +/- 3.7 Mhz, centered on 27.1 Mhz. This corresponds to a velocity range of +/- 10 m/s. Some 

runs were also made at a velocity range of +/- 25 4s. 

532 
533 
3. DISCUSSION - VIEWGRAPH 3 

Illustrates the location and orientation of the lidar van and beam during tests at Stapleton Ae. 

534 
OPHIR CW WIND-SHEAR LIDAR 

0 LOCATION DURING STAPLETON AP TESTS 

a 

10,004 OPHIR LIDAR 

t 

N 

535 
4. DISCUSSION - VIEWGRAPH 4 

A color photograph of the Lidar Portable Van on location at Stapleton Aqon 

S. DISCUSSION - VIEWGRAPH S 

ds away. As the w 
I li 

LIDAR DATA QUI& LOOKS oct05ah.raw I1 

0.9 2.6 288 

0.7 1.7 294 

-0.8 2.8 253 

-0.4 2.5 259 

0.1 2.5 272 

1.1 2.2 300 

0.3 1.6 281 

16: 20: 28 

16: 20: 33 

16: 20: 39 

16: 20: 45 

16: 20: 50 

16: 20: 56 

16: 21: 1 

0.5 2.2 282 

A3 33 3CA 

16: 21 : 7 

iC. 3* ic1 I".**. #Y N -- vy.l v -10.00 -6.00 

DOPPLER VELOCITY (m/s) 

539 
6. DISCUSSION - VIEWGRAPH 6 

A larger portion of this same calibration wheel experiment. Spectral intensity is contoured showing the 

changing wheel velocity both toward and away from the lidar. The central section blanked out is not 

observable with this system due to zero velocity stray light and modulator noise pickup. 
LIDAR DATA VELOCITY CONTOURS oct05.raw 

View Rotating Wheel Segment Calibrator 

4.00 -2.00 2.00 6.00 

DOPPLER VELOCITY (m/s) 

1.00 

541 
7. DlSCUSSIoN - VIEWGRAPH 7 

A comparion of lidar monitored wind velocity (solid) as compared to the along-beam wind component of a 

eo-located anemometer (dashed). 

542 
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8. DISCUSSION - VIEWGRAPH 8 

A sample spectral intensity gray scale plot of the lidar return from natural wind. The wind velocity 

changes from -2.5 m/s to zero during the course of the experiment. 
545 
9. DISCUSSION - VIEWGRAPH 9 

A similar plot showing light and meandering wind where velocity toward and away from the lidar was 

simultaneously observed within the beam length. This illustrates that the system can record wind shears if 

they occur within the beam. 

. 546 
0 

547 
14. DISCUSSION - VIEWGRAPH 10 

Conclusions drawn from this research effort. 

548 
CONCLUSIONS 

0 COST EFFECTIVE HARDWARE DEMONSTRATED 

- 3.5 watt CW 10.6~ output power 

- Wind can be remotely monitored 

- Divergent winds can be seen 

STAPLETON AP TESTS 

- Intermittent Testing Aug and Sept 1990 

- No wind shear events occured 

- Sensitivity marginal in clear air 

- Sensitivity adequate in dust or precipitation 

0 PROTOTYPE DESIGN STATUS 

- Proof-of-concept prototype is difficult to align, 

bulky 

- 13.5db signal processing sensitivity improvement 

possible 

- Airborne use requires significant redesign 

- Possible ground-based utility at secondary airports 

549 
I I. DISCUSSION - VIEWGRAPH 1 I 

The last two viewgraphs relate to a different meteorological sensor for airport safety use. They are 

presented very briefly here for general interest. Ophir's subsidiary corporation, Radiometrics Corporation, 

has developed and is now internationally marketing a millimeter wave radiometer that is useful in geodetic 

surveying, weather forecasting, and radio-astronomy. It can also be configured to be capable of monitoring 

aircraft icing conditions above airports. 

Viewgraph 11 is a copy of an illustrative handout about the sensor. 

550 
If vou are involved in precbe geodetic measurement. 

meteorology. or long-baseline astronomy. you should be 

aware of the newly 

poration .Microwave 

commercially available. transportable instrument can 

be used in the follow in^ applications: 

Wexher forecasting and modification 

Se3 level measurement for climactic change 

e Remote sensing of geophysical resources 

m Slessunng strains in the esnh's surface and 

deucting plarc tectonic motion 

e Forecsstmg aircraft icing . 

Very Long Baseline Interferometry (VLBI) 

Standard output measurements include: 

e Sky brightness temperature (degrees Kelvin) 

Total precipitable water (in millimeters) 

e Total liquid water (in millimeters) 

e Excess path lengrh (vapor refractive emr in centimeters) 

Unique design features include: 

6 Fat Start-up 

Quasi-optical lens components 

0 Low power requirements (17 watts) 

Internal noisc diode calibration sources 

Gaussian Horn-Lens antenna (5" be 

Sky brightness temperature accuracy of 0.5 K 

6 Mountable on standard surveyin 

e Complete internal au~~bra~o 

pod 

seconds 

Dual wave1 u~ment (23.8 G 

3 1.4 CHz) 

Automatic elevation sc-umin 

selected azimuth 

e Portability (I5 kilo s in a 45x28~74 ccntimetcr package) 

Internal micmproccssor conml for automatcd 

mcasurernent 

---__~ 

Plans include the addition of several passive 50-60 CHz 

oxygen chan~e~ to allow atmospheric temperature 

profiling as well as atmospheric moisture measurements 

from a single instrument package. 

For more infor~tion concerning this instrument, 

Telephone (303) 9 

2~Hour ~eIef~x (303) 9~-2~57 

55 
12. DISCUSSION - VIEWGRAPH 12 

On Feb 27.1990 at 0240 Zulu the Federal Express Cessna 208 NWFE crashed upon landing at Stapleton in 

an icing related incident. 

Radiometrics was opting its WVR-IO00 Radiometer 30 miles away in Boulder, Colorado during this 

period of time. A data trace showing a time h supercooled liquid water amount (icing 

tendancy) aloft is shown. The time of the crash wnasadot. Itcanbe 

seen that the crash occllred at the beginning of a severe icing aloft as observed by the 

IR-2OOO. This data has been pvided to the NTSB. We present it here for general interest since it may 

eventually prove to be a new method to monitor hazardous icing conditions aloft during aircraft airport 

approach and landing. 

552 
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553 
Continuous Wave Laser - Questions and Answers 

Q: JACQUES MANDLE (SEXTANT Avionique) - What are the characteristics of your 

telescope; type and aperture; variable or fixed focussing distance? 

A: LOREN NELSON (OPHIR Corporation) - The telescope was an off axis Doll-Kirkman 

telescope, 8 inches in aperture. That type was chosen in order to minimize the spicular 

reflection from the internal optical components of the scope. The focusing distance was 

adjustable manually between the range of 200 meters to infinity and the data you saw was 

taken at a setting of 500 meters. 

Q: PETER SIN- (Colorado State University) - With reference to the millimeter wave 

radiometer, what water vapor spectral line does the instrument employ and why was that 

frequency selected? 

A: LOREN NELSON (OPHIR Corporation) - At the end of the presentation I briefly 

indicated that the Radiometrics WVR- lo00 millimeter wave radiometer had detected an 

icing condition which was related to the February '90 Stapleton crash of an aircraft. Water 

vapor has a single purely rotational line at 23 GHz, the nearest closest line being at 183. 

We operate on the wings of the 23 GHz line, specifically at 23.8 GHz. That specific wave 

length was chosen for three reasons, one of which is, at that wave length the pressure 

dependence of the line broadening is altitude independent so we can use the same 

attenuation coefficient at all altitudes in the atmosphere. A second reason is by ICAO 

International Treaty, 23.8 GHz is an internationally protected band where nobody is 

allowed to radiate energy. Since we're looking at very weak emission on the order of 30 

degrees Kelvin brightness temperature, that becomes important. And the third reason is, 

that 23.8 GHz has a specific relation to our second channel at 31.4 and that let's us use a 

patented technique to half the cost of the instrument. We measure at 23.8, which is a water 

vapor absorption line, we measure at 31.4, which is a water vapor window. Where there 

is a square law relation to the absorption of liquid water the two equations can then be 

solved to come out with the liquid water line interval and the water vapor line interval. 

Q: GAUDY BEZOS (NASA Langley) - I am interested in more information on the sensor 

that measured the super-cooled liquid water content. How and where was the sensor 

mounted, was it at ground level? What were the liquid water content values measured? 

A: LOREN NELSON (OPHIR Corporation) - The Sensor happened to be at our research 

facility in Boulder, Colorado, which was 30 miles away €?om the Stapleton Ahport. It was 

mounted at ground level looking vertically, in a vertical acceptance beam. The sensor is 

about the size of a large mailbox and mounts on a standard surveying tripod. It's also 

capable of scanning in azimuth and elevation. The values weren't purely liquid water 

content, but are precipitable liquid water. The liquid that would be obtained if all of the 

water in a vertical column was squished down to a liquid layer at the bottom. They were 

on the order of one centimeter of liquid water. 

554 
c 

Session VIII. Airborne LIDAR 

Status of 2 Micron Laser Technology Program 

Mark Storm, NASA Langley 

555 
October 17, 1990 

Status of 2 Micron Laser Tochnology Program 

Mark Storm*, ST Systems Corporation (STX) 

28 Research Drive 

Hampton, Virginia 23666 

This paper describes the status of 2 micron lasers for windshear 

detection. Theoretical atmospheric and instrument system studies 

by Russell Tang and Rowland Bowles have demonstrated that the 2.1 

micron Ho:YAG lasers can effectively measure windspeeds in both wet 

and dry conditions with accuracies of 1 m/sec. Two microns laser 

transmitter technology looks very promising in the near future but 

several technical questions remain. Ho:YAG laser would be small 

compact and efficient requiring little or no maintenance. Since 

the Ho:YAG laser is diode laser pumped and has no moving part, the 

lifetime of this laser should be directly related to the diode 

laser lifetimes which can perform in excess of 10,000 hours. 

Ho:YAG efficiencies of 3-122 are expected but laser demonstrations 

confirming the ability to Q-switch this laser are required. 

Coherent laser operation has been demonstrated for both CW and Qswitched lasers. 
Presented to the: 

Third Combined Manufacturers' and Technologists' 

Airborne Wind Shear Review Meeting, Hampton, Va. 

October 17, 1990 

Mark E. Storm 

STX/NASA Langley 

557 
1 .O Introduction 

-Requirements for Coherent Lidar 

-Laser approach 

2.0 Single-Frequency Ho:Tm:YAG 

-Laser performance 

-Frequency Tuning 

-Heterodyne detection 

3.0 2-micron laser issues: 

-Efficiency Considerations 

-Crystal Spectroscopy 

4.0 Injection Seeding Experiment 

-Coherent Technology Results 

5.0 Summary and Prospects for 

a Windshear Transmitter. 

558 
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SINGLE-MODE LASER FOR INJECTION LOCKING 

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APPROACH: 

FABRY -PEROT 

PLANO-PIANO 

DIODE-USER PUWED 

ACHIEVEMENTS: 

SINGLE-MODE LASING OF H0:TM:YAG 

10 mW optical power at 2.091microns 

68% slope efficiency, QE.= 1.8, 4% optical-optical 

31 GHz [4.5 Angstroms] Temperatuie Tuning 

Demonstrated Heterodyne Detection 

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-CW, single-frequency demonstrated. 

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Henderson 

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self-heterodyne experiment. 

Storm 

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for Q-switched operation. 

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-100 Hz min. rep. rate 

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Session VIII. Airborne LIDAR 

Avionic Laser Multisensor Program at Litton Aero Products 

Rod Benoist, Litton Aero Products 

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Avionic Laser Multisensor Program at Litton Aero Products 

Questions and Answers 

Q: MIKE McCLENDON (American Airlines) - How long until a flying prototype? How 

long will the evaluation last? How long until a production system? How much dollars? 

A: ROD BENOIST (Litton Aero Products) - Each year we do a project plan which looks at 

these numbers and I'll tell you what our plan is. Basically we see a prototype as being an 

18 month project and then the production system another 18 months. So you're looking at 

from a kick off of about three years to production. In tern of dollars, I certainly listened 

very interestedly to what Dr. Tag had to say and wouldn't disagree with him at all on any 

point. We have a very aggressive target price though of $50,000. It's a target. So we're 

probably looking at 3 to 4 years to production and we're not kicked off on a prototype right 

now. However, an order for 100 systems, lo00 systems would probably do it. 

586 
Session IX. Airborne Passive Infrared 

587 
588 
Session IX. Airborne Passive Infrared 

Status of NASA's IR Wind Shear Detection Research 

Rr. Burnell McKissick, NASA Langley 

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Status of NASA's IR Wind Shear Detection Research 

Questions and Answers 

Q: MIKE TAYLOR (Boeing) - Will a lightning flash or a series of flashes in the infrared 

sensors field of view cause a temperature anomaly similar to a microburst event? 

A: BURNELL McKISSICK (NASA Langley) - Lightning flashes tend to be too local. 

They are very small events. The temperature anomaly that is sensed by infrared, the one 

that is really detectable from the standpoint of wind shear hazards, is a reduction in 

temperature drop. Lightning wouldn't be that. If you could sense one, it would be like a 

spike, I would think, a rise in temperature. Also being very local, I don't think it would be 

something you could sense from infrared. 
B 

Session IX. Airborne Passive Infrared 

Status of Turbulence Prediction System's AWAS III 

Pat Adamson, Turbulence Prediction Systems 

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PASSIVE INFRARED SYSTEM RECORDS 

THE FIRST EVER VALIDATED IN-FLIGHT PREDICTION 

OF Fs MICROBURST 

H. PATRICK ADAMSON 

TURBULENCE PREDICTION SYSTEMS 

3131 INDIAN ROAD 

BOULDER, COLORADO 80301 

Paper Presented at SAE 57 Meeting 

Cincinnati, Ohio 

October 8, 1990 

614 
ABSTRACT 

On July 7, 1990, a passive infrared system flown on the 

University of North Dakota Cessna Citation 11 atmospheric 

research aircraft achieved the first ever advance warning of an 

in-flight windshear encounter. 

The Cessna, following vectors from a ground based Terminal 

Doppler Weather Radar (TDWR) operated by MIT and NASA, 

intentionally flew towards a known windshear. The infrared 

system on the aircraft recorded the detection of the windshear 

with a 35 second advance warning. 

The aircraft continued to fly into the windshear to record the 

encounter. The aircraft was equipped with a: 1) Turbulence 

Prediction Systems (TPS) passive infrared Advance Warning 

Airborne System (FIWAS), 2) inertial navigational system (INS), 

and 3) air data measurement device. The data recorded in-flight 

by the infrared system was later compared to and found to agree 

with the data recorded by the TDWR and the in-situ air data. 

615 
Backqround and Introduction 

The hazard to aircraft resulting from an unexpected 

encounter with low-level windshear is well established. In 

studies using flight simulators, it was proven that the amount of 

warning time provided to the flight crew was the most significant 

factor in ensuring a successful recovery from a microburst 

encounter.' The AWAS-111, which is the third generation system 

and is in the process of FAA certification, provides advance 

warning by sensing the temperature signature of a microburst 

ahead-of the aircraft. A number of studies have demonstrated 

that there is a reliable relationship relating the severity of 

the microburst hazard to the change in temperature between the 

ambient air and the microburst.2 

temperature and through the use of a proprietary algorithm, 

constructs a hazard index. 

The AWAS senses this change in 

4 

When this index exceeds a pre-determined level, an alert is 

provided to the flight crew through an aural warning and the 

illumination of a red warning lamp in the cockpit. 

The following describes the performance of the AWAS during 

the approach to and the penetration of a severe microburst in 

Orlando, Florida. To judge this performance, the data recorded 

by the AWAS is compared to that recorded by the in-situ aircraft 

sensors and by the ground based TDWR. 

Significant advance warning (10 seconds or more) prior to a 

microburst encounter has not been available until now. The 

Turbulence Prediction Systems (TPS) Advance Warning Airborne 

System (FIWAS), a passive infrared spectrometer, provided the 

first ever verified advance warning (more than 35 seconds) of a 

severe windshear event. This historic event occurred on July 

7th, 1990. 

616 
1 

RAWINDSONDE Data - Figure 1 

Massachusetts Institute of Technology Lincoln Laboratory 

(NIT) -conducted a RAWINDSONDE (sounding) of the air over Orlando 

at 16:50 GMT, approximately two hours before the microburst 

developed. This sounding revealed a very wet layer of air from 

18,000 to 23,000 feet. Just below this wet air was a layer of 

dry air extending down from 18,080 feet to the 9,000 foot level. 

Another dry layer also existed below the 6,000 foot level. This 

type of configuration in the upper atmosphere, i.e., a wet layer 

with underlying dry layers is believed to constitute the 

conditions which favor the formation of wet microbursts. 3 

617 
FRED REMER 

UND FLIGHT SCIENTIST NOTES 

14:31:30 Engine start. A cell is developing just to the 

northeast of the airport. There are towering 

cumulus all quadrants. Plan is to get up early 

and hope a cell drifts over the airport. Planning 

on successive ILS 17 approaches. The 1753 Z ATIS 

is 4,500 SCT, 25,000 bkn, visibility 12 miles, 

temperature 95, dew point 71, wind 110 @ 4 kts, 

altimeter 30.03". Crew: Kent Streibel, 

Frederickson, Remer, Copp. 

14:43:5S Airborne. Climbing out to the south. ATC is 

taking us high (6000 ft.). 

14:50:10 Downwind for ILS 17. The storm is situated over 

the approach end of Runway 17. It is 60 dbZ. 

Lots of anvil. Lots of precipitation. 

14:51:07 T h e s t o r m is starting to produce a microburst at 

the surface. It is iust off our left wing. We 

are trying to keep the approach short so we can 

penetrate. 

14: 52:09 FL-2 observes a 25 knot divergence over the 

approach end of Runway 17. We are on final and 

heavy precipitation is obscuring the view of the 

airport. 

14; 57: 29 Climbing out after penetration. Strong downdraft 

in precipitation and increasing tailwind as we 

exited the precipitation. Excellent study. Down 

air was 15 m/s. 
3 4 km 

14 8 km 

e 1 *a 1s 2 km 

13 0 deg 

0 4 dcq 522 ft 

4 5 nm 152 5 de9 

619 
TDWR Data - Figure 2 

(pictured on previous page) 

The TDWR scans provi 

microburst just north of 

divergence of 23 m/s or a 

approximately 3 miles. T 

by Bowles/Hinton was 0.15. 

occurred near the center 

with a peak downdraft of acon from 

the aircraft (indicated by the let shows that 

the sequences and related 

for both the TDWR and the 

scan represents the rain rate per hour. A 60 dEz reading is 

greater than 9.98 inches per hour. The velocity scan represents 

the horizontal winds. The minuses represent winds blowing toward 

the TDWR while the positive readings represent winds blowing aw?y 

from the TDWR. The horizontal windshear occurs between the 

positive and negative readings. A reading of -12 m/s indicates a 

horizontal wind of approximately 24 knots. 

620 
Ground Track - Figure 3 

The Cessna Citation I1 was stabilized on an approach path 

toward the developing microburst in time to allow the AWAS to 

view the microburst for 90 seconds prior to penetration. When the 

aircraft was 90 seconds from penetration, the microburst (which 

was almost 3 miles in diameter) occupied approximately 40 degrees 

of the field of view. Since the AWAS has a; field of view of only 

two degrees, the AWAS sensed the event throughout the entire 

approach. 

The five letters, A through E, depicted in all of the graphs 

LOCAL GMT SECONDS 

represent the following: 

A: Start of Stabilized Flight 14:54: 29 18:54 : 29 53669 

8: First AWAS Peak 14: 55: 02 18: 55: 02 53702 

C: First AWAS Alert 14: 55 : 22 18: 55: 22 53722 

D: Second AWCIS Alert Condition 14:55:42 18: 55: 42 53742 

E: Peak Inertial Hazard 14: 55:57 18: 55: 57 53757 

Flight scientist notes indicate that at 14:50:10 (53410 sec) 

the TDWR is indicating that the storm detected near Runway 17 has 

a reflectivity of 60 dbZ. This corresponds to a rain rate of 

greater than 9.98 inches per hour. ATC reports at 14:54:24 (53664 

sec) a divergence of 40 knots. 

621 
Altitude Profile - Figure 4 

While approaching the microburst, the aircraft maintained a 

3.5 degree glide slope. The aircraft (just before point 'D') 

leveled off while penetrating the microburst. Later it continued 

its glide path until it leveled off at approximately 500 feet. 

The microburst maximum shear occurred at point 'E', where 

the combination of the horizontal and vertical winds combined 

(3 "650' AGL. The pilot countered the threat with increased 

throttle and continued through the event. 

633 
Roll, Pitch, and Heading Profiles - Figure 5 and 6 

CI constant heading is important for a predictive system 

because it is necessary to be observing the atmosphere in the 

expected fliqht path. The heading, as indicated in Figure 5, was 

constant throughout the approach to and the penetration of the 

microburst encounter. 

The roll pro6ile had a maximum deviation of 10 degrees 

during the encounter with the microburst. Roll angles varied 

from +2 to -4 degrees prior to penetration. During maximum 

shear, the greatest roll moment occurred (+lo to -SI. 

623 
The increasing changes in pitch as the aircraft approached 

the microburst is indicative of the increasing turbulence 

encountered. The greatest changes (-6 to +4) occurred on 

penetration of the microburst. 

53680 53700 53020 53040 53760 53780 

SmND6mNlD= 

Airspeed and Thrust Profile - Figure 7 

In preparation for penetrating the microburst, the pilot 

increased airspeed by 10 knots going from 175 to 185 knots. The 

pilot then leveled out the descent anqle and increased the engine 

RPM by 20%, going from 45 to 6SX. - 

During initial penetration (prior to point 'D'), the 

aircraft recorded a substantial reduction in performance. Even 

though the pilot increased engine thrust, the airspeed decreased 

by 10 knots. FI significantly greater decrease in performance 

could be expected in an aircraft with less power capacity, i.a., 

a lower thrust to weight ratio. 

624 
Outside Air Temp Profile - Figure 8 

The outside air temperature profile obtained from the 

standard Citation instrument indicates a 6' C temperature 

decrease existing between the edge of the microburst and the 

maximum shear. This is the temperature change that is remotely 

sensed by the infrared system. 

625 
Horizontal and Vertical Wind Profile - Figure 9 

These winds were calculated from the on-board INS sensor as 

the Cessna approached and passed through the microburst. While 

some degradation of the wind data was probably introduced by the 

turbulent flight, the major wind features of a typical microburst 

were recorded. The horizontal winds first shift from a slight 

tail wind to a performance increasing head wind as the microburst 

is approached. This occurs several seconds before point 'C'. This 

performance increasing head wind shifts rapidly to a tail wind 

near the axis of the microburst at point 'E'. The vertical winds 

indicate a major down draft beginning at 'C' and continuing 

throughout most of the event. 

It should be noted that the maximum shear occurs with the 

combination of the horizontal wind and the second vertical 

downdraft at point 'E'. It is this combination of a changing 

horizontal wind (decreasing performance) and a downdraft that 

maximize the hazard to the aircraft. 

638 
0.2 

0.18 

0.16 

I :::; 

10:: I 

h 0.06 

0.04 

0.02 

0 

53470 53090 5371 0 53730 53750 53770 

53880 53700 53720 53740 53760 53'780 

I smm€s?mMMII)Man 

Hazard index F (threat) - Figure 10 

The hazard index (F) represents the threat to the aircraft. 

F multiplied by the acceleration due to gravity (g) represents 

the thrust in ktdsecond necessary to maintain level flight. 

In this flight, the wind hazard index was calculated from 

the INS winds. The one hertz data from the UND aircraft was used 

for high fidelity information. The winds are averaged over a 6 

second period in order to reduce the effects of atmospheric 

transients which may be turbulent but not sustained. The 6 second 

running average is used to compute the wind hazard index by the 

401 lowing equationb: 

F (dWH/dt)/g - VW/AS 

where dWH/dt is the change per unit time in flight path wind 

velocity. The units are kts/sec: 

g is acceleration due to gravity in kts/sec (19.04 kts/sl 

VW is the vertical wind velocity in kts 

AS is the air speed of the plane in kts 

In the instance where F = 0.17, the thrust required to 

negate the threat is 3.24 kts/s (0.17 x 19.04). This is within 

the performance capabilities of the Cessna Citation 11. 

627 
0.2 

0.19 

0.18 

&5 0.17 

!?I 0.16 

I 1 :::: 

0.13 

0.12 

0.11 

0.1 

53670 53690 53710 53730 53750 53770 

53680 53700 53720 53740 53760 53700 

sBo3M)6mxIIIDNK;IIT 

AWAS Performance vs In-Situ - Figure 11 

The actual performance of the AWAS, in respect to accurately 

predicting the hazard to the aircraft, is provided in Figure It. 

The only in-situ reference is at point 'E' indicating a hazard of 

0.17. 

The AWAS first sensed a hazard of 0.15 at point 'B'. Because 

this predicted threat was calculated above the altitude limit of 

1500 feet, the alarm was not sounded. This did represent 

however, a potential predictive warning of 55 seconds. 

The first AWAS infrared (IR) based predictive alert was 

recorded at point 'C'. Both aural and visual alerts were 

enabled at 1302 feet. This represented a predictive warning of 35 

seconds. 

At point 'D', the AWAS provided an alert based on outside 

air temperature (OAT). The use of this sensor provided a hazard 

of 0.13 and a 15 second warning. 

The preset hazard thresholds in the AWAS are 0.15 for the IR 

and 0.13 for the OAT. The alerts were active at points 'B' and 

'D' but because the present software inhibits aural and visual 

warnings at or above 1500' AGL, the alarms were inhibited at 

point '8'. 

628 
AIRCRAFT VIDEO OF HICROBURST ENCOUNTER 

A forward looking video camera mounted in the UND aircraft 

affords a pilot’s eye view of the approach to the event. This 

video, along with flight scientist notes, is used as a 

confirmation tool- i.e. to identify pilot reactions, onset of 

rain, etc. 

Conclusions: 

TDWR F Index’ = 0.15 

In Situ F Index = 0.17 

AWGS F Index = 0.15 55 seconds advance warning 

0.16 35 seconds advance warning 

0.s 15 seconds advance warning 

0.13 

FAA Certification 

FAA certification is in process. The application was filed 

in-January 1990 and completion is expected in early 1991. 

An FAA STC for AWAS-I11 installation on the UND Cessna 

Citation 11 was issued on 05/17/90. Research flights of the UND 

Citation since 05/17/90 will be used for Proof of Intended 

Function. Most recently the Citation has flown in the Orlando 

TDWR study (5190 through 9/90) and in a Denver area dry 

microburst study (9190). Numerous hazardous conditions occurred 

during these flights. The relevant flight and TDWR data is 

currently being analyzed by TPS, NASA Langley and UND Aerospace 

Sciences personnel. 

An FAA STC for AWAS-I11 installation on American Airlines 

MD-80 (specifically DC-9-82 f 83) was issued 09/27/90. 

The first of three AWAS-I11 installations was completed 09/27/90. 

Preliminary flight test data has bein collected with actual 

commercial flight data expected soon. Data will be collected over 

1000 flights to assist in operational aspects of certification. 

629 
BIBLIOGRAPHY 

1 - Hinton, David A., 1990: "Relative Merits of Reactive and 

Forward-Look Detection for Windshear Encounters During 

Landing Approach for Various Microburst Escape Strategies", 

NASA Technical Memorandum 4156, DOT/FAA/DS-89/35. 

2 - Proctor, F. H., 1969: "A Relationship Between Peak 

Temperature Drop and Velocity Differential in a Microburst", 

Preprint, 3rd International Conference on the Aviation 

Weather System, Anaheim, CA. 

3 - karacena, F. and Maier, M.W., 1987: "Clnalysis of a 

Microburst in the FACE Meteorological Mesone'twork in 

Southern Florida", American Meteorological Society. 

4 - Adamson, H. P., 19BB: "Airborne Passive Infrared System for 

the Advance Warning of Low-Level Windshear and Clear Air 

Turbulence: 1968 In-Service and Theoretical Work". 

AIA&/NASA/AFWAL Conference on Sensors and Measurements 

Techniques for Aeronautical Applications, 9/88, Atlanta, 

Georgia. 

5 - Eowles, R. L. and Hinton, ID. A., 1990: "Windshear 

Detection: Clirborne System Perspective", Presented at 

WINDSHEAR-One Day Conference, London, England, 11/90. 

6 - Bowles, R. L. and Hinton, D. A., 1990. Same as Above. 

630 
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Status of Turbulence Prediction System's AWAS I11 

Questions and Answers 

Q: MARILYN WOLFSON (MIT Lincoln Laboratory) - Can your sensor be used to detect 

clear air turbulence? If so, do you have any data that shows its effectiveness? 

A: PAT ADAMSON (Turbulence Prediction Systems) - Yes. We'll be doing clear air 

turbulence tests in the American Airlines program. I forgot to mention it in the talk. We 

expect to get six minutes warning at high altitude in clear air turbulence. 

Q: MIKE GALE (American Airlines) - Based on the positive reaction by the ''scientific 

community" to the 35+ second predictive warning of the AWAS lII in relatively heavy 

rainfall on 7/1190, has the question regarding IR penetration distance been laid to rest? 

A: PAT ADAMSON (Turbulence Prediction Systems) - I don't know if it has been laid to 

rest. From my perspective we certainly look through some of the rain. We're still trying to 

analyze how far through the rain we looked One of the things we hope to get out of the 

UND sensor is the rain rate from the aircraft. So we'll get some numbers from that work. 

ROLAND BOWS (NASA Langley) - I'll answer the same question that was addressed 

to Pat because I think it was addressed to both of us. Data is data. If Pat has no problem, 

anybody that wants it can take it home with them. My conclusion is I saw the performance 

increase on the back side of the microburst right in the rain core. From best estimates 

anywhere from 5 to 6 inches per hour, maybe as high as 7 inches per hour of rain, that's 

pretty wet. Objectively it looked like it saw through it. So, I'll share that data with 

anybody. 

UNKNOWN - Would you share it with the Long Beach Aircraft Certification Office? 

ROLAND BOWS. (NASA Langley) - Any time they are ready. 

HERB SCHLICKENMAlER (FAA) - We're in the throws of putting together a briefing 

for Long Beach of not only this meeting but some of the technical topics that they might 

want to review with us as well. Guice Tinsley is also interested in coming down here with 

his team, as soon as funds are available to mvel, to get a review of what this meeting did 

and what happened. 

635 
636 
Session IX. Airborne Passive Infrared 

Status of Colorado State Universities' IR Research 

Dr. Pete Sinclair, Colorado State University 

637 
An Airborne FLIR Detection and Warning 

System for Low Altitude Wind Shear 

Peter C. Sinclair 

Department of AtmospheriG Science 

Colordo State University 

Fort Collins, CO 

October 18,3390 

To be published in: 

Peter M. Kuhn 

ARIS, Inc. 

Fort Collins, CO 

The Journal of Applied Meteorolbgy 

November 1990 

638 
X bs t ract 

There is now considerable evidence to substantiate the causal relationship between low 

altitude wind shear (LAWS) and the recent increase in low-dtitude aircraft accidents. The 

Sational Research Council (1983) has found that for the period 1964 to 1982, LAWS was 

involved in nearly all the weather related air camer fatalities. However, at present, there 

is 110 acceptable method, technique, or hardware system that provides the necessary safety 

margins, for spatial and timely detection of LAWS from an aircraft during the critical 

pliases of landing and takeoff. The Federal Aviation Administration (FAA) has addressed 

this matter (Federal Registry, 1988) and supports the development of an airborne system 

for detecting hazardous LAWS with at least a one minute warning of the potential hazard 

to the pilot. One of the purposes of this paper is to show from some of our preliminary 

flight measurement research that a forward looking infrared radiometer (FLIR,) system can 

be used to successfully detect the cool downdraft of downbursts (microbursts/macrobursts) 

and thunderstorm gust fiont outflows that are responsible for most of the LAWS events. 

The FLIR system provides a much greater safety margin for the pilot than that provided 

by reactive designs such as inertial-air speed systems that require the actual penetration 

of the MB before a pilot wbsning can be initiated. Our preliminary results indicate that 

an advanced airborne FLIR system could provide the pilot with remote indication of hlB 

threat, location, movement, and predicted MB hazards along the flight path ahead of the 

aircraft. 

In a proof-of-concept experiment, we have flight tested a prototype FLIIl system (nonscanning, fixed range) near and within Colorado ME’S with excellent detectability. The 

results show that a minimum warning time of onefour minutes (5-10 km), depending on 

aircraft speed, is available to the pilot prior to MB encounter. Analysis of the fight data 

with respect to a modified ‘Hazard Index’ indicates the severe hazard that :he apparently 

weak and innocuous MB’s present to both the commercial transport pilots as well as the 

much larger number of pilots who fly the smaller general aviation and executive aircraft. 

639 
1. Introduction 

Over the past few years the importance of low altitude wind shear (LAWS) from thunderstorm outflows and downbursts to aviation safety has resulted in the development of 

several new detection techniques and warning systems. The driving force for this atmospheric research had its roots in the sobering statistics of LAWS related accidents. The 

19i5 Eastern Airlines accident at Kennedy Airport (Fujita, 1985) provided much of the 

impetus for this initial research and development work. 

The National Transportation Safety Board (NTSB) statistics show that 1987 was the 

worst year for air travel since 1974 with 31 aircraft accidents claiming 231 lives. A number 

of these accidents were related to low altitude wind shear (LAWS)' incidents during the 

approach or takeoff phases. Ln addition, a study conducted by the National Research 

Council (1983) for the period 1964 to 1982 showed that LAWS was involved in nearly 

all the air carrier fatalities. Since 1982, the NTSB has studied three additional LAWS 

accidents, including the widely publicized Delta Airline microburst accident at Dallas/Fort 

Worth International Airport where 134 passengers and crew were killed. These studies do 

not indude similar statistics for the largest aircraft segment of the country, i.e. private and 

executive aircraft or general aviation aircraft (GA). Because of their low-altitude operating 

regime GA aircraft have increased possibilities of encountering dangerous wind shear events. 

Aircraft with high airspeed and wind loading appear to be more sensitive to headltail 

wind variations than aircraft with low airspeed and wing loading which are more sensitive 

to downdraft/updraft penetrations (Stengel, 1984). Our preliminary studies Suggest that 

many small, private aircraft acadenb, especially over high terrain are the result of LAWS 

generated by gust fronts (GF), and/or micro-macroburst (MB) activity. 

Although, significant progress has been made in the development and testing of the 

TDtVR2 and the LLWAS3 for large airport LAWS hazards (Mahoney, et al. 1989; Turnbull, 

'LAWS u lued in this propd is a generic knn which induda the wind tbear/vertical motion fields 

'TDWR: Tennind Doppler Weather Mu (Research Applications Program, 1988) 

'LLWAS: Low Level Windshear Alert System (Wikon and Rued, 1986; Goff and Grunzow, 1989) 

produced by gust frontr (GF), md microburxts/mmbursts (MB). 
et nl., 1989; Goff and Gramzow, 1989; McCarthy and Wilson, 1985; Campbell, et ai., 1989; 

Smythe, 1989), the FAA (Federal Registry, 1988) and other Federal agencies now recognizes 

that there is a need for an airborne low altitude wind shear system that will: 

1. supplement the planned 47 airport deployment of LLWAS and TDWR warning systems, and 

2. provide an on-board aircraft system that will indicate low altitude wind shear hazards 

at all airports for all commercial aircraft during the critical landing and takeoff phases. 

The importance of an airborne system is manifested in its unique capability to search, in 

real-time, the airspace directly ahead of the aircraft for suspected LAWS/MB activity during 

the entire approach to or departure from all runways at any airport. Figure 1 schematically 

depicts a possible LAWSIMB scenario for the landing (LDG) and takeoff (T/O) phases 

that involve a MB penetration. The-faward fooking infrared radiometer (FLIR) system 

remotely monitors the cold downdraft region of the MB vertical core as the aircraft descends 

along the glide slope toward the runway. Prior to and during takeoff, the aircraft FLIR 

system can scan vertically and horizontally ahead of the airdt to detect MB activity. 

Airborne inertial systems must first sense positive deviations above the glide slope due to 

an increase in headwinds or vertical motions (RL,) bdore corrective action can be initiated 

(Fig. 1). Further penetration into the MB to Rk are needed by these reactive systems 

to completely assess the MB intensity and safety of rtight. A similar situation develops for 

aircraft departures through a MB at locations RrI and RG. It is well recognized. that severe 

MB wind fields are capable of bringing down any commercial or private aircraft now flying. 

Consequently, aircraft inertial systems do not provide adequate warning for avoidance or 

escape of severe! LAWS/MB situations. Even in nonsevere situations they do not provide 

avoidance capability and may be marginal in providing a timely alert to the pilot and/or 

flight control system. In essence they are a reactive not a predictive flight safety system. 

641 
2. The Forward-Looking Infrared Radiometer (FLIR) System 

a. Tnstnunentatron 

Our objective has been to determine the applicability of a prototype infrared (IR) system 

for airborne, advance detection of thunderstorm downbursts which lead to low altitude 

wind shear (Fig. 2). The IR sensing system is a precision radiation thermometer with an 

instantaneous field of view (IFOV) of 2 deg. and special filters for sensing in the 13 to 

15 micrometer portion of the atmospheric molecular spectrum of COz. The radiometer is 

mounted (forward pointing) under the wing of a small atmospheric research aircraft (Fig. 

3). The wing suspension strut and instrument pod for the radiometer are located such that 

the radiometer IFOV is outside the propellor arc. 

-4 highly efficient onboard data acquisition system provides the data processing and 

calculation of Doppler winds, gust gradient observations (be gust probe system) together with aU standard meteorological parameters (Sindair and Purdom, 1989,1983). An 

advanced, high accuracy DME/LORAN-C navigation system allows precise positioning of 

the airaaft with respect to the location of advance shear detection and subsequent shear 

encounter. The central processing unit (MASSCOMP multi-bus computer) provides data 

sampling (25-100 samples sec"), storage, caldation, and graphical display in quasi-realtime. All data sampled is initidly stored on hard disk (80 megabytes) and then it is dumped 

to a compact, cassette type tape for final storage prior to landing. Past flight data processing is accomplished on the airborne computer and then dumped to a printer/graphics 

ground system. During the research flight the computer aIso provides curient graphical 

display of all the parameters for real-time display and control of the flight operations. 

b. Atmospheric Physics of Microburst Detection 

Previous work by several authors has shown that there is a demonstrated relationship 

between the temperature Merence across a shear-producing gust front or downburst outflow and the wind speed and direction of the gust front outflow. The larger temperature 

differences appear to produce higher wind shear or peak gusts. Fawbush and Miller (1954), 

642 
Foster (1958), and Proctor (1989) have provided a physical basis for predicting surface peak 

gusts caused by thunderstorm density currents. Temperature drops of 5°C may readily accompany peak gusts of 17 m s-l while those of 15°C are associated with peak gusts of 

approximately 40 m 5-l (Fig. 4). The more recent work by Proctor (1989) involving MB 

modeling tends to corroborate these earlier results of Fawbush and Miller and Foster for 

non-frontal thunderstorms. For example, Proctor’s results show a maximum deviation from 

earlier data of approximately -4 m s-l at a temperature drop (AT) of approximately 6°C. 

At other AT dues the surface wind gust values are also slightly lower with both data sets 

indicating nearly identical peak winds at AT = 16°C. 

On the other hand, however, Fujita (1985) has shown that 40% of NIMROD and JAWS 

microbursts are warmer than their enviroment at the surface. The outflow is then not strictly 

analogous to a relatively cold gravity or density current, although it initially may have a 

similar momentum structure. As a result, the temperature anomaly across the leading edge 

of the outflow at the surface may not always indicate a cool gravity current outflow with a 

known temperature drop vs. maximnm wind gust relationship. Thus, a FLIR temperature 

sensing-wind shear predictor system that looks at the surface outflow region would give 

confusing resalts much of the time. In addition, infrared observations of the surface outflow 

during the landing approach wdd also include a ground surface heat source term that 

would swamp the MB outflow signa. Consequently, our present FLIR system has an IFOV 

that intercepts the MB in a horizontal plane (Fig. 1). Thus, as the aircraft descends, 

successively lower regions of the MB vertical core are remotely sensed by the FLIR system. 

Below approximately 300 m AGL, the FLIR system will at some point intercept the MB 

outflow region. However, the FUR system is designed to provide a warning signal to the 

pilot Iong before this low dtitudelow speed situation develops. Consequently, the FLIR 

detected temperature anomalies will normally not include those positive anomalies that 

may be measured in the surface layer. If positive temperature anomalies aist significantly 

above the surface layer, then the MB will in aIl probability not be a flight hazard. 

843 
In some of our previous research (Kuhn et al. (1983), Kubn and Sindair (1987), Sinclair 

and Kuhn (1989)] low level penetrations of downbunts and microbursts indicated that the 

magnitude of the time rate of change of temperature difference ($$) was indicative of gust 

front intensity. These results suggested that the criterion for potential shear warning was 

-0.5*C/s. For larger negative values of s, the algorithm applied to the radiometer output 

predicts gust front shear to also increase. Note we are continuing our FLIR mezurements 

in order to increase the number of MB penetrations from which statistical and dynamical 

formulations can be developed between the MB temperature anomaly and the low altitude 

wind shear intensity. 

In a horizontally uniform temperature field, both the near filter channel of the radiometer, or the static air temperature measured at the aircraft, and the forward, long-range 

sensing filter channel of the radiometer sense the same temperature. As a cool MB is 

approached, the long range channel begins to sense a-coaler temperature well before the 

aircraft reaches the gust front, and the war channel senses the warmer static temperature 

at the aircraft until the cool downdaft or gust front is penetrated (Fig. 1). At this point 

both radiometers sense the same temperature for a period of time. No alert for LAWS is 

produced until the temperature difference between the forward sensed temperature and the 

aircraft temperature reaches the predetermined negative threshold (AT) and/or negative 

rate threshold (g). 

The width of the FLlIt radiometer filter pass band, Au, is an important consideration 

in designing the optics of the FLIR LAWS radiometer (Caracena, et d., 1981).'Theoretical 

considerations show that narrow pass bands give the best spatial discrimination of thermal 

perturbations, while broad pass bands produce the strongest corresponding perturbation 

signal in the radiometer output. 

Radiation in the atmospheric molecular spectrum of carbon dioxide (NE) and from the 

target (NT) that reaches the radiometer optics detector may be expressed a 

N = NE + NTfwatts cm-'sr-'] 
or 

See Appendix 1 for explanation of symbols. The first te Eq. (1) represents emitted 

radiance from the atmosphere (well-mixed COz) while the second term represents the target 

radiance transmitted through the atmosphere to the detector. 

In the first term (XE) of Eq. (1) the horizontal transmission may be expressed as 

where the product, qp, is the mean density of carbon dioxide gas. The weighting function 

distance in Eq. (1) is given by as a function of the horizontal path distance, 2. 

Equation (2) may be differentiated with respect to distance, 2, to give the logarithmic 

weighting function: 

This term weights the radiance received kom the target at the radiometer fiom distance 

increments in the direction of the target, such as a cold microburst or gnst front where LAWS 

may exist. This weighting function thus characterizes the contribution of IR radiation in 

the wavelength range selected by the filter through portions of the atmosphere along the 

cone of acceptance of the IR sensor. The choice of the filter spectral band (determined by 

the eut-on and cut-off filter wavelengths) therefore determines the rage or 'look distance' 

of the radiometer. The 'look distance' (t) is defined as the weighted mean distance (f), i.e. 

A detailed eduation of Eq. (3) a% a function of various horizontal distances, t, and altitudes 

(33 to 800 m) over various pass bands at 10 a'* intervals in the 667 to 710 cm" (14.99- 

14.08 prn) portion of the C02 spectrum (Fig. 5) provides a large matrix of logarithmic 

weighing functions. For our prototype IR detector system, we selected a weighting function 

centered near 700 cm" (14.29 prn) which results in a theoretical, fixed 'look-distance' 

of appmximately 5.0 km (Fig. 6). This configuration would give approximately 100-1.10 

645 
seconds warning time to microburst and shear encounter for our aircraft penetration speeds. 

For transport aircraft which have approach speeds of approximately 150 mph, the warning 

time to MB penetration would be only slightly less, i.e. 75-105 seconds. 

The second term (NT) in Eq. (1) represents the target temperature which in this case 

refers to the cool downdraft or microburst at temperature (To). If the target is at or 

within the equivalent 'look distance', it will be easily detected. For targets beyond the 'look 

distance', the atmospheric transmittance [~(AY)] will act to suppress the target radiance. 

The technique is to scan radially (in combination with azimuth scanning) with various 

filters [~J(Y)] until a particular 'look distance' provides a maximum change in radiance. 

This provides an estimate of the target distance from the FLIR system. 

c. FLIR System Performance 

To establish some confidence in the ability of the FLIR system to detect MB temperature anomalies of at least a few degrees centigrade, an analysis of the detection system noise 

equivalent radiance (NEN) and noise equivalent temperature difference (NEAT) thresholds was accomplished. The FLIR system employs a hyperimmersed thermister bolometer 

detector in the front end of a precision radiation thermometer which has the following 

specifications: 

did angle intercept at detector, [A~l - cos AB)]; sr-l 

detector IE'OV, (2.0°); where B and q3 are spherical coordinates 

electronic bandwidth (1.0 Hz) 

filter eaaency (0.68) 

lens eilidency (0.44) 

electronic system noise factor (1.2) 

optics Clear apaatnre (0.785 an2) 

detector area (0.25 x 104cm2) 

detector detectivity (3.0 x 108cm HZ'/~W") 

From these system parameters the noise equident radiance (NEN) can be calculated, 

NEN = 4.0 x 10%atts ~m"sr'~. 
The NEN provides a lower threshold at which the FLIR system can detect atmospheric 

radiant anomalies. 

In terms of temperature thresholds, a Compatible noise equivalent temperature difference 

(XETD) can also be obtained from the foUdng expression: 

where: 

E 3 emissivity (1.0) 

F I sensor focal Iength (14 mm) 

B I Plan& radiation law 

To 

TB I background temperature (294 K) 

r, 3 atmospheric transmission (0.35) 

to I optical transmission (0.30) 

blackbody target temperature (292 K) 

With these dues of the system parameters, the noise equivalent temperature difference is: 

NETD = 0.03 K . 

This NETD represents the necessary temperatundifference between the MB target (292 

K) and the environment (294 K) to produce a signal-to-noise ratio of unity (laboratory case, 

to = 1.0). For a real atmosphere with 350 ppm COz, 5 gm Kgm" water vapor, and the 

MB at a range of approximately 5 km, the NETD becomes: 

NETD = 0.12 K . 

These dts are compatible with the expesimentally determined FLlR system sensitivity 

of f0.1' K and acc~lfacy of f0.5" K. 

These ptdomance parameters win be improved signiftcantly in a second generation 

FLIR design which employs a cooled, HgCdTe (Mercury-Cadmium-Tduride) detector that 

provides a NEN = 4.72 Y watts 

Atmospheric effects (absorbtion and scattering) act to degrade the FLIR system performance. We have assumed that the MB is essentially a black body radiating through an 

intervening FASCODE2 model atmosphere (Clongh et al, 1986) that absorbs (COz and water vapor) and reradiates ad a black body. Background radiation is neglected since the MB 

647 
lateral and verticd dimensions provides an essentially opaque (black) body that completely 

intercepts the IFOV of the FLIR system. Scattering by dry atmospheric aerosols is small 

compared to carbon dioxide and water vapor absorbtion. For example, the LOWTRAN 7 

tropospheric aerosol model (Kneizys, et ai., 1988) for a mid-latitude MB situation indicates 

that neglect of aerosol scattering leads to a percentage error that is less than 0.2%. 

This analysis of the FLIR system performance provided a quantitative foundation from 

which we concluded that MB's with at least a AT = lo-2OC could be detected remotely 

through an absorbing atmosphere in the 12-15 pm infrared spectra passband. The resuits 

of several relatively 'weak' (AT = 2OC) MB penetrations also support the results of this 

system analysis and show that the FLIR system estimated accuracy of fO.5'C is met or 

exceeded. 

We have tested this basic concept under actual flight conditions and some of these 

measurement results are discussed in the foilowing sections. 

3. Preliminary Measurements and Observations 

a. Verification of FLIR DeteetabilitJr 

The prototype FLIB radiometer was instaUed on the right wing of our atmospheric research aircraft, a Cessaa T207. A highly &aent on-board data acquisition system (MASSCOMP computer) provides digital recording (2540 sps) of doppler winds, 3 axis gust probe 

and strapdown gyro parameters, dong with standard meteoroIogicaI parameters (Sindair 

and Purdom, 1989,1984,1983aJq Sindair, 1979,1973). 

Several flight tests ofour present proofofconcept system not only brought to light 

several new featnres of the microburst phenomena but provided, as well, a red microburst 

environment for preliminary testing of the forward-looking IR (FLIR.) wind shear detection 

system (Sindair and Kahn, 1987, 1989). Two examples of these penetrations are discussed 

below in order to show the potential for further development of the present proof-of-concept 

detection system. The approach to the microburst penetration is depicted in Fig. 7 with the 

winds (VH,~), the temperature difference (a,",) between the microburst and the aircraft 
environment, and the FLIR temperature difference (ATR) shown in Figs. 8 and 10. In 

these two MB penetrations the aircraft was %own in a constaat attitude, constant power 

configuration which allowed altitude changes above and below the initial point. We believe 

these to be the first airborne measurements made near and within a microburst of vertical 

motion (w), horizontal wind (VH), AT,, and ATR. 

The important features of these penetrations are outlined below: 

1) MB#1 

(a) The penetration was begun at 1800 ft (549 m) AGL, 18 km south of the Cheyenne 

Ridge (Colorado-Wyoming border) on 11 August 1987 at approximately 1400 

MST. The aircraft's true heading was approximately 270' at a true airspeed of 56 

m sec"'. The MB depiction in Fig. 7 is a reasonable facsimile of the penetration 

configuration. The four graphs in Fig. 8 represent (1) the atmospheric vertical 

motion (w) in m s-l, (2) the horizontal wind (VH) in degrees from true 

north (vertical lines) and knots, (3) the static (environmental) temperature (T,) 

at the aircraft, and (4) the far field radiometric temperature minus the static 

temperature (T,) measured at the aircraft (ATR). The abdssa is the horizontal 

distance in kilometers from the initial point. 

(b) The vertical motion field (10) shows the characteristic upward velocity of 1 m 

s-l below the cloud on approach to the MB. The core of the MB occurs at 

apprcrrdmatcly 10.0 km and is 'buried' within a heavy precipitation' (HP) core 

(Fig. 9) whac the maxinmm vertical velocity of w = -12.5 m s-* is reached. A 

secondary region of large vertical motion (c = -8 m s'*) was also encountered 

in light precipitation (LP) prior to entering the MB core at t E 7.5 km. This 

secondary downdraft core is driven by the upstream flow field of the downstream 

vortex (Fig. 9). It is important to note that this secondary downdraft core 

was encountered primarily because of the selected aircraft penetration altitude 

and heading relative to the MB orientation. Other grcraft penetration headings 

649 
and altitudes could have produced quite different secondary, as wd as primary, 

downdraft structure due to the MB asymmetry and vortex circulation structure. 

(c) The horizontal wind field (V,) during most of the penetration indicates a headwind component of approximately 10 knots. Within the HP core of the MB the 

wind changes abruptly to a tailwind of 15-20 knots. This wind reversal (AVH = 

25-30 knots), coupled with the severe downdraft of the MB, provides a critical 

flight regime for aircraft maneuvering near the ground. Since this was a midlevel MB penetration (i.e. initially above the vortex flow field), the VH wind field 

did not exhibit the classical strong headwind-tailwind sequence that is normally 

observed closer to the ground in the MB outflow region. 

(d) The static temperature (T,) measured at the aircraft represents the temperature 

variations near and within the MB with respect to a reference altitude (z z 550 

m AGL), i.e. the initiak altitude at z = 0. The.process lapse rate required to 

reference the measured temperature from altitudes above and below this reference 

altitude was obtained from multi-level aircraft soundings near and within the MB. 

The temperature measurements indicate a sharp decrease at approximately z = 

5.5 km, just prior to entering the light precipitation (LP), Fig. 9. A maximum 

temperature deficit or change of AT, = 2°C occurs near the backside (upstream) 

of the MB core just outside of the EP in the rain-cooled region. 

(e) The FLXR,, ATR data plot indicates a target acquisition at about 3.3 km or 

appraOdmateJyMkm from the target which represents the rain-cobled are of 

the wet MB at z a 34Skm. As pointed out above in the temperature (T,) 

discassion, the maximam AT, actually occurs on the upstream or backside of 

the MB. However, the FLIR measured ATR of -2°C agrees with the in-situ AT, 

6.0 

4-40 

=., , c :-e-. 

of -2"C, and therefore a warning of impending MB penetration of,deast2-h 

minutes is adable to the pilot of a jet traasport type aircraft in the landing 

phase. At slower approach speeds, this warning time is significantly increased. 

It is important to note also, that because of the FLIR systems minimum de650 
tectability of approximately f0.5"C, the first significant temperature decrease 

at z z 5.5 km of AT, = 0.5"C, was actually detected at approximately 2 % 1.3 

km. Consequently, this rain cooled region of the LP region which proceeded the 

main core of the MB, may provide alert alarms prior to penetration of the MB 

core on particular aircraft penetration tracks. In any case, these preliminary 

measurements indicate that our FLIR system can detect the MB core through 

light precipitation. 

The cross-over point where AT > 0 does not mean that the wet MB is 

now warmer than the neaf field static temperature. What has happened is that 

some of the precipitation has been deposited on the radiometer optics. This 

water coating on the lens has resulted in the blockage of outside radiation to 

the detector. The detector then also views reflected energy from the heated 

black body reference cavity during this part of the chopper cycle. This results 

in an erroneously high temperature output which will eventually approach the 

45°C cavity reference. Hence, the AT'S will progressively increase in a positive 

direction as indicated for 2 5.7 km. We are testing several design modifications 

which will eliminate this precipitation contamination of the FLIR optics. 

2) MB#2 

On the same day, a second MB penetration was made Over flat terrain just north 

of Fort Collins, CO (Figs. 10 and 11). The important features of this penetration are 

outlined below: 

(a) The penetration was started at 1150 ft (350 m) AGL at approximately 1500 MST. 

The aircraft true heading was 200' at a true airspeed of 57 m sec". This MB 

configuration is similar to that depicted in Fig. 7, but with very little vortex rollup of the outflow near the ground. The three graphs depict the same parameters 

as displayed in the first MB penetration (Fig. 8). 

65 1 
(b) The vertical motion field (w) in this case is primarily downward on approach to 

the wet MB. This is a result of the light rain encountered between z = 2.5 km 

and 5.0 km. The core of the wet MB is located at approximately 9.0 km and 

is 'buried' within the moderate precipitation (MP) core where the downward 

vertical motion reaches a maximum of w z -14 m s-l. In this case, MB#2 had 

a much more extensive area of LP prior to penetration of the MB core which was 

approximately the same diameter as that of MB#1 (Figs. 9 and 11). Although 

the largest vertical motion (to zz -14 m s'l) was encountered within the LIB 

core, the downward vertical motion was still strong just upstream from the MP 

in the rain-cooled region (Fig. 11). This region of downward motion appears to 

frequently occur on the upstream side, which appears to be a rain cooled region 

following the primary precipitation core of the MB. 

(c) The horizontal wind field (Vn) during most of the penetration indicates a headwind component of approximately 10 knots. In this case, the wind begins to 

change within the core of the wet MB from southwesterly to a 5-10 knot northerly 

flow. While the effective headwind-tailwind component amounts to approximately 20-25 knots, the change takes place over a horizontd distance of 4-5 km. 

This change is more gradual in headwind-tailwind component (e % 2.8 x 

sa'') than in MB#1 where essentially the same change occurred over a 1 km 

distance (e = 13.8~ see-l). Note, that the shear (e) in MB#1 significantly exceeds the presently accepted minimum wind shear hazard of 2.5 x 

sec'' (Mahoney, et ol., 1989): Again, however, this is a mid-level MB penetration 

where the VH wind field did not exhibit the classical headwind-tailwind sequence 

that is normally observed closer to the ground in the MB outflow regions. 

(d) The temperature minimum of approximately 18.5"C occurs at 2 = 9.3 km (Fig. 

10) which agrees well with the location of the maximum downward vertical motion of w = -14 m s'l (Fig. ll). Thus, the total temperature deficit is approximately AT, = 1.8OC. The T, measurements indicate that the cool !dB downdraft 

652 
core begins at z a 8.3 km and extends to 2 4 11.0 km. Note, that the temperature returns slowly to a near constant environmental due of T, z 2O.O0C. 

This slow return of the temperature to a somewhat lower value on the upstream 

side of the MB is due primarily to the effect of the rain cooled region left in the 

‘wake’ of the MB. Also, as in MB#l, there is a definite temperature decrease 

as the aircraft approaches or enters the precipitation regions. In MB#2, this 

initial temperature decrease occurs at z z 5.2 km while in MB#l this same 

initial decrease of temperature occurs at z z 5.5 km. In both wes, this initial temperature decrease is associated with the approach to or encountering 

fight precipitation (LP) preceding (or downstream of) the MB core. Penetration 

tracks from the upwind side of the MB would show a more gradual temperature decrease characteristic of the trailing ‘wake’ or rain-cooled region. On the 

other hand, cross-stream penetrations of the MB core may show neither of these 

temperature variations, especially in the case of asymmetric MB flow structure. 

Under particular conditions therefore, these temperature decreases may prove to 

be important precursors of MB presence and intensity further along the flight 

path. Numerid simulations of microbursts also indicate a temperature drop 

prior to penetration of the MB core, primarily during the increasing headwind 

portion of the penetration (Babcock and Droegemeier, 1989; Droegemeier and 

Babcock, 1989). This is easily explained in that in these cases the modeled penetration track is through the symmetrical outflow vortex roll-up whi& represents 

cooler air than the environment. However, as Proctor (1989) and others (Bedard 

and LeFebvre, 1986) have pointed out, the presence of a surface stable layer or 

warm boundary layer can greatly modify the temperature of the outflow (vortex) 

air-to the point, in some cases, where the increasing headwind may be warmer 

than the surrounding environment. In the two cases we have cited here the initial penetration flight track is just above the outflow acd consequently the first 

temperature decrease is due to the LP region preceding the MB core. 

653 
(e) The FLIR, ATR data plot suggests a MB target acquisition at t z 3.0 km or 

b. 

approximately 6.3 km from the MB core at t 2: 9.3 km (Fig. 10). In this 

case, the detail of the maximum ATR is somewhat obscured by the effect of the 

precipitation on the PRT-5 optics. h this case, the maximum temperature deficit 

(ATS z 1.8"C) also compares favorably with the maximum FLIR measurement 

of ATR z 1.8°-2.00C. Again, a warning time of approximately 2 minutes is 

available for transport type aircraft and up to 4 minutes for smaller, general 

aviation aircraft. Furthermore, we believe that the MB was, in essence, initially 

detected at z = 1.0 km due to the cool downdraft in LP at z z 5.2 km. As 

in MB#l, this early detection of the cool downdraft preceding the MB core 

along this penetration track provides 1 minute plus alert signal at z z 1.0 km in 

addition to the 2 minute warning at z zz 5.0 km of impending MB penetration. 

Microburst Features Important to €'E& Safety 

1) Headwind/TaiIwkd-Vertica Motion Factor 

Our Eight research indicates, in agreement with previous events and research, that 

the low Ievd penetration of a fully developed microburst (MB), which combines the 

effects of strong headwind/tailwind and vertical motion factors, be very hazardous 

to the untrained pilot. However, this is not the only hazardous situation for the unsuspecting pilot. "here are many more MB's that appear weak and innocuoui to the pilot 

than there are those that can be easily distinguished by a trained pilot. Many of these 

so-called innocuous MB's are dry and therefore not easily detected by the proposed 

airport radars. However, these MB's are capable of producing vertical and horizontal 

flow fields that are still hazardous with respect to transport type aircraft landing and 

takeoff performance margins. Furthermore, pilots of smaller aircraft may well find 

that their aircaft ianding/ta,keoff performance margins (dimb rate, controllability, 

speed control, etc.) are significantly exceeded during these MB penetrations. 
Consequently, in order to fully document this flight safety hazard, it is imperative 

that in-situ flight measurements by research aircraft be continued in a full range of MB 

types, at various altitudes and penetration headings with respect to the MB track. 

Our preliminary flight results indicate that in certain MB approach headings and 

altitudes the vertical motion field may provide a more hazardous %ight regime than 

the headwind/tailwind factor. In other approach headings and MB configurations, the 

reverse may be true or both factors may be of near equal importance. The availability 

of in-situ measurements of this type by research aircraft will provide the air-truth 

needed for radar algorithm improvement, numerical modeling studies, and realistic 

aircraft simulation operation and training. 

2) The Hazard Index 

In order to put some of our preliminary measurements in perspective with the 

antiapated hazards of MB penetration, the hazard index (r) developed by Targ and 

Bowles (1988) is shown in Figs. 9 and 11, Le., 

along with a second hazard factor proposed by the authors, 

F=F I+- [ 12:"1 

where: 

ir . E 

g E accelerationofgravity 

to I vertical wind velocity component 

V I trueairspeedoftheaircraft 

A = altitude above ground level (AGL) 

Lagrangian change in the wind dong the aircraft flight path 

Positive values of F indicate aircraft performance loss (i.e. decreasing headwind or 

increasing tailwind and/or downdrafk) while negative values of F indicate aircraft 

performance gain (i.e. increasing headwind or decreasing tailwind andfor updraft). 

The F factor is quantitatively related to the effect of wind shearjvertical motion on 

the aircraft energ state and the available rate of climb potential. We suggest an 

655 
additional hazard index factor (F') which is represented by the second hazard index 

graph (A) in Figs. 9 and 11. It indudes the additional hazard of the aircraft AGL 

altitude, i.e. the potential MB hazard is substantially increased for a low level aircraft 

penetration us one at a higher altitude where recovery may be more probable. From 

our experience with general aviation aircraft, an altitude loss of 250-300 m is not 

unusual in our present penetration technique, Le. constant attitude-constant power 

profile. Note, this altitude loss results in a maximum 7-10 degree flight path angle with 

the horizontal and thus does not significantly affect the hazard index (F) derivation 

approximations. As the aircraR approaches the ground due to aircraft performance 

loss within the MB (F > 0), the hazard index (P) increases significantly due to the 

altitude term (1+ 9). Thus, F* is always greater than F depending on the aircraft 

altitude (AGL). For example, at critical altitudes below 120 m, F' will be more than 

twice the value of P. An analysis of a wide range of commercial aircraft (light-tomedium weight) performance capabilities indicates that the hazard index factor (F') 

could be used to alert the pilot of the Bight hazards of MB penetration, Le. 

MB Flight Hazards 

No hazard: F < 0.10 

Yellow alert: 0.10 5 F < 0.20 

Red alert: P 20.20 

The yellow alert implies considerable caution must be exercised by the pilot to avoid 

unacceptable altitade/airspeed losses during MB penetration. The red alert indicates 

that MB penetration is not advised and appropriate abort and go-around procedures 

will be necessary. Consequently, in both MB#1 and MB#2 (Figs. 9 and ll), the 

hazard index [F or F'] becomes significant (yellow and red alerts) from near the 

forward edge of the MB to an area just upstream of the rear precipitation boundary. 

This hazard region is generated primarily by the vertical motion term (v) and the 

ground proximity term (1 + 9). Only near the rear boundary of MB#1 (Fig. 

9) does the wind shear term (%> become more significant (at z z 10.9 km) than 

656 
the vertical motion term (v). The general dominance of the term f is important 

when one considers that most privatecommercial aircraft have easily generated climb 

capabilities significantly less than the 8-15 m s-* vertical motions measured in MB#l 

and MB#2. 

4. Condusions 

We anticipate that continued aircraft probing of microbursts of various sizes and 

intensities at different altitudes and relative penetration headings will yield significant 

information on MB structure and aircraft hazards IF, F']. This information coupled 

with the FLIR (ATR) measurements will provide a data base from which alert and 

warning algorithms can be developed for second and third generation FLlR detection 

systems. These on-going and future studies will bring into sharper focus the importance of water mgwr absorbtion, predpitation screening of MB infrared signals, and 

warm MB fa3se alarms. The latter factor, warm MB's, is considered by many to be 

simply a manifestation of the distarbance of the warm, surface layer air by the MB 

outflow. As a result, ground surface temperature measurements could indicate a warm 

MB core which in reality may still be colder thaa its environment at an altitude of 

50-100 m. This warm surface layer is usually below the FLIR scan volume and would 

therefore not become a faSe alarm factor. Additional measurements will provide a 

dearer and quantitative picture of the actnd atmospheric processes responsible for 

the warm MB structure. 

657 
Acknowledgementa. The research was supported by NSF Grant #ATM-84-20980 (Thunderstorm Outflow Studies), NOM Grant #43-RANR-5-03966, and ARE, Inc., Fort Collins, 

CO. The authors thank Becky Armstrong for preparation of the text and Judy Sorbie-Dunn 

for drafting the figures. 
Appendix: Symbol and Acronym Table 

A: 

AT, 

AV 

st-l 

x 

P 

AGL 

DME/LORA.N-C 

IFOV 

U 

t 

radiance, w cm-2 sr-l (B I blackbody radiance) 

temperature, degrees Kelvin 

C02 absorption coefficient, cm2g"' 

mass mixing ratio of COZ, g g-' 

atmospheric temperature, K 

Target temperature, K (Downburst volume) 

optical thickness of COz gas (g cm-2) 

vertical motion, m s-l 

horizontal distance, km 

vertical distance, m 

temperature difference between FLIR sensed air temperature and the 

aircraft static temperature 

time rate of change of forward looking IR air temperature 

minus static air temperature at aircraff, "C s-l 

static temperature deficit between aircraft and microburst 

optical filter band width, cm'l 

steradian 

wave number, an-' 

wavelength 

C02 transmittance, % 

air density, g an", p/wI 

radiometer filter transmission, % 

Above Ground Level 

Distance Measuring System/Long Range Navigation System 

Instantaneous Field of View 

659 
References 

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Propagation Laboratory, Boulder, Colorado, 112 p. 

Campbell, S.D., M.W. Merritt, and J.T. DiStefano, 1989: Microburst recognition performance of TDWR operational testbed, Thini International Conference on the rlciation Weather System, Anaheim, CA, AMs, Boston, Jan 30-Feb 3. 

Caracena, F., P.Y. Kuhn, and R.L. Kurkmski, 1981: Design and preliminary tests of an 

IR-airborne LLWS remote sensing system, AIAA Paper 81-0239, Jmuary. 

Clough, SA., et al., 1986: Atmospheric radiance and transmittance: FASCODE 2, Pmedings of 6th Conference on Atmospheric Radiation, WiIIiamsburg, VA, AMS, Boston, 

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Droegemeier, K.K. and M.R. Babcock, 1989: Numerical simulation of microburst downdrafts: application to on-board and look-ahead sensor technology, Preprints, AIAA 

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Fawbush, E.J., and R.C. MilIer, 1954: A basis for forecasting peak wind gusts in non-frontal 

thunderstorms, Bull. Amer. Meteor. Soc., 3S, 14-19. 

Federal Registry, 1988: Airborne low-altitude wind shear equipment and training requirements, Vo1w.~ 53, No. 187, Rules and Regulations, p. 37688. Department of Transportation, F--LA, 14CFB Parts 121 and 135 [DOCET 19110: Ammendment Nos. 

121-149, 135-273. 

Foster, D.S., 1958: Thunderstorm gusts compared with computed downdraft speeds, Mon. 

Wea. Reo., 86, (3). 

Fujita, T., 1985: The downburst, Department of Geophysical Sciences, University of Chicago, 

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Goff, C.R. and R.R. Gromzow, 1989 The FederaI Aviation Administration's low level windshear alert system: a pmject management prospective, Thini International Conference on the Aviation Weather System, Anaheim, CA, AMs, Boston, Jan 30-Feb 

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Kneizys, F.X., et al., 1988: Users Guide to L0WTRA.N 7, Environmental Research Paper 

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Kuhn, P.M., R.L. Kurkawski, and F. Caracena, 1983: Airborne operation of an infrared 

low-level wind shear prediction system, J. Aircraft, 20, 170-173. 

660 
I 

Kuhn, P.M. and P.C. Sindair, 1987: Airborne infrared wind shear detector performance in 

rain obscuration, AIAA Paper, 25th Aerospace Conference, Reno, NV, January. 

National Research Council. 1983: Low altitude wind shear and its hazard to aviation. 

National Academy Press, Washington, D.C., 161 pp. 

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by TDWR: performance assessment, Third International Conference on the Aviation 

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project at Denver's Stapleton International Airport: operational testing of terminal 

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Boston, MA, 247-256. 

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Anaheim, CA, XMS, Boston, Jan 30-Feb 3. 

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661 
Sinclair, P.C. and P.M. Kuhn, 1989: Aircraft low level wind shear detection and warning 

system, Third International Conference on the Aviation Weather System, Anaheim, 

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Smythe, G.R, 1989: Evaluation of the 12-station enhanced low level wind shear alert system 

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662 
Figure Captions 

Fig. 1 LAWS/MB Detection Systems. Rr, and RT refer to reactive systems that require the 

aircraft to penetrate and react to the LAWS/MB circulation. Surface based single 

doppIer radars (TDWR) have good surveihce capabilities but may not detect alI 

MB's (dry) or winds at low altitudes. The FLIR system remotely monitors the cold 

downdraft region of the MB during landing and takeoff. Vertical scanning avoids 

intercept with ground surface and warm boundary layer air. 

Fig. 2 Thunderstorm Microburst Detection by Scanning FLIR System. The forward scanning and ranging capabilities of the new FLIR system provides a 50-i0 second warning 

of microburst penetration to the pilot of the approaching aircraft. Note that the FLIR 

system has an IFOV that intercepts the MB in a horizontal plane above the ground 

surface. 

Fig. 3 Wing-mounted Forward-Looking Radiometer Pod. The radiometer FOV(fl0") is 

completely outside of the engine propellor arc. The radiometric measnrements are 

supplemented with: 

0 Gust probe measurements of u',d,w'. 

0 Doppler (navigation) wind measurements of Q,5. 

0 Temperature and dewpoint measarements. 

0 Red-Time, Computer (MASSCOMPjConcurrent Systems) controlled data acquisition, data storage, and color graphid display. 

Fig. 4 Relationship of Thunderstorm Peak Gust with Temperature Drop (AT) at the Surface 

(Fawbnsh and Miller, 1954). 

Fig. 5 Transmithnce of a 1,000-foot path in air at sea level containing 5.7 millimeters of 

precipitable water at a temperature of 79°F. 

663 
Fig. 6 COz weighting functions for passbands 20 cm" wide about center frequencies labeled 

in the figure. 

Fig. 7 Mid-Level Penetration of Wet Microburst with T207 Research Aircraft. 

Fig. 8 MB#l; Variations of Vertical Motion (w), Horizontal Winds (V'), Temperature (Ts), 

and Radiometric Temperature Difference (ATR) During a Wet Microburst Penetration 

(see text for explanation and discussion). 

Fig. 9 MB#1 Cross-Section of Flight Paths and Vertical Motion Field (w) With Respect to 

Distance (2) in km from the Initial Point at z z 550 m. The mean (layer) environmental wind (V'(C)] and the MB translation velocity at mid-levels is labeled dong with 

the depiction of heavy (HP) and Light (LP) precipitation. The lower graph shows the 

variability of the hazard factors F and F' dong the flight path (see text for further 

explanation). 

Fig. 10 MB#2 Variations of Vertical Motion (tu), HorizontaI Winds (VH), Temperature (T,), 

and Radiometric Temperature Difference (AT) During a Wet Microburst Penetration 

(see text for explanation and discussion). 

Fig. 11 MB#2; See Figure 9 and text for explanation. 

664 
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675 
Status of Colorado State Universities' IR Research 

Questions and Answers 

Q: DAVE HINTON (NASA Langley) - You discussed a microburst penetration technique 

for your Cessna that involved lowering the nose to increase or preserve airspeed, then 

trailing off this airspeed for potential energy at low altitude. I can understand doing this 

during intentional research penetrations begun at reasonable altitudes, but I am skeptical 

that this could be safely performed in an inverted encounter at low altitude, say 100 or 200 

feet AGL. Are you advocating a pitch down technique for general aviation pilots? 

A: PETE SINCLAIR (Colorado Stare University) - Yes. For inten 

down-drafts of greater than 7 to 10 meters per second. The amoun 

course, will depend on the magnitude of the down-draft and the altitude above ground 

level. 

Q: DAVE HINTON (NASA Langley) - Have you conducted any piloted simulation studies 

to determine the acceptability and viability of this procedure for GA pilots of average skill? 

A: PETE SINCLAIR (Colorado Stare University) - Not yet, but I plan to enter our 

measured wind profiles into a flight simulator for development of GA flight procedures. 

ROLAND BOWS (NASA Langley) - It amazes me that people don't understand that you 

descend when you lower the nose of an airplane. It also Surprises me that we talk about 

airspeed loss, dynamic pressure, forces on big lifting surfaces of 20 to 30% and realize that 

there is still the factors of 2 in lift coefficient by just getting the wing bite into the relative 

wind in the right way. It's not a very simple problem. 

WAYNE SAND (NCAR) - I guess I have to respond a little bit. There is some foundation 

to what Peter is saying in this whole thing. It's a technique that actually has been proven 

by the sail plane people. They do this all the time to deal with rotor clouds when they're 

doing wave flights and all that sort of thing. The way they deal with it, to get through there 

as quickly as possible with the least altitude loss possible, is to go fast and to get the nose 

down. So I think that's the foundation for a lot of what he's saying and what he's trying to 

suggest. I think it's a long ways from proving that's the right way to do it. One of our 

people has gone through some calculations on that with this sort of thing in mind and 

actually came up with the same conclusion that you're probably better off in a light plane to 

get through there as quickly as you can however you do that, providing you have the 

ground clearance and all that sort of thing. I'm certainly not to the point of advocating that 

yet either. It is something to think about and it's one of the points that I think should be 

addressed. 

ROLAND BOWS (NASA Langley) - Sail planes don't have engines on them. One of 

the fmt rules is to get the thrust above the horizon. 

UNKNOWN - Being both a sail plane pilot and a general aviation commercial sector pilot, 

I was just going to emphasize that in the sail plane arena the only option he's got to increase 

his forward speed, and therefore minimize the time in the shear, is by lowering his nose. 

That's the reason why we do that. However, in our sector, particularly the commercial 

sector, you have other options available. I think that Peter's goal is certainly worthwhile 

and that's to minimize the time in the shear. I think we can all agree that's a worthwhile 

objective but whether you lower the nose and go for the ground in order to do that or not is 

probably worth discussing. 

676 
DAVE HINTON (NASA Langley) - I'm also a sail plane pilot and I also understand 

wanting to put the nose down to get out of the sink as quickly as you can. But what works 

at 3000 feet may not 

procedures knows, yo 

there are other factors 

30. As anybody that has done any research on recovery 

simply go for the optimal re technique and say fly it, 

677 
678 
Session X. Airborne Doppler Radar / Industry 

PRKE LANK NOT FBLM 679 
680 
4 

Session X. Airborne Doppler Radar / Industry 

Status of General Motors Hughes Electronics Research 

Dr. Brian Gallagher, Delco 

Mark Selogie, Hughes 

681 
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DESIGN CONSIDERATIONS FOR AN AIRBORNE 

WENDSHEAR DETECTION RADAR 

Hughes Aircraft Company 

An airborne radar can be used to provide reliable forward 

looking windshear detection. The radar uses a direct measure of 

wind velocity to determine the hazard F-factor and issue a warning 

to the pilot. The radar measures wind velocity as a function of range 

and determines the presence of windshear if there is an abrupt 

change in wind direction over a short range interval. This change in 

wind direction is recognized by the radar as a distinct S-shaped 

curve in the range-velocity domain. The NASA windshear simulation 

has been used to verify the radar's ability to detect this S-shaped 

winds hear curve. 

In order to provide a useful alert to the pilot, the radar must 

provide at least 15-20 seconds of warning and provide this warning 

with a very low false alarm rate. In addition, the radar must have 

adequate range to penetrate the ' windshear to enough depth to 

discriminate dangerous shears from benign shears. Scan-to-scan 

correlation logic may be employed to lower the false alarm rate. The 

overall design issues involved in specifying a radar to detect 

windshear include its frequency, transmitter power, antenna 

beamwidth, coherent doppler processing, range resolution and 

interference rejection. 

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711 
Status of General Motors Hughes Electronics Research 

Questions and Answers 

Q: SUSAN KIM (Boeing) - You mentioned your goal is a targeted false alarm/nuisance 

rate of 1 per 10,OOO flight. How do you plan to test/verify/achieve this rate? 

A: BRIAN GALLAGHER (Delco) - We plan to achieve the rate through the discrimination 

techniques that we are developing which primarily rely on the horizontal temperature 

gradient. For example, angular size would be an important means of discriminating cold 

fronts, gust fronts, things that are non threatening. As far as verifying that, or testing that, 

that's a good question. I'll give you a pat answer. This is per discussions that we had 

with the FAA Los Angeles Certification Office. The answer is primarily through systems' 

simulations with "sufficient data to support the integrity of the simulation model." The 

question is what is sufficient data. And that data will be collected through flight tests and 

in-service evaluations that are being planned. 

Q: SUSAN KIM (Boeing) - How do you define a false alarm? 

A: BRIAN GALLAGHER (Delco) - Another word for a false alarm is a false alert. It's an 

alert which occurs when the design wind shear threshold conditions do not exist. An 

example that I could give is an atmospheric temperature merit that emulates or masks or 

emulates a microburst without any turbulence whatsoever. Those things do exist out there 

and as a result we're going to have noriperfect systems. 

712 
Session X. Airborne Doppler Radar / Industry 

Saberliner Flight Test 

Bruce Mathews, Westinghouse 

713 
714 
- 

Sabreliner Flight Test 

for 

Airborne Windshear Forward Looking Detection and Avoidance 

Radar Systems 

Bruce D. Mathews 

Senior Engineer 

Westinghouse Electric Co. 

Electronic Systems Group 

Radar Systems Engineering 

Baltimore , Md. 

Abstract 

An important aspect in the design of an airborne radar for low level 

windshear avoidance is the false alarm/alert rate. To be used and trusted by 

pilots, any indications and/or displays of false hazards must be infrequent. A 

"clean scopem design aims to preserve detection performance and eliminate 

distracting false alarms. For lookdown radar, urban discretes and ground moving 

vehicle traffic dominate the false alarm design problem. Depending upon their 

relative location, spatial extent, and relative amplitude, these returns will 

compete with microburst windshear observables and may furnish false alarm 

candidates. 

Westinghouse conducted a flight test with its Sabreliner AN/APG-68 

instrumented radar to assess the urban discrete/ground moving vehicle clutter 

environment. Glideslope approaches were flown into Washington National, BWI, and 

Georgetown, Del. airports employing radar mode timing, waveform, and processing 

configuration plausible for microburst windshear avoidance. The perceptions, 

both general and specific, of the clutter environment furnish an empirical 

foundation for begining low false alarm detection algorithm development. 

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P 753 
Saberliner Flight Test - Questions and Answers 

Q: ERNEST BAXA (Clemson University) - Can you comment on clutter spectral 

characteristics of the Washington, DC overflights? Do you feel that urban clutter will be 

distinctly differed from non-urban? 

A: BRUCE MATHEWS (Westinghouse) - The term "clutter spectral characteristics" to me 

or to Westinghouse Airborne Radar people means strictly a geometric Doppler sense. So it 

is really the amplitude distribution of Rayleigh scatterers geometrically in a range gate that 

sets up the Doppler spectrum for them What did I expect the 

urban clutter to look like? It was pretty much what we expec 

distribution of urban clutter that makes it confounding and that s 

urban clutter. 

Q: WAYNE SAM) (NCAR) - What did you leam from these flight tests? Can you 

maintain a clear screen in these environments? 

A: BRUCE MATHEWS (Westinghouse) - We are still looking at that data so I can't really 

comment very much further on that. 

7s4 
/ 

Session X. Airborne Doppler Radar 1 Industry 

Status of Ben& Research 

Daryal Kuntman, Bendix 

755 
DOPPLER WEATHER RADAR 

WITH 

PREDICTIVE WINDSHEAR DETECTION CAPABILITY 

DARYAL KUN~N 

BENDIX/KING AIR TRANSPORT AVIONICS DIVISION 

OCTOBER 18, 1990 

768 
WE ARE ... 

A DIVISION OF ALLIED-SIGNAL AEROSPACE COMPANY WHICH IS 

A PART OF ALLIED-SIGNAL CORPORATION. 

HAVE BEEN ~NUFACTURING AIRBORNE WEATHER RADARS SINCE 

1954. 

HAVE THE MOST RADARS (OVER 35,000 DELIVERED) ON AIR 

TRANSPORT TYPE AIRCRAFT FLYING WORLDWIDE. 

COMMITTED TO THE DEVELOPMENT OF AIRBORNE WEATHER RADAR 

WITH FORWARD LOOKING PREDICTIVE WINDSHEAR DETECTION 

CAPABILITY. 

757 
BENDIX/KING ATAD RADARS 

IN CURRENT AIRLINE FLEETS 

- RDR-1E: MAGNETRON TRANSMITTER NOT SUITABLE FOR WINDSHEAR 

DETECTION 

- RDR-1F: ~GN~RO~ TRANSMITTER NOT SUITABLE FOR WINDSHEAR 

DETECTION, 

- RBR-4A: LATEST GENERATION 

SOLID-STATE TRANSMITTER 

TU LLY COHERENT 

DOPPLER TURBULENCE DETECTION CAPABILITY 

768 
a 

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759 
PLAN 

- TO ADD WINDSHEAR DETECTION CAPABILITY TO THE RDR4A SYSTEM AS A MODIFICATION. 

- CONDUCT FLIGHT TESTS WITH AIRLINES DURING 1991. 

760 
MODIFICATIONS 

RECEIVER/T~NS~ITTER : - ADD WINDSH~R DETECTION HARDWARE 

AND SOFTWARE 

0 ADD WINDSHEAR MODE CONTROL SOFTWARE 

- ADD WINDSH~R DATA TO THE OUTPUT 

BUSES 

CONTROL PANEL: ADD WINDSHEAR MODE SELECTION CAPABILITY 

I NDI CATOR: ADD WINDSHEAR DATA DISPLAY CAPABILITY 

ANTENNA: NO MODIFICATIONS REQUIRED 

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763 
RDR-4A CHARACTERISTICS 

WEATHER TURBULENCE WINDSHEAR 

AND DETECTION DETECTION 

MAP MODE 

125 W (NOMINAL) 

6 AND 18pSEC 6ps~C 2pSEC 

ALTERNATING 

380 Hz 1600 Hz 6000 Hz 

320 NMILES 40 NMILES 10 NMILES 

PULSED COHERENT 

9345 + 2 MHz 

5 DB 

180" I 40" 

35 DB 

3.3" ELEVATION 

3.4" AZIMUTH 

764 
ISSUES 

TECHN I CAL : - GROUND CLUTTER ELIMINATION 

- ESTABLISHMENT OF HAZARD THRESHOLDS 

- DEFINITION OF DISPLAY DATA BUS 

CHARACTERISTICS 

- SPECIFYING DATA INPUT REQUIREMENTS 

- DEFINITION OF FORM/FIT/FUNCTIONAL 

REQUIREMENTS (ARINC) 

OPERATIONAL: 0 MEANS OF SELECTING WINDSHEAR MODE 

- DISPLAY MEANS 

- AURAL ALERTS 

- INTERACTION WITH REACTIVE 

W I NDSHEAR DETECTION SYSTEM 

CERTIFICATION: - ESTABLISHMENT OF A CERTIFICATION 

CRITERIA SIMILAR TO THE REACTIVE 

WINDSH~~ DETECTION SYSTEM 

765 
4 " . 

;.. 

ESSENTIAL REQUIREMENTS FOR CERTIFICATION 

WITHOUT EXTENSIVE FLIGHT TESTS 

- ESTABLISHMENT OF PERFORMANCE CRITERIA USING SIMULATED 

DATA (NASA) 

- DEFINITION OF TEST MEANS USING SIMULATED SIGNAL INPUTS 

(NASA) 

- MINIMUM OPERATIONAL REQUIREMENTS (RTCA) 

- TSO (FAA) 

- ADVISORY CIRCULAR FOR AIRWORTHINESS AND OPERATIONAL 

APPROVAL (FAA) 

788 
Session X. Airborne Doppler Radar / Industry 

Status of Collins Research 

Roy Robertson, Collins 

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Status of Collins Research - Questions and Answers 

Q: PAUL KELLY (21st Century Technology) - Given the fact that at lower altitudes radar 

is most susceptible to ground clutter effects and given the fact that microbursts are 

frequency wet at higher altitudes and dry at lower altitudes, it is obvious that a Doppler 

based system shows its greatest weakness in the zone in which the information from it is 

most critical for flight safety. Given the cost of a shear alerting system, airline decision 

makers will have to be very pragmatic in evaluating competing systems. Does this not 

illustrate a great need in the industry for some mechanism for codifying and indexing 

prediction effectiveness on a qualitative and quantitative basis to provide a tool for decision 

makers in system selection. 

A: ROY ROBERTSON (Collins) - The answer is yes. You are correct, the tendency is 

that radar do act in the direction which you say, low altitude, dry microburst, are difficult 

environments for the radar to operate. However, I will not say that the radar would be 

ineffective. We, frankly, are optimistic that radar will still be quite effective in that 

environment. Your question about the indexing and coding, or method of categorizing the 

effectiveness of different systems, is a very complicated question. It's the combined effort 

of everyone at this review meeting to try to determine what effectiveness is and how 

effective individual sensors are. That involves defining the environmental set as well as the 

performance of individual sensors. That requires a great deal of data. Analysis can only 

take that question so far. So until a body of experience is gained on individual predictive 

sensors, that question cannot be answered. The likely result is that different sensors will 

excel in different areas. Then it will be up to the airliie to perceive what individual 

propemes are more valuable to an airline and that will be different from one airline to 

another. 

PAUL KELLY (21st Century Technology) - There has to be some emphasis on 

categorizing the degree of effectiveness because we have to do something about giving 

airline management, which is where the bottom line is, some tool for evaluating competing 

systems. That's the bottom line that all of our discussions relate to and hence the criticality 

of our addressing this factor. 

ROY ROBERTSON (Collins) - I think that the sum body of knowledge arising from all 

this effort will certainly move in that direction. 

Q: PAUL KELLY (21st Century Technology) - Does the onus for such a code and 

indexing arrangement not fall on the FAA or is the FAA adopting the position that the 

initiative will have to corne from the industry and expecting the aviation industry to do what 

it did with the aircraft aging issue when the industry drew up the recommendations and 

presented them to Sam Skinner for signature? 

A: HERB SCHLICENMAIER FAA) - You're ahead of me Paul on what the industry 

did with Sam Skinner. What we've done in this area is as we've done before, work with 

the industry on what is perceived as a joint industry need. The rationale for the FAA 

getting together with NASA in the first place, first back in '86 and then again this fiscal 

year on the new agreement, was to formalize some sort of a smcture for conducting the 

research to look into the questions. But as Roy was saying before, there are some 

questions in this matter that need to be addressed that are not pertinent to government 

research. There is not that much expertise quite honestly, at least within the civil aviation 

side, for the marketing, development and cost effective maintenance and distribution of a 

piece of avionics into the civil aii carrier fleet. I have yet to brief the associate administrator 

for marketing in the FAA. Those kinds of decisions and questions need to rest with the 

780 
Boeings, Douglas, Lockheeds and their customer base. That has as much of an effect on 

the frnal design and decision of what the technology is and how it addresses the problem. 

78 1 
783 
Session XI. Airborne Doppler Radar / NASA 

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9 

Session X. Airborne Doppler Radar / NASA 

Clutter Modeling of the Denver Airport and Surrounding Areas 

Steve Harrah, NASA Langley 

V. Delnore, Lockheed 

R. Onstott, ERIM 

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To accurately simulate and evaluate an airborne Doppler radar as a wind shear 

detection and avoidance sensor, the ground clutter surrounding a typical airport must 

be quantified. To do this, an imaging airborne Synthetic Aperture Radar (SAR) was 

employed to investigate and map the Normalized Radar Cross Sections (NRCS) of the 

ground terrain surrounding the Denver Stapleton Airport during November of 1988. 

Images of the Stapleton ground clutter scene were obtained at a variety of aspect and 

elevation angles (extending to near-grazing) at both HH and VV polarizations. 

This presentation will discuss the method of data collection, the specific observations 

obtained of the Denver area, a summary of the quantitative analyses performed on the 

SAR images to date, and the statistical modeling of several of the more interesting 

stationary targets in the SAR database. Additionally, the accompanying moving target 

database, containing NRCS and velocity information, will be described. 

Denver Grou nd Clutter Obse rvations and Data Co llection 

Two years ago at the Williamsburg meeting, we described the ground clutter data we 

were hoping to obtain at Denver the following month. Well, the flight was a success, 

and now we want to describe the data and some of the analyses that we and the 

Environmental Research Institute of Michigan (ERIM) have done. 
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Basis for Studv ina Grou nd Clutter 

The motivation here is that we're developing a Doppler radar to be carried on the 

airplane, looking down along the glide slope, to detect wind shear. But there's a 

backdrop of ground clutter we must deal with. To suppress the effects of ground 

clutter, we have to understand its distribution, statistics, and characteristics. 

To do this, we flew a Synthetic Aperture Radar (SAR) at Denver -- not to detect wind 

shear, but to study ground clutter. What we learn about ground clutter from the SAR 

goes into a computer model of the airport environment as seen by the airborne 

Doppler radar. Les Britt will describe that to you in the next paper. 

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Radar's Eve View o f Airport 

Here's the approach to %-Left at Denver. 

You can see the runway, but look at all this other stuff around it: tall buildings, 

mountains, industrial parks, even moving stuff on these highways are railroads. 

All reflecting your radar beam and sidelobe energy back up to you, cluttering up you 

radar screen and increasing the difficulty of any discrimination scheme in your signal 

process0 r. 

This is what we're trying to sort out. We're not constructing a data base for a 

subtraction scheme, but instead trying to understand ground clutter so we can process 

it out in the general case. 

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J3-3 with SAq 

Here is the P-3, at Buckley Air National Guard Base, a few miles southeast of Denver 

Stapleton, on the morning we flew. 

We used an X-band SARI with its antenna mounted on the belly of a P-3 operated by 

the Naval Air Development Center. 

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SAR Swath Geo met ry 

This is the setup we used to map out the ground clutter. We flew several 

configurations, differing in depression angle and polarization. 

The P-3 is shown on the right, with the SAR looking out to its side, and mapping 

everything within this swath at a resolution of 3 m on the ground. 

The usual scheme got us out to a depression angle of about 5 degrees, but for a 

couple of passes we flew at a lower altitude (all AGL, of course), and got out to 3 

degrees. Reflectivity at these near-grazing angles is important, because that's what a 

real-aperture radar looking down a 3-degree glide slope will be seeing. 
801 
SAR Coveraae o f Denver Area. Part 1 

Here's a perspective sketch of the Denver area: The airport, downtown, the 

mountains, and Boulder; the marked areas on the ground show some of the areas we 

mapped. There are orthogonal looks at the same target area (the airport), and the 

mountain passes. 
803 
There are also 4 successive passes, each stepped about 2 1/2 miles over, and all 

looking in the same direction, so that we see each target at up to 4 different depression 

angles. 

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SAR lmaae o f Denver Area 

Here's some of the processed data: 

This is a false-color SAR image, rendered here in gray-scale, at 20 m ground 

reso I uti on. 

The image is corrected for range fall-off, but not normalized to any one depression 

angle, so what you're seeing is differences in reflectivity due to depression angle and 

to the target's characteristics. 

The airport is the dark area in the center, with its runway areas and passenger 

terminal. you can see buildings, highways, and lots of clutter sources. 

We've identified and cataloged the normalized radar cross section and depression 

angle of each type of target on several of these images, to model the stationary 

environment around Denver. 

And, using aerial photographs and lots of students, we've estimated the distribution, 

density, and speeds of car, truck, and train traffic along some of these highways, 

streets, and railroads. 

This gives us moving target information, which we feed into Les' model. 

808 

Statistical Analvses a nd . Ground Clutter Modeling s. D. Harrah. NASA Lanalev -. Research Center 

v Comments 

In order to realistically simulate and evaluate the performance of any airborne Doppler 

radar as a forward looking wind shear sensor, it is imperative to generate an accurate 

representation of the backscattered ground clutte Researchers at NASA LaRC 

have developed a robust airborne Doppler radar ion program, which generates 

a realistic radar I/Q signal from a complex scattering scene. This scene may consist of 

weather, stationary ground clutter, and/or moving clutter. The simulation program 

incorporates a Normalized Radar Cross Section (NRCS) ground clutter database as 

its source for the ground clutter signal. A Synthetic Aperture imaging Radar (SAR) was 

employed to measure the backscattered NRCS levels of the terrain surround the 

Denver Stapleton airport. It should be noted that, all the angles in this section are 

referred to as incidence angles. The classical definition of incidence angle is the 

angle measured from the surface normal. Since it is impractical to measure the mean 

surface normal for each ground cell, the incidence angle referred to here is measured 

from vertical for each ground cell. It should further be noted that, some authors prefer 

to use the complement of the incidence angle often called the depression angle. 

Ground Clutter Stat istical Modelina/AnalvsiS 

In this portion of the presentation, I would like to show some of the results of a 

statistical analysis performed on the Denver Stapleton ground clutter database. The 

purpose of this analysis may be divided into three categories. First, to validate the 

backscatter levels observed in the SAR images. Second, to determine any pertinent 

statistical information which would help in the modeling of ground clutter at high 

incidence angles. Third, to determine if any statistical properties existed in the Denver 

ground clutter database which would help in the discrimination of the backscattered 

ground clutter and weather signals. 

To achieve these goals, we analyzed the NRCS levels observed in the Denver ground 

clutter database to investigate incidence angle and polarization effects and to 

determine the utility of the spatial Normalized AutoCorrelation Function (NACF). In 

investigating incidence angle and polarization effects, we generated both full image 

and sub-image analyses. Some of the specific targets of interest, which we 

investigated were: the urban environment, isolated tall buildings, and scenes of the 

Rocky mountains. Some of the statistical parameters generated during the analysis of 

each image were: the dynamic range (minimum to maximum), the mean, and the 

variance, of the NRCS levels found in the Denver ground clutter database. 

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Denver StaD leton SAR lmaae HH Polarization) 

The next two SAR images are grey scale representations of the NRCS values obtain 

for the Denver Stapleton ground clutter scene. Each image has been calibrated, 

mapped from slant range to ground range, and corrected for range fall-off. The first 

image was obtained using HH polarization and the second used VV. The two images 

were recorded simultaneously using the ERIM SAR. Each image is comprised of 

thousands of cells, -20 m X 20 m, in size. The approximate total dimensions of each 

image and the near and far range incidence angles are reported on each image. 

810 

Note that , the two images are on a common grey scale; thus, allowing a direct 

comparison of the intensity for common areas in each image. Because of the rather 

large quantity of data in each image, %as well as, the large dynamic range of the NRCS 

values, I doubt that these reproduced images will be highly enlightening. Therefore, I 

would like to remind everyone that, a complete set of SAR images for Denver are 

available to anyone interested. This data can be obtained on a variety magnetic 

storage media and in almost any format. 

Although some differences can easily be seen in the two images, only through a 

statistical analysis can the differences be quantified. 
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Histoa ram of the Denver Star, leton SAR lmaaes 

This histogram clearly shows the distribution of NRCS values in the two images. The 

mean and the standard deviation for each distribution are spe d at the top of the 

plot. From this full image analysis it appears that VV polariz would produce a 10 

to 15 dB lower ground clutter return than would HH polarization. 

Often HH polarization is used in weather radars, since it gives a slightly larger rain 

return, typically a few dB. However, this occurs almost exclusively with large rain drop 

sizes, where the droplets flatten during their descent due to air resistance. But larger 

drop sizes also produces a larger signal, which in turn reduces the need for using the 

polarization sensitivity of rain. Since the 10 or 15 dB gained would out weight the 2 or 

3 dB lost, the largest Signal-to-Clutter Ratio (SCR) for this clutter scene would be 

achieved using VV polarization. 

Even though these statistics contradict the usual preference of HH polarization for a 

weather radar, we do nat contend that all wind shear radars be built using VV 

polarization exclusively. Which polarization should be used for wind shear detection 

and under what circumstances, is still an open question and will be investigated 

during our flight program. It should be reemphasized that the statistics shown here are 

for large images consisting of many different scattering types, at very high incidence 

angles, and are only necessarily representative of this one image. Some images may 

produce larger VV returns. Image composition is the prime factor for determining 

which polarization will produce the larger returns. 

Since image composition is the prime factor in determining polarization and more 

importantly in producing the larger SCR, full image analysis can only show the 

aggregate effect of all the scatterers over the entire image. In order to specify how 

each scattering type contributes, we divided each image into smaller nearhomogeneous sub-images on which we performed the same types of statistical 

analyses. Because of time, I would like to show you, only a small fraction of the many 

sub-image results we have obtained, for specific targets of interest. 

814 
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Scatte raram of Ta II Bu ildinas in the Den ver Swleto n SAR Imaw 

Tall buildings, such as those in an urban environments, are primary sources of ground 

clutter, since they offer a large physical cross section and are constructed of metal and 

concrete. Also, at incidence angles near-grazing, which would be typical of a wind 

shear radar during landing, the flat sides of a building will produce a near specular 

return. Typical NRCS values are shown in the scattergram as a function of incidence 

angle. These NRCS values were calculated for numerous, isolated, tall buildings 

present in the SAR images. 

This scattergram shows at least two important NRCS features of tall buildings. First, 

the influence of the incidence angle and the severity of tall building NRCS levels. 

Second, the insensitivity of the buildings in these images to polarization. In the case of 

the former, this plot shows that NRCS levels beyond the dihedral angle but 10' or 

more shy of grazing, produce little return. However, the NRCS can get quite large for 

near- dihedral or grazing incidence. The scattergram also shows that these buildings 

are polarization insensitive. So we might not gain any ground clutter suppression by 

choosing one polarization over another, for images (or environments) consisting of 

primarily tall buildings. 

Although Denver has a number of tall buildings, it should be noted, that these areas do 

not comprise more than 10% of the total SAR image. Thus one might immediately 

guess that natural terrain causes the polarization sensitivity. Although natural terrain 

does account for some of the polarization sensitivity, it is the rural and lightly 

industrialized areas which seems to make the majority of the contribution. 

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SAR lmaae o f the De nver Ce ntral Bus iness D istrict fC B D) 

The typical size and consistency of a sub-image is shown in this grey-scale 

representation of the Denver Central Business District (CBD). It should be recalled 

that, a sub-image consisted of primarilv one type of scattering category. However as 

often was the case, even small areas contained different type of scatterers; note the 

several highways crossing this sub-image of the Denver urban scene. 

The four westward-looking images of Denver, generated by four aircraft tracks each 

successively more westward, produced a unique situation. Since each image 

consisted of significant portions of the previously obtained image, it was possible to 

compare NRCS levels of the same sub-image at several different incidence angles 

(elevation) while maintaining roughly the same aspect angle. 

818 

Incidence Ana le Statistics of the Denver CBD S AR lmaaes .. 

For Denver's CBD we were able to extract three sub-images, each recorded using HH 

polarization and each covering a different incidence angle range. Statistics were 

developed for each of the sub-images individually. Shown here are the minimum, 

mean, and maximum NRCS values for the specific incidence angles occurring in each 

s u b-i mag e. 

The procedure used to develop these statistics is as follows. Each full image is 

analyzed and the location of the specific sub-image is determined. This portion of the 

image is electronically copied to a file along with its incidence angle information. Thus 

the statistics are representative of the the same ground area viewed at different 

elevation angles. Each sub-image is carefully examined to verify that it is comprised of 

the same location and number of cells as is in the other sub-images. Then the 

dynamic range and the mean NRCS for each row in each sub-image is determined. 

Naturally the mean and any other Calculated statistics are generated from their linear 

scale values rather than their logarithmic representation. Since all the cells in a single 

row are at the same incidence angle, we may plot these statistics versus the incidence 

angle for each row, to obtain the figure shown here. 

This type of graph shows the general trend in the specific clutter category (urban) as a 

function of incidence angle. The mean NRCS level is nearly constant across the entire 

range of incidence angles, increasing only -5 dB around 84'. Note however that, the 

dynamic range increases some 20 to 30 dB over the range of incidence angles. This 

information is of great use, for statistically modeling urban ground clutter. 

It might further be noted that, this complex, near-homogeneous urban clutter scene 

does not agree with the previous scattergram plot of isolated, tall buildings 

(comparing the mean NRCS with those in the scattergram plot). Although agreement 

is good at the lower incidence angles (-76' - 79'), where the contributions by tall 

buildings, as suggested by the scattergram plot, is roughly comparable with the mean, 

the strong NRCS levels of tall buildings at the higher incidence angles does not seem 

to affect the mean NRCS level significantly. Since each range bin of our radar 

footprint is much larger than the cell size used in the tall building clutter, we would 

expect to see NRCS levels more indicative of the mean level rather than the maximum. 
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statistics o f the Rockv Mountain SAR Imaa 

Another target of interest was the mountainous areas surrounding Denver. NRCS 

data was obtain of these areas in order to quantify the second-go-around returns from 

the mountains. This data was collected for both the "Thrust Feature" and the actual 

Rocky Mountains themselves. The plots show both typical NRCS levels and incidence 

angle effects for both types of scatterers. Specifically, the plots show that the only 

significant NRCS levels are contained in some of the "thrust feature" data; however, 

since these high levels only occur a low incidence angles, it is not likely that an 

aircraft's radar will encounter this "thrust feature". Furthermore, it should be noted that 

the "thrust feature" is a high, directionally dependent (aspect angle) scatterer and 

because of the aspect views obtained, the NRCS levels shown here should be 

representative of the largest levels that might be observed for these elevation angles. 

822 
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The mean NRCS levels, for each scattering category, contained in the Denver 

Stapleton ground clutter database are consistent with the few available sources of 

high incidence angle ground clutter data. This conclusion is based upon a literature 

survey and a comparison with previously obtained ERlM archived SAR images. 

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If a statistical model is incorporated into a computer simulation, rather than a direct 

measurement of actual NRCS levels, then the variance must be increased with 

increasing incidence angle. Although empirically derived formulae are often used in 

statistical models for NRCS ground clutter generation, these formulae typically Q& 

describe the variation of the mean NRCS level with incidence angle (i.e., they use a 

fixed variance). However, it is necessary to also incorporate fluctuations in the second 

moment statistic (the variance) as a function of incidence angle, if one is to produce a 

truly realistic, backscattered, ground clutter, radar I/Q sequence. 

We have found little or no useful levels of the 2-dimensional, spatial, Normalized 

AutoCorrelation Function (NACF) in the Denver SAR images. Although we have not 

shown the results of the investigation of the applicability of using a 2D spatial NACF, it 

should be noted that such an investigation has been pursued. There have been 

numerous hypotheses suggested, by myself and other researchers, for the failure of 

such a technique applied to the Denver images. However, 1 do a feel that I can 

elaborate on each hypothesis without showing some of the substantiating plots, and 

since it has been determined that this information would not be appropriate for this 

level of a technical conference, 1 will only report this conclusion without the 

substantiating information. 

A significant level of polarization sensitivity has been observed during full image 

analyses. However many of the sub-image analyses of the various targets of interest 

(primarily consisting of high NRCS ground clutter sources) have shown little or no 

polarization sensitivity. It appears that the primary factor determining a wind shear 

radat's polarization is the composition of the ground clutter scene. Different 

polarization configurations be necessary in an operational wind shear radar with 

the choice of polarization based upon the constituent scatterers surround an airport. 1 

believe this is a issue which will only be determined by experience, and at our next 

meeting I hope to be able to report our finding on this matter. 

A detailed inspection of the Denver ground clutter database has shown that rnanmade targets are the only sources of 

incidence angles. Natural targets, in general, offer very low NRCS levels compared to 

man-made targets at the same high incidence angles. Full image and sub-image 

analyses have been performed in order to isolate and coregister large NRCS sources, 

thus producing this result. 

The relative levels of backscattered signal returning as second-go-around from the 

mountainous terrain surrounding Denver should produce little effect on the 

performance of a wind shear radar. This too will be investigated during our 

experimental flights around Denver. 

NRCS ground clutter at near-grazing 
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For an airborne wind shear radar, removal of a stationary ground clutter signal may be 

accomplished quite simply, provided that an accurate aircraft velocity can be 

established. This is because stationary clutter produces a narrow, localized-velocity, 

spectral signature; thus, filtering only requires a simple notch filter to be implemented 

in the frequency domain. Moving clutter however can be spread across the entire 

frequency domain, producing multiple velocity modes within a single range bin. Also, 

as described earlier, these man-made targets can be a primary source of large NRCS 

levels. Simply stated, moving clutter can, and should be expected to, exist in nearly 

every range bin and produce a continually changing, high amplitude, clutter signal 

across the entire frequency domain, which makes filtering it, the most difficult problem 

facing an airborne wind shear radar. Although the situation may sound bleak, much 

progress is being made in this area and will be discussed by Dr. Les Britt in the next 

presentation. 

In order to investigate a variety of signal processing algorithms for moving clutter 

rejection, moving clutter databases, for the Denver and Philadelphia airports, were 

created. Also the additional functionality of incorporating moving clutter was added to 

the NASA airborne radar simulation program. To generate the moving clutter 

databases, it was necessary to measure certain pertinent parameters. First, all of the 

roads, highways, and railroad lines, which are to be incorporated, must be measured 

and coregistered with the SAR image database. Second, all of the various statistics 

which characterize moving clutter must be measured or analytically derived. These 

statistics must describe the spatial, RCS, and velocity distributions of the moving clutter 

image. 

826 
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Aerial Photogmphs of the Denver Stag&t.on Area 

Aerial photographs of the Denver and Philadelphia areas were examined to establish 

the locations of all the roads, highways, and railroad lines incorporated in the moving 

clutter database. This allowed coregistration of the moving and stationary clutter 

databases. In addition to "mapping out" each of the roads, several other parameters 

were estimated based upon the examination of these aerial photos. An estimate, of 

the number of cars, the number of trucks, and the mean speed for each vehicle type, 

was calculated for each road and highway included in the map. 

Based upon these measured parameters, a literature survey, and an intensive 

interrogation of the SAR images, a statistical model was developed for moving clutter 

in and around the Denver and Philadelphia airports. Using this model, a random 

sequence of 10,000 moving targets were generated and used in coordination with the 

NASA airborne radar simulation program. 

828 

Denver Movina Clutter RCS Mag 

Shown here is a graphical view of plllv one of the parameters, RCS, describing the 

moving clutter database. It might be noted that this plot only ws a few of the major 

roads and highways in the Denver area. In generating a m 

several parameters must be included, not just RCS. The entire parameter suite used 

in the simulation program includes: a spatial distribution, an RCS distribution, and a 

velocity distribution. 

clutter database 

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aerial ::ots and extracted sequences from the SAR images, it was 

determined that most traffic is distributed uniformly over small stretches of highway. 

Using the estimated density of cars and trucks for a specific section of highway, a 

uniformly distributed random sequence of cars and trucks were generated along that 

road. 

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~~~~v~~~~~er model uses log-normally distributed RCS. This is based primarily 

on measured observations in the €RIM SAR images of Denver, Philadelphia, and 

several other, archived, scenes. The RCS mean and standard deviation, respectively, 

used in our model for the Denver moving clutter was: 

Automobiles +4 & +2 dB 

Train Cars +10 & +2 dB 

Vdocitv Distributi * 

Based upon a lite%ure survey, it was determined that traffic velocity primarily follows a 

normal distribution. An estimated speed limit, based upon the type of road, was used 

as the mean velocity and the standard deviation was approximately given by 10% of 

the mean. It should be noted that this parameter must retain a directional quality, if an 

accurate Doppler signature is to be generated. More simply stated, the moving clutter 

model must have inwardly and outwardly directed velocities with respect to the radar 

radial (i.e., positive and negative velocity components). 

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These two histograms show a statistical summary of the RCS and velocity distributions 

found in the Denver moving clutter database. Note the mean and standard deviation, 

for each distribution, is shown at the top of each plot. These histograms represent full 

image statistics and are generated from over 10,000 moving targets located in the 

database. Also, the velocity distribution contains moving targets from both interstate 

highways and residential streets; thus, it is not necessarily representative of the 

velocity profile on a single street or highway. Note also that, the velocity distribution is 

in fact representative of the magnitude of the velocities within the database. As 

mentioned on the previous page, for an accurate radar simulation the Doppler 

signature, in a given range cell, will almost always contain both positive and negative 

velocities (frequencies). 

833 
2.5 I 

-3 -2-1 0 12 3 4 5 6 7 8 9 1011 

RCS (d8) 

DENVER MOVING CLUTTER DATABASE 

VELOCITY DISTRIBUTION 

p = 29.6 m/s AND u = 23.6 m/s 

2.5 

2 

0 

b2 

1.5 

1 

0.5 

0 

20 25 30 35 40 0 5 10 15 

VELOCITY (M) 

833 
In summary, the benefits of this research can be separated into two categories, 

general "scientific" knowledge and wind shear radar specific "engineering" 

information. 

Scientific Benefits: 

To my knowledge, this data represents the first, nonclassified, consistent, very high 

incidence angle, NRCS ground clutter measurements. Additionally, since the 

measurements were obtained using a fully polarimetric, high resolution SAR, the 

NRCS levels in each ground clutter cell are representative of nearly homogeneous 

scatterers. This allows a measure of the true polarimetric properties of a single 

particular scatterer. 

!%?~k?f~~?t%e analyses have helped in producing design considerations for 

the NASA Wind Shear Radar. A few of these are: the need for HH and VV polarization 

capability to further study polarization and clutter suppression techniques, identification 

of man-made targets as the only major source of large radar cross section has help in 

lowering the fear of perpetual radar receiver saturation, and mountain clutter should not 

produce a significant second-go-around clutter signal thus reducing the necessity for 

special hardware and software processing algorithms. 

Also the incorporation of realistic, high incidence angle, stationary and moving ground 

clutter data, into the simulation program has lessened the need for modelling. Which 

can only improve the accuracy and increase the realistic performance of the backbone 

of this program, the NASA airborne Doppler radar simulation program. 

I would like to take this opportunity to remind everyone that, any of this data can be 

made available, on a wide variety of media and formats, by contacting: 

E. M. Bracalente, V. E. Delnore, or S. D. Harrah 

NASA Langley Research Center. 

834 
a 

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W 

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YO 

835 
Clutter Modeling of the Denver Airport and Surrounding Areas 

Questions and Answers 

Q: BRUCE MATTHEWS (Westinghouse) - NASA is and has been collecting an 

impressive amount and breadth of clutter data. Does this data conform to expectations as 

available from the literature? 

A: STEVE HARR4.H (NASA Langley) - I guess the answer is yes in that what we can 

compare it with we do get good agreement. However, there is a disparity in the models for 

very high incidence angle radar cross sections of different ground clutter types. With that 

in mind one has to be careful in just saying yes we agree with literature because literature 

states two or three different answers. We picked the right one. 

Q: BRUCE MATI'HEWS (Westinghouse) - Analytic models of various classes of 

scatterers, such as grass, forests, etc., as functions of grazing angle, wave length, etc. 

exist and can serve adequately in many, perhaps not all, purposes. Why has NASA chosen 

an empirical data bank approach rather than connected patches of analytic models? 

A: STEVE HARRAH (NASA Langley) - First of all there is some disparity or 

disagreement among the different models. Secondly and possibly even more importantly, 

we're trying to account for all of the interactions between, say, cars, trees, grass and 

different things that one would actually see in the actual operation of a radar. If you simply 

associate a certain ground patch with grass and another with cars, you can get back the 

right cross section for each one of them, if they were individual and isolated, but not 

necessarily show the effect of trees on cars or cars on trees and so forth. So, you don't get 

all the multipath and all the complicated scattering that would go on if you simply use a 

analytic approach. From that standpoint the empirical does give us a vexy realistic look or 

interpretation of the data, what's actually on the ground. Secondly, the ground areas that 

we've been looking at are on the order of 10s of kilometers in both down range and cross 

range direction. It's very difficult to model that amount of data. 

EMEDIO BRACALENTE (NASA Langley) - I want to add just some more to that 

question. Of course one of the things we were primarily concerned about was the urban 

type clutter around airports and the analytic models associated with buildings, urban 

environments, and the automobiles along the highways, at grazing angles or low 

depression or high incidence angles. This is not covered very much in the literature and 

very difficult to develop analytically. So we felt the only way to really be able to develop a 

high resolution small area set of individual scatterers representative of urban clutter was to 

actually take real data and form map, so that when you look at it with a full apexture antenna 

you sort of collect up a set of multiple scatterers within your beam that are representative of 

what the radar might see when it was looking at an actual urban clutter environment. That 

was probably one of the main reasons why we went out empirically rather than trying to do 

it analytically. In fact we had some effort under way looking at it analytically and it becarne 

pretty complicated and difficult to model every little patch in that way because of the lack of 

data. 

836 
Session X. Airborne Doppler Radar / NASA 

Radar Simulation Program Up-grade & Algorithm Development 

Charles Britt, RTI 

837 
838 
Y 

RADAR SIMULATION PROGRABS 

UPGRADE & ALGORITHM DEVELOPMENT 

CHARLES L. BRITT, PH.D 

Research Triangle Institute 

610 Thimble Shoals Blvd. 

Suite 203B 

Newport News, VA 23606 

NASA Contract NAS1-18925 

October 18, 1990 

839 
Radar Simulation 

This is a block diagram of the NASA Radar Simulation program 

which was discussed extensively at the previous meeting. The 

radar simulation program is a comprehensive calculation of the 

expected output of an airborne coherent pulse Doppler Radar 

system viewing a low level microburst along or near the approach 

path. Inputs to the program include the radar system parameters 

and data files that contain the characteristics of the 

microbursts to be simulated, the ground clutter map, and a 

discrete target data base which provides a simulation of moving 

ground clutter. 

discussed previously. 

For each range bin, the simulation calculates the received 

signal amplitude level by integrating the product of the antenna 

gain pattern and the scattering source amplitude and phase of a 

spherical shell volume segment defined by the pulse width, radar 

range and ground plane intersection. A series of in-phase and 

quadrature pulses are generated and stored for further processing 

if desired. In addition, various signal processing techniques 

are used to derive the simulated velocity and hazard measurements 

and stored for use in plotting and display programs. 

The data bases used in the simulation have been 
I RADAR SIMULATION I 

Radar Parameters 

Antenna Patterns 

A/C Pos., Microburst Pos. 

Calculate ~ Microburst 1 

Rain Return Data Base 

Calculate ]Clutter Map1 I 

J 

Clutter Return Data Base 

1 I 

Discrete Target ~-1 DataBase I J 

Add System 

1 Calculate I 

I & Q Pulses 

Simulated AGC & 

A/D Quantization 

Store Raw 

Radar Data 

Signal 

Processing 

I I 

Signal Levels 

Clutter Levels 

Derived Velocity 

Shear Hazard Index 

Turbulence 

Doooler Soectra 

(Autoregressive Model Coeff. 

841 
Airborne Doppler Radar Detection of Microburst Windshear 

using the radar simulation program. 

slope encounters a microburst on the path between the aircraft 

and the touchdown point. This situation has been selected 

because it provides the most severe clutter environment for the 

radar. 

This view graph shows the situation that has been simulated 

An aircraft on the glide 

842 

Measured Wind Velocity 

The following view graphs indicate examples of the outputs of 

the radar simulation program. Vi hows the measured wind 

velocity plotted versus range-to-touchdown for pulse-pair and spectral 

average processing. In addition, the "true" wind velocity is plotted 

for comparison. 

844 
x 

c 1. 

841 
Hazard Factor Vs. Range 

View Graph 4 provides another example of the simulation 

output. In this case the hazard factor is plotted versus range 

for both pulse-pair and spectral average processing. In 

addition, true hazard factor and the total hazard factor is 

plotted. The total hazard factor includes the vertical component 

of the hazard factor calculation (the vertical component is not 

measured by the radar). 

848 
4 

I 

9 

0 

I 

I? 

0 

I 

847 
Windshear Radar Display 

produced by the radar simulation program. 

of radar measured velocity and hazard index are shown. The 

hazard index display clearly shows areas in which the hazard 

index exceeds a given value. 

View Graph 5 shows the examples of simulated sector scans 

A false color display 
849 
Simulation Improvements 

program that have been accomplished since the last manufacturers 

meeting. The major topics to be discussed in the talk include the 

development of the hazard detection, characterization and threat alarm 

algorithms and the completion of the hazard display and alarm simulation. 

View Graph 6 lists the major improvements to the radar simulation 

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851 
Windshear Radar Alarm Algorithms 

View graph 7 indicates the requirements that the windshear 

radar alarm algorithms must meet in order to provide an alarm to 

the aircrew. These requirements include detection, characterization of the hazard and evaluation of the threat to the 

aircraft. 
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853 
Detection of Hazard 

View graph 8 indicates the techniques and algorithms used in 

the simulation (and to be used in the NASA experimental weather 

radar) to detect a hazardous windshear situation. 

854 
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855 
Weighted Least Squares Hazard Estimator 

View graph 9 is a sketch indicating how the weighted leastsquares hazard estimation algorithm estimates the slope of a 

series of velocity measurements in adjacent range bins. The 

slope of the velocity/range line is proportional to the 

horizontal component of the hazard factor. The measurements that 

are used to estimate the least squares line are weighted by the 

spectral width. 

large spectral widths are associated with measurements that 

contain extensive moving ground clutter and therefore may not be 

accurate measurements. Weighting the individual velocity 

measurements in this way tends to improve the estimate of the 

true hazard. 

It has been observed through simulation that 

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857 
Characterization of Hazard 

View Graph 10 indicates the techniques used to characterize 

the hazard detected by the radar. The size and the centroid of a 

hazardous area detected by the radar are computed and the centroid 

is tracked by the radar. An extensive set of track-while-scan 

algorithms eliminate many false hazard ar s due to moving ground 

clutter by elimination of hazardous areas ess than a threshold 

area and by assuring that a hazardous area exist over several 

radar scans. This set of algorithms tends to eliminate many 

false hazard areas (false alarms) due to moving and stationary 

ground clutter. 

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859 
Threat Evaluation 

After a hazardous area has been detected and tracked, a 

time-to-closest approach to the aircraft (TAU) is calculated and 

an alarm to the aircrew is given if the time-to-closest approach 

is less than a threshold value. 
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861 
Display, Tracking and Alarm Program 

This is a simplified block diagram of the display, tracking 

and alarm program that is used to provide the map displays and 

simulated windshear alarms. The program uses the data generated 

by the radar simulation program discussed previously. The 

program implements the algorithms discussed. 
DISPLAY, TRACKING & ALARM PROGRAM 

Data from radar 

simulation program 

Find 

Track-w h ile -scan 

algorithms 

Time-to-Closest 

I Display & Sound1 

Alarm 

863 
Windshear Hazard Display 

This is a windshear hazard display generated by the display 

tracking and alarm program. When all criteria have been met for 

a hazard alarm, "SHEAR HAZARD" is printed on the screen along 

with a red ball to indicate the hazard area on the map. A 

dynamic simulation of this hazard display will be shown on the 

computer monitor. 
865 
Future Efforts 

This view graph indicates some of the efforts that will 

conducted in the near future. With the development of the NASA 

experimental radar system it is expected that real ground clutter 

data will be obtained and will be used in the simulation program 

in place of the existing ground clutter models. 

algorithms will be developed, such as auto-regressive modeling 

techniques, and will be investigated using the simulation 

program. 

estimation of the vertical component of the hazard index and the 

incorporation of this component in the alarm algorithms. 

Many alternate 

Additional work is being done to determine a technique for 

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867 
868 
Session X. Airborne Doppler Radar / NASA 

Signal Processing Techniques for Clutter Filtering & Wind Shear Detection 

Dr. Ernest Baxa, Clemson University 

M. Deshpande, VIGYAN Gorp. 

869 
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870 

1 
Signal Processing Techniques for Clutter Filtering and Windshear 

Detect ion 

E. G. Baxa, Jr., Clemson University 

ABSTRACT 

It has been argued that the windshear hazard factor is a 

sufficient statistic for detecting hazardous windshear conditions. 

The hazard factor is ccrnputed by estimating the spatial gradient 

of windspeed across the radar sector of coverage. With the 

airborne Doppler radar, one approach is to use estimates of 

windspeed within each range resolution cell as a basis for 

estimating this spatial gradient. Currently, research is directed 

at understanding how to obtain the best possible estimate of 

windspeed conditions within a range cell. Conventional pulse-pair 

processing obtains mean estimates of windspeed. The presence of 

strong ground clutter in a low altitude airborne radar return can 

significantly bias these mean estimates. One thrust of this 

effort has involved use of adaptive clutter rejection filters 

based upon auto-regressive modelling of the ground clutter 

returns. This offers the potential for using very simple finite 

impulse response digital filters to eliminate highly specular 

ground clutter returns. For situations where the weather return 

is quite low, e.g., the "dry" microburst, clutter rejection 

filtering can reduce the weather return signal levels to the 

extent that the variance of the mean estimates is quite large. 

Research is involved with using mode estimates, i.e., estimates of 

the most probable windspeed, in each range cell in determining the 

hazard factor. An extended Prony algorithm is discussed. It is 

based upon modelling the radar return as a time series and appears 

to offer potential for improving hazard factor estimates in the 

presence of strong clutter returns. 

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873 
FINAL APPROACH SfTUATlON 

dry microburst 

5km 

Notes 

H U' 

u I! 

Simulated final approach situation with 

A/C on 3 degree glideslope and radar 

antenna elevated 2 degrees. Dry 

microburst in front of Denver runway 26R. 

data taken at Denver Stapleton airport. 

Gromd clutter return is based upon SAR 

Signal to clutter ratios are on the order 

of 0 dB in the range cells in which the 

microburst is present. 

874 
DRY MICROBURST 

T 

10th Order M Spe~t~n 

Notes 

Auto-regressive model determined spectrum 

in each of the fifty range cells with 

the simulated "dry1' microburst without 

any clutter present. Signal-to-noise 

ratios in the range cells with the 

microburst varies from 0 to 30 dB. 

Note: zero windspeed corresponds to zero 

Doppler relative to the ground speed 

of the aircraft. Positive windspeed 

corresponds to winds toward the aircraft 

and negative is away from the aircraft. 

Range cells are 150 m. 

875 
DOPPLER MEAN ESTIMATES 

weather only - mean estimates 

10th order 

0 10 20 30 10 50 

Notes 

Mean windspeed estimates considering 

simulated "dry" microburst without 

ground clutter. Five different mean 

estimates are used: 

1. pulse-pair computed in the time doma,n 

2. pulse-pair computed in the frequency 

domain using an AR spectrum estimate 

3. Fourier domain mean estimate 

4. AR spectrum domain mean estimate 

5. First order AR model pole estimate 

Note: The microburst appears in range 

cells 20-33 (approximately). Some 

estimates of mean have been edited 

to zero outside this range based upon 

estimated signal to noise ratio in return. 

il G 
loth order 

rk.rrrrm*ur 

f 

0 10 20 30 50 

rang. cell 

Notes 

Width estimates for the situation in the 

previous slide. Four different width 

estimators have been used: 

1. pulse-pair width computed in the time 

2. pulse-pair width computed in the AR 

3. AR spectrum standard deviation 

4. First order AR model coefficient 

domain. 

spectrum frequency domain. 

Note: Some width estimates for range cells 

outside those containing the microburst 

have been edited to zero because of low 

signal to noise ratio estimates. 

877 
DOPPLER WE EsTlMArrs 

weather only 

2nd order extended prony mode estimates 

2 largest modes 

ermmmuy fl&lkaaa 

-2 

-3 

0 10 20 30 so 

range cell 

data 111. 810719.da1 ualng wdel OROER 2 

aldth threshold 5.0 

otes 

i It' II 

Spectrum mode estimates using an extended 

PROM algorithm based upon a second 

order AR model of the data. Outliers 

are caused by insufficient model order. 

L: 
. -. I 

DRY MICROBURST IN amR 

I 10th Order AR Spectrum 

50 

AR model determined spectrum in each of 

the fifty range cells with the "dry" 

microburst and ground clutter present 

in the return. No clutter rejection 

filtering is used. Ground clutter in 

the range cells 40-50 in the negative 

Doppler region is associated with 

an interstate highway included in 

the simulation. Signal to clutter 

ratios are on the order of 0 dB. 

Note that the microburst can still be 

identified. 

R )f 

Notes 

879 
DOPFXER MEAN ESTIMATES W 

weather +clutter - mean estimates 

10th order model 

Notes 

Mean estimates without clutter rejection 

filtering for the situation depicted 

in the previous slide. The same five 

estimators used proviously are included. 

Again some of the mean estimates have 

been edited to zero based upon signal 

to noise ratio estimates of the return. 

Y 

I 

Note that the clutter biases the mean 

estimates in the range cells 20-33 

so that the presence of the mocroburst 

is no longer evident. 

r: 

880 
10th order extended prony mode estimates 

2 largest modes 

II 

3 

2 

2 

I 

0 

-3 J 

0 IO 20 30 10 5c 

range coil 

data filo Dlp7ll.dal using mod.1 ORDER IO 

I 

Notes 

Spectrum mode estimates using an extended 

PRONY algorithm based upon a tenth 

order AR model of the data. Only the 

two strongest modes within each range 

cell are retained. Outliers are 

caused by the presence of discrete 

clutter (e.g. interstate highway) 

Note that the microburst spectrum modes 

are clearly identifiable even though 

no clutter rejection filtering has 

been done. 

881 
DRY MICROBURST WITH omw amR FILTER 

II 10th Order AR Spectnnn li 

Notes 

AR model determined spectrum in each of 

the fifty range cells with the radar 

return pre-processed with an optimum 

clutter rejection filter in each range 

cell. The filter in each range cell 

is based upon a tenth order AR model 

generated FIR filter which is 

adaptively determined using simulated 

clutter-only data for the situation 

depicted earlier. 

Note the mocroburst is clearly present and 

some of the discrete clutter in later 

range cells is not completed eliminated. 

I I 

il 

882 
POST-FILTERED MEAN Esnwms 

optimally filtered clutter+ weather - mean estimates 

10th order 

0 io io io 

otes 

Mean estimates with optimum clutter rejectio: 

filtering. The same five mean estimators 

used previously are compared. Again 

some of the mean estimates have been 

edited to zero because of low signal 

to noise ratio estimates. 

Note that the microburst can be clearly 

identified. 

883 
PHASE NOISE EFFECTS ON amR FILTERING 

atopband width 181 -150 Hz. Am-70 dB 

1s 1 

IS 

a 

3 

-2 

-7 

-12 

0 00 0 os 0 IO 0 1s 0 20 0 2s 

Notes 

f tf 

Radar system pulse-to-pulse phase jitter 

is analyzed in the presence of the 

low signal to clutter ratio situation. 

zero Doppler with a stopband width 

of 150 Hz and 70 dB stopband attenuation 

is analyzed. The prefiltered signal 

to clutter ratio is held to -30 dB 

and the weather mean Doppler is varied 

from 100 to 250 Hz. As the phase jitter 

noise is increased the clutter spectrum 

is spread to the point that the rejection 

filter will not provide enough signal 

to clutter ratio gain for reliable 

pulse pair processing. 

Here an ideal notch filter centered at 

3 

884 
SUMMARY 

@ Charscterization of windspeed within 8 radar range resolution 

cell can be severely limited by ground clutter returns 

0 Low level weather returns will psmt tho greatest challenge in Hazard detectbn 

0 sigrrpl pr0aSSSing needs hlU& variety or algorithms 

md may rsquin, supercomputer proamsing lods for 

nt.l tim implemsntPtion 

Notes 

Y rc 

Characterization of ground clutter returns 

in initial flight tests will be of 

paramount importance. 

A suite of signal processing algorithms 

will be needed to improve confidence 

in hazard detection 

Airborne radar will be important for 

hazard detection but should be 

integrated with other sensor types. 
Bibliography 

1. E. G. Baxa, Jr. and J. Lee, "The Measurement of Windspeed 

Gradient with Low PRF Radar, "Proc. Southeast. Symp. on Sys. 

Theory, SSST-88, Charlotte NC, March 1988. 

2. J. Lee and E. G. Baxa, Jr., "Preliminary Analysis of Windshear 

Detection Signal Processing Considering Doppler Weather 

Radar," Radar Systems Laboratory TR No. 8, Research Triangle 

Institute subcontract 4-414U-3042 under NASA contract NAS1- 

17639, Clemson University, September 1988. 

Spectrum Estimation," Radar Systems L oratory TR No. 9, NASA 

grant NAG-1-928, Clemson University, December 1988. 

the Presence of Radar Oscillator Phase Jitter," Proc. 21st 

Southeast. Symp. on Sys. Theory, Florida State University, 

Tallahassee, March 1989. 

Estimating Spectral Moments of Meteorological Doppler 

Spectra," Proc. 21st Southeast. Symp. on Sys. Theory, Florida 

State University, Tallahassee, March 1989. 

6. W. T. Davis, "The Effects of Clutter-rejection Filtering on 

Estimating Weather Spectrum Parameters," Radar Sys. Lab. TR 

no.10, NASA LaRC grant NAG-1-928 and NGT-70055, Clemson 

University, July 1989. 

Transform - The STUSE Algorithm for Spectral Estimation,'' IEEE 

Trans. on Acoust., Speech, and Sig. Proc., vol. 37, no. 11, 

pp. 1763 - 1765 , November 1989. 

Doppler Weather Radar Applied to the Detection of Low Altitude 

Windshear," Radar Sys. Lab. TR no.11, NASA LaRC grant NAG-1- 

928, Clemson University, December 1989. 

9. B. M. Keel and E. G. Baa, Jr., "Adaptive Least Square Complex 

Lattice Clutter Rejection Filters Applied to the Radar 

Detection of Low Altitude Windshear," Proc. 1990 IEEE Int. 

Conf. Acoust., Speech, Sig. Proc., pp.1469-1472, Albuquerque, 

N.M., April 1990. 

Airborne Pulse Doppler Radar Signal Processing in the 

Detection of Hazardous Windshear" Radar Sys. Lab. TR no.12, 

NASA LaRC grant NAG-1-928, Clemson University, May 1990. 

12. J. Lee and E. G. Baxa, Jr., "Phase Noise Effects on Turbulent 

Weather Radar Spectrum Parameter Estimation," Proc. 1990 IEEE 

Int. Radar Conf., pp.345-350, Arlington, VA, May 7-10, 1990. 

13. E. G. Baxa, Jr. and J. Lee, "The Pulse Pair Algorithm as a 

Robust Estimator of Turbulent Weather Spectral Parameters 

using Airborne Pulse Doppler Radar," (submitted to IEEE Trans. 

on Aerspace and Elect. Sys.) , September 1990. 

3. E. G. Baxa, Jr., "Resolution of the STU Algorithm Used in 

4. J. Lee and E. G. Baxa, Jr., "Pulse-pair Spectral Estimates in 

5. W. T. Davis and E. G. Baxa, Jr., "Effects of Filtering on 

7. E. G. Baxa, Jr., "On Implementation of the Discrete Fourier 

8. B. M. Keel, "Adaptive Clutter Rejection Filters for Airborne 

10. J. Lee,"Analysis and Improved Design Considerations for 

886 
Estimation of Radial WindSpeed 

Manohar D. Deshpande 

Vigyan Inc., Hampton 

887 

Estimation of Radial WindSpeed: 

* From the I and Q data, the mtfm radial windspeed 

is determined using Covariance arid Spectral 

domain approaches. 

* Here we study the pcrforrnance of each of these 

techniques under varying signal to noise ratio. 

Covariance Met hod: 

If R(T) is the covariance function of the received A 

sequence then the mean Doppler frequency fd can 

be estimated by 

1 h Im . (R( Tr) * Arctan(- Re(R(Tr) fd Z 

2nTr 

The mean radial wind speed is then obtained as 

889 
SDectral Estimation Methods: 

If S(f) is the spectral density of the sequence 

then 6 can be estimated by using 

N/2 

S(fi)W(fi) 

i=-N/2 

where W(f) is the weighting function introduced to 

suppress the stationary ground clutter which is 

centered around zero Doppler frequency. 

The spectral density S(9 is determined using 

following methods. 

(1) Periodograni Method 

(2) Forward - I{ ac k wa r d Linear Predict ion 

Method 

(3) Eigenvector method 

(4) MUSIC Method 

890 
Thc pcrformancc of tficsc ii~c~lio~i~ when thc 

signal to noise ratio is v;iricd b~~irccri 10 dB to -5 

dB.is studied 

From these results it may lx concluded that 

Covariance method undcr severe SNR performs 

better than other mcthods. 

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912 
Airborne Radar Simulation Studies of the Denver July 11,1988 Microburst 

Charles Britt, RTI 

E. M. Bracalente, NASA Langley 

913 
914 
AIRBORNE RADAR SIMULATION STUDIES OF THE 

DENVER JULY 11,1988 MICROBURST 

E. M. Bracalente NASA Langley Research Center 

C. L. Britt, Research Triangle Institute (RTI) 

On July 11,1988 5 United Airline (UAL) aircraft had inadvertent encounters with a 

microburst that struck Denver Stapleton airport. Four of these aircraft 

experienced severe wind shear during final approach to 26LbR runways, and had 

to execute emergency missed approach recovery procedures to escape the 

hazard, barely avoiding a fatal accident. The question was asked, what would an 

Airborne Doppler Radar with wind shear detection capability had seen if it had 

been available on these aircraft. Would the radar have detected the microburst 

with sufficient warning time to allow the pilot to avoid the severest portlon of the 

microburst. To answer these questions a simulation stud was conducted using 

I: he July 11 microbur8t data base generated by the NASA Microburst Wind Shear 

Model (developed by Fred Proctor of MESO INC.) was used in the radar simulation 

along with the Denver statlonary and moving clutter maps described in the first 

presentation of this session. 

In the simulation program a wind shear detection Doppler radar was laced in 

UAL 395 and 236 aircraft and flown along their landln flight paths. fhe 

rameters, 

which will bo Qwcri &d later, ware used in the sirnulation. Output d splay information and wind 8hesr detection processing was produced as the aircraft 

approached the microburst. The following charts present information on the 

results of this simulation study. 

the Radar sirnulation program described b 6. L. Britt of K TI In the second 

resentation of this session (SESSION XI d: IRBORNE DOPPLER RADAR/NASA). 

microburst was placed at tho ap roprtate location an 8 intensity corresponding to 

each aircraft landln approach t P me. A baseline set of radar design p" 

915 
DENVER JULY 11 U-BURST AT TIME PERIOD D49 

lVELOClTY PLOT) 

The upper plot shows an X-Y horizontal cross sectlon, at 100 m altitude, of wind 

vectors for the mlcroburst (U-B) that struck Denver Stapleton air ort on July 11 

1988. The gray shade contours indicate wind speed (scale on le R ) In meters per second (m/s), and the arrows show wind direction. The wind direction vectors are 

shown every 200 m. The Y-axis runs north, the X-axis east. The lower plot shows 

a vertical cross section (altitude, Z vs X distance) through the U-B along the A/C 

flight path. The altitude resolution is approximately 80 meters. The down draft 

wind vectors and divergent outflow wind vectors at low altitude can easily be 

seen. 

The data for this plot was generated by the NASA U-B wind shear model. Actual 

measured meteorological data prior to the storm are used aa inputs to the model. 

The structure of the storm and wind fields resulting from the model, and shown 

here, compare ve close to the actual U-B that occurred on July 11, as confirmed 

from the A/C that encountered the storm. This plot is for simulation time D49, 

corresponding to the actual time associated with the position of UAL flight 395. 

The center of the U-B Is approximately 2.2 kilometers (KM) (1.2 nautical miles 

(NM)) east and .5 KM (.25 NM) south of runway 26L. The airport runways are 

indicated on the figure. The arrows in the U-B show the strong out flow divergence with severe velocity wind shear. 

The microburst intensity and location are shown here about a minute after it 

descended to the round at about the time UAL 395 was at 1200 feet approaehin 

runway 26L. UAL 95 Is shown in the fl ure as it apprOa~hO8 the storm 7 KM (3. 

NM) from touch down (TO) and 4.8 KM ( .6 NM) from the center of the U-B. 

Ap roximately one minute later UAL 395 was at the center of the storm and came 

to gain altitude and escape the U-6. 

by ground based x oppler radar, and reconstructed winds using recorder data 

# s 

wit PI in 75 feet of the ground and .5 miles short of the runway TD before it was able 

s 

916 

DENVER JULY 11 U-BURST AT TIME PERIOD D49 

1 REFLECTIVITY PLOT) 

This plot is identical to the D49 velocity plot exce t the gray shade contours 

ma or portion of the microburst outflow region the reflectivity levels range from 0 

to 1 0 Dbz. This microburst is considered a relatively dry microburst. The 

reflectivity levels are 3 orders of magnitude lower then the levels experlenced in 

the Dallas-Fort Worth microburst of 1985. These lower levels of reflectivity present a more difficult problem for the radar to detect especially in the presents of severe ground clutter. 

indicate the reflectlvity levels in Dbz that existed P n the microburst. Within the 

918 
0 
DENVER JULY 11 U-BURST AT TIME PERIOD D51 

JVELOCITY PLOT) 

This figure shows the velocity contours of the U=B 2 minutes later in its 

development from time period 049. At this time the storm has grown in size and 

intensity , as seen in the figure, and has moved slight1 east to 2.3 KM (1.2 NM) 

from the runway. The location of UAL 236 which was r ollowing behind UAL 395 is 

shown in the figure 4.5 KM (2.7 NM) from the U-B. One minute later UAL 236 was 

located near the center of the U-B approximately 2 KM (1.1 NM) from TQ and 150 

m (492 ft) above the ground before it began to gain altitude. A portion of a 

second smaller microburst can be seen NW of the main microburst. 

920 
P 

b 

0 

D 
DENVER JULY 11 U=BURST AT TIME PERIOD D51 

IREFLECTIVITY PLOT) 

This plot is identical to the D51 velocity plot exce t the gray shade contours 

major portion of the microburst outflow region the reflectivity has increased a 

little to levels ranging from 0 to 23 Dbz. 

indicate the reflectivity levels in Dbz that existed P n the microburst. Within the 
0 

0 

0 

d 

0 

0 

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RADAR BASELINE OPERATING PARAMETERS 

FOR HAZARD DETECTION 

Using the radar simulation program, a set of radar displays of the wind shear 

hazard that would be seen by a Doppler radar located on board UAL 395 & 236 a/c 

were produced. 

A set of arameters were chosen for the operation of the wind shear detection 

least squares hazard detection and hazard tracking a gorithms describe in the 

second presentation of this session were utilized in the simulation runs. In 

addition a variable antenna tilt was employed to keep the 3 Db point of the main 

beam hittin the ground 8 km in front of the aircraft. In the simulation program as 

sector every 3 sec., with the ra ar sampling a .5 to 5 km range in front of the 

aircraft. The data is processed to velocity and wind shear information. The 

horizontal hazard index (F-Factor) Is derived and tracked by the radar. If the 

hazard, area, and alarm thresholds are all exceeded an alarm Is sounded to the 

pilot. The next sets of figures show sample display8 of data generated by the 

radar, illustrating the effects of moving ground clutter and its reduction using 

antenna tilt. 

r 8 radar. T f: ese parameters are listed on the accompan ing chart. The wei hted 

the aircraft B s moved along the lide slope the antenna 18 scanned over a 42 deg. 8 

924 
925 
With the NC approx. 3.3 km (1.8 NM) from the center of the storm a velocity display as shown in this figure was produced. 

The radar is scanning +I- 21 degrees in azimuth, and covers a haif to 5 km range 

or approx. 60 sec in front of the NC. The velocity scale is show on the right in 

m/S. 

The negative velocities, in the dark region approximately 2 km from the a/c, are 

winds toward the NC i.e. head winds. These winds correspond to the leading edge of the U-burst, and are about -15 m/s (30 K). At a greater range near the 

center of the storm the horizontal velocity is zero as shown by the medium gray 

area. This is followed by the positive velocities corresponding to the outflow on 

the other side of the u-burst (+12 Wr). These produce tall winds to the NC. This 

sudden change in direction of wind flow at these magnitudes will produce a wind 

shear which will severely effect the performance of the NC. 

The radar can only measure the radial or horizontal outflow velocities from the Uburst. tt can not sense the down-flow velocity. This down-flow which is at a 

maximum at the center of the U-burst also produces a wind shear which effects 

the performance of the AIC. 

Also shown in thi ay, on either side of the U-B are a significant number of 

velocity contours cod by clutter returns from moving vehicles on the roads 

and interstates surrounding Stapleton air ort. The antenna in this case was set 

clutter returns. To reduce the clutter the antenna needs to be tilled up. A tilt of 

Is ahown in a later display. However, it is of interest to s88 how well 

threee weig d"B. ted least squares hazard algorithm would perform in detecting the U-B 

hazardous area in the prmence of this severe clutter. The next chart shows the 

results. 

at a 0 deg. tilt relative to tho glide slope. ph is tilt angle produces the worse case 

920 
-- QI 

w 

937 
RADAR HAZARD INDEX CONTOUR DISPLAY 

Before information is presented to the pilot the radar performs additional data 

processing to assess the wind shear hazard associated with any wind velocity measurements. 

This display shows contours of the horizontal wind shear hazard index 

associated with the previous wind speed measurements for an antenna tilt of 0 

deg. The hazard index relates the effect of wind shear on a loss in A/C 

performance. It is derived from the spatial rate of change in wind velocity, Le. 

wind shear in m/s per m, multiplled by the A/C velocity and divided by the force of 

gravity. The index is a measure of the spatial wind shear’s effect on the A/C 

erformance. Positive indexes indicate a loss of performance on the A/C. R egative indexes will produce a performance increase. If the total index - i.e. 

sum of the vertical and horlzontal component - exceeds a positive .1 over a 

large area or time interval, severe performance degradation will occur to the A/C 

and is considered hazardous if encountered at low altitudes. Wb see from this 

display, of the horizontal component alone, that a large area of hazardous wind 

shear exists about 3.3 km in front of the A/C. 

It can be noted from the display that very few hazard indexes where enerated by 

area near the center of tho U-8. 

tilted up. Tho next two dbplays show the result3 of tilting the antenna up by 3 

degthe movin ground clutter. The weighted least squares hazard algor B thm 

weighted t a em out. Unfortunate1 it also weighted out some of the U-B hazardous f o reduce this problem the antenna must be 

928 
s 

92 
RADAR WIND VELOCITY CONTOUR DISPLAY 

U-BURST D49: ANTENNA TILT = 3 DEG 

This display shows the velocity contours of U-B 049 at the same time interval as 

the previous velocity plot. In this case the antenna is tilted 3 deg. above the glide slope. Note, in comparison to the 0 deg tilt case, the significant reduction in the 

moving ground clutter si natures. Also a larger ortion of the U-B velocity 

produced by processing thk veloclty information. signature is discernible. B he next figure shows t R e hazard index display 

930 
931 
RADAR HAZARD INDEX CONTOUR DISPLAY 

U-BURST D49; ANTENNA TILT = 3 DEG 

This display shows contours of the horizontal wind shear hazard index 

associated with the previous wind d measurements for an antenna tilt of 3 

deg. In this case a much larger PO of the U-8 hazard area is produced. Note that two small hazard areas, near the outer portion of the display, are produced by the moving ground clutter targets that were not removed during the hazard 

algorlthm processing. 

After the radar identifies hazardous areas within a sc8n display it performs additional processing to 8ssesses the size and amplitude of these areas, tracks 

the hazardous areas, determines If the various thresholds have been exceeded 

and then provides a shear hazard warning to the pilot. A sample of a shear 

hazard warning display 18 8hown in the next figure. 

932 
933 
RADAR SHEAR HAZARD WARNING DISPLAY 

U-BURST D49: ANTENNA T1LT = VARIABLE 

During the simulation run the antenna was continuous1 scanned as the a/c was 

km) in front of the a/c. To minimize the clutter returns the antenna was 

continuousiy tilted up from the glide slope, as a function of a/c altitude, keeping the 3 Db point of the main beam hitting the ground 8 km in front of the aircraft. 

Positive horizontal hazard indices of .07 or larger that occur over an area of .65 

square Km (diameter of .9 km or flight time of about 10 seconds) or greater were 

set as thresholds for definin hazardous areas. The radar tracked the hazardous 

seconds of the NC’s approach. 

A sample of this type displa is shown in fhe ajoinin figure. The dark gray area 

hazard area, and a shear hazard warning has been sounded. At this time the pilot should begin his missed approach procedures. 

UAL 395 continued its landing approach until it actually entered the U-B before 

the pilot began his recovery and missed approach procedure. UAL 395 continued 

descending to 100 ft above ground level before the a/c was able to gain altitude 

and continue the misbed approach procedure. 

If UAL 395 had a Dopplor radar with wind shear processing capability on board 

the a/c, the pilot could have executed the missed approach procedure much sooner and avoided the tmverest part of the storm. 

A simuilar set of simulations were conducted on the flight of UAL 236 as it 

approached U-B DSl. A similar warning display was produced by the radar 40 

seconds prior to encounter. 

pro ressing along the glide slope. The radar continu J to process and evaluate 

the 1 azard threat and produced an alarm when the a/c was 40 sec (approx. 3.4 

areas and produced a shear 1 azard warning display if they occurred within 40 

In the display, at about 3.3 x M range, with the dark c B rcle indicates a severe 

Airborne Radar Simulation Studies of the Denver July 11, 1988 Microburst 

Questions and Answers 

Q: RUSSELL TARG (Luckheed) - At what rain rate does water bu 

perfomce of weather radar - red out? How will rain effect wind shear 

A: EMEDIO BRACALENTE (NASA Langley) - If the rain rate builds up, of course, we 

get a much stronger back scatter return signal for the radar to operate on. We also get 

attenuation, but at these frequencies and over the short ranges we're talking about the back 

scatter actually inmses a little bit faster than we get the attenuation. Over large ranges the 

attenuation could become critical, if the heavy rain existed over very large portions of the 

range. When we ran the simulation for the Dallas/Ft. Worth case, which had e 

heavy rains in it, probably in the 8 to 10 inches per hour rate, we saw attenuation which we 

incorporate in the simulation program. But, it was not sufficient to decrease the back 

scatter signal. We still had a very strong signal noise ratio. In fact we ran that even up at 

the KU ban where the attenuation is much heavier and still were able to see through it. So 

in general, we don't think attenuation of rain rates are going to have an effect. Actually, we 

prefer to have the rains a little bit heavier because we have a stronger signal to work with. 

There is the question of heavy rain on the radome and those effects have been addressed off 

and on. In general the microburst type phenomenon tends to occur in an atmosphere where 

we're not encountering rain initially. We're looking forward and since we're trying to 

protect over the 5 to 10 kilometer range we don't think there will be any degradation due to 

heavy rains. Exactly at what level buildup it would take to completely degrade 

performance, you're probably talking about extremely heavy rains which probably are up 

in the tens of inches per hour. They don't usually exist over a very large extent so the 

attenuation is still going to be small. 

938 
Session X. Airborne Doppler Radar / NASA 

Description, Characteristics, & Testing of the NASA Airborne Radar 

W. R. Jones, NASA Langley 

0. Altiz, Rockwell International 

P. Schaffner, NASA Langley 

J. H. Schrader, RTI 

H. J. C. Blume, NASA Langley 

937 
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Experimental Radar System Block Diagram 

This block diagram shows the complete Wind Shear radar system. The top row of 

blocks shows the pilots standard system and a proposed auxi 

information from the experimental radar. The second row is 

which is mounted in the nose of the aircraft. The lower section consists of the 

modified research weather radar unit from RockwelVCollins and the NASA/Langley 

developed and built subsystem comprising control and display computers, system 

interfaces to the aircraft @ATAC), the VQ detectors, timing circuits and data 

recording system. 
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ind Shear Experimental Radar - Functional Block Diagram 

This block diagram shows the major functional components of the NASA/Langley 

Experimental Radar in some detail. The RockweWCollins modified €UT unit has 

analog and digital interfaces to the remainder of the system. The analog outputs from 

the R/T unit consist of the Coherent Reference (COHO ref.), used to lock the phase of 

the 3rd local oscillator (3rd LO) for the 3rd IF in the NASA VQ Detector, and the 1st 

IF (mislabeled 1st RF Out on the diagram) which provides the "video" signal to the 

VQ Detectors. Digital output lines from the €UT carry the clock signal (used to 

synchronize an 8 phase clock in the NASA portion of the system), the Frame Trigger 

(Trig.) which denotes the start of a new 128 pulse frame of data, and the Inhibit 

(Inhib.) signal which indicates when alternate transmit pulses are being inhibited in 

the Range Alias mode. Communications between the R/T unit and the NASA control 

computer are carried out over ARINC 429 (control) and ARINC 453 (data) serial 

busses. The control computer also houses a number of other interface cards. A 

DATAC interface card used to acquire data from the aircraft data systems. A 

GPIBEEE-488 interface card provides for control of the Programmable Low Pass 

(anti-aliasing) Filters and the Programmable Pulse Generator used for tape recorder 

timing. A DSP card and an associated interface card implement digital bin-to-bin 

Automatic Gain Control (AGC) using averages (for each bin) of the log detector 

output over a portion of each frame to calculate attenuator settings for the next frame. 

The SampleNrite control circuit generates timing signals to clock data into FIFO 

buffers and to insert "line sync" word patterns in the I&Q digital data stream at the 

beginning of each line of data corresponding to the set of returns from a single 

transmit pulse. The Tape and Processing I&Q buffers are organized in a ping-pong 

arrangement where the A buffers are filled first, followed by the B buffers. Digitized 

data flows to the Tape and Processing FFOs in parallel. While the B buffers are 

being clocked out to tape (based on signals from the Read Control circuit) or read by 

the Display Processing Computer, the A buffers are being filled with digitized data 

from the A/D converters. The auxiliary Data FIFO and a similar FlFO hosted in the 

Display Processing Computer are simultaneously filled with data by the Control 

Computer. This auxiliary data includes aircraft data from the DATAC system, 

hardware status and control words, Collins R/T information from ARINC 429 

(Control) and ARINC 453 (Data) bus interfaces, and bin-to-bin AGC log channel 

averages. This data is clocked out to tape at the beginning of each frame of 128 

pulses. 

946 
I I! 

947 
WIS Radar Waveguide & Component Location Aboard Test Aircraft 

The Experimental Windshear Radar System components are distributed in several 

locations in the NASA/Langley 737 aircraft. The Antenna and Pedestal are mounted 

behind a radome in the nose of the aircraft. This assembly is fed by waveguide routed 

through a waveguide switch located near the pilot's Standard Weather Radar unit in 

the nose E&E compartment. This waveguide switch is controlled by the pilot and 

allows switching between the Standard and Experimental R/T units. The unused 

system's output is fed to a Dummy Load to prevent unwanted radiation into the 

interior of the aircraft. The pilot's Indicator (Display) and Control units are interfaced 

to the Standard FUT via ARINC 429 and 453 buses. The experimental R/T unit and 

2 KW High Power Amplifier Unit are located aft of the cockpit in the galley area. 

Another waveguide switch, controlled by the Experimental R/T unit, switches the 

HPAU in and out of the system as requested by the experimenters at the dual bay 

Wind Shear Radar Experiment Station located near the tail in the aft cabin. 

Connections from the Experiment Station to the Experimental R/T unit include 

ARINC 429 and 453 buses, and coaxial cables carrying 1st IF, Coherent Reference, 

and monitor signals. 

948 
949 
Console Equipment Arrangement 

This figure shows the location of various components of the Experiment Station 

portion of the system in the dual bay rack. 

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WXR 700 XN Research Radar System 

This block diagram shows the Rockwell Collins supplied modified Weather Radar 

system components. This system can operate as a stand-alone radar but will generally 

be operated as an integral part of the NASALangley Experimental Wind Shear Radar 

sys tem. 

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WRT 701 XN Receiverflransmitter 

This simplified block diagram illustrates the internals of the Collins R/T unit and the 

interfaces which allow it to be integrated as a component of the NASA/Langley 

system. The AC Attitude control is an ARINC 429 bus, separate from the ARINC 

429 Control bus driven by the Control Computer, which supplies roll and pitch 

information used to be used by the R/T unit in compensating for effects of aircraft 

motion on antenna pointing. The First Intermediate Frequency output (erroneously 

shown as an input) provides to signal input to the NASA/Langley developed portion 

of the system. A coherent reference is also provided as an output in order to allow 

coherent detection to be employed to generate In-phase and Quadrature components 

of the radar return. 

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HPA 701 XN Power Amplifier 

The HPAU traveling wave tube amplifier provides a 10 dB or greater increase in 

transmitted power to provide greater signal strength. 

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WMT 701 XN Antenna 

The antenna is the same flat plate unit supplied with Collins’ Standard Weather Radar 

but a n additional rotational joint has been added to the positioner to allow a 90 degree 

rotation of the antenna to provide either horizontal or vertical polarization in order to 

allow investigation of any polarization effects which might aid in separating signals 

resulting from weather from those produced by ground clutter. 

968 
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Research System Detector (simplified) Block Diagram 

The NASA system incorporates synchronous detection to provide In-phase and 

Quadrature components of the radar signal. A log detector is used to drive a Digital 

Signal Processing card, implementing a feed forw bin-to-bin digital Automatic 

Gain Control system which sets three programmable attenuators in the I&Q signal 

path in order to minimize system noise and keep the signal within the dynamic range 

of the 12 bit A/D converters. 

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961 
isplay and Recording Subsystems Simplified Block Diagram 

The primary goal of the current stage of the Wind Shear Radar Experiment is to 

collect data on tape for post-flight analysis. The I&Q and AUX data streams are 

recorded on a Kodak Datatape 1" 14 track tape unit providing up to 4.4 GBytes of 

storage at data rates up to 1.6 million 12 bit digital words per second. One channel is 

used in direct or analog mode to record an IRIG-A (10 KHz carrier) time code signal 

used to locate desired segments of data on playback. The last channel is used by the 

tape recorder's error detection and correction circuitry. 
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964 
Wind Shear Data Playback Process 

A Compaq 386120 AT compatible computer is used to play back data from the 14 

track flight tapes at a ground based playback station. The data is dumped to a 500 

MByte hard disk at a continuous 50,000 wordsecond rate. Each disk full of data is 

transferred to an 8mm Exabyte Cassette Tape in a format which can be read by the 

Interactive Systems Corporation UNIX based analysis software. On the UNIX system 

the data is then loaded into an Informix database system where it can be accessed by 

analysts. 

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Real-Time Display Processing 

A quick-look real-time display has been implemented as part of the Experiment 

Station on the aircraft. This system consists of a Data Translations DT7020 DSP 

board hosted in a Texas Microsystems €3386 20 MHz rack mounted PC/AT 

compatible system. The DT7020 card is loaded with data acquisition and processing 

routines by the 80386 host processor. The DSP board acquires data from the I&Q 

Processing FIFOs, via a DT-Connect parallel interface, and from the Auxiliary data 

stream provided by the Control Computer. This data is processed in a continuous loop 

and the processed data is available to a program running on the host which can then 

provide a variety of display formats. This system is a valuable diagnostic tool and 

will aid in effectively using the system to collect data for later analysis. In a later 

stage of the program a more powerful real-time computer system is planned in order 

to demonstrate wind shear hazard detection in real time using more sophisticated 

algorithms than are possible on the DSP board. 

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OA 

OVERVIEW 

OF THE 

WXR-700XN RESEARCH RADAR SYSTEM 

PART OF THE 

NASA AIRBORNE RESEARCH RADAR SYSTEM 

PRESENTED BY 

ROCKELL INTERNATIONAL - COLLINS 

OCTOBER 16-18, 1990 

971 
CONTENTS 

WXR- 7OOXN RESEARCH WAR SYSTEM 

CONTROL SOURCES 

01 SPLAY MNITOR 

HPA-7OlXN POYER AMPLIFIER 

WMT- 701XN AMTENNA 

WR1-7OlXN RECEIVER TRANSMITTER 

EuWs 

FIGURE 1 BLOCK DIAGRAM, WXR-7OOXN RESEARCH RMAR SYSTEM 

FIGURE 2 AIRCRAFt CONTROL ANO OISPUY SUBSYSTEM 

FIGURE 3 GROUND CONTROL AN0 OISPUY SUBSVSTU4 

FIGURE 4 SIMPLIFIEO BLOCK DIAGRAM: WRT~7OlXW RECEIVER TRANSMITTER 

972 
ROCKWELL INTERNATIONAL, COLLINS 

FIGURE 1 BLOCK OIAGRAH, WXR-7OOXN RESEARCH RADAR SYSTEM 

973 
w-m (FIGURE 1) 

TEST COMPUTER (IN COMPATIBLE) AN0 CDIO-701XN CWUTER INTERFACE CARD WITH 

NASA OR COLLINS SOFTWARE IN CWUTER (FIGURE 2). 

COLLINS WDP-701 WEATHER OISPUY PROCESSOR USED IN CONJUNCTION WITH A 

PERSONAL COMPUTER SYSTEM AND COLLINS SOFTWARE, (FIGURE 3) 

rtuuMum 

WXI-711 INOICATOR (FIGURE 2) 

COLOR RGB TV MONITOR USED WITH WDP-701 (FIGURE 3) 

I CWUTER TEST el-= COI 0-IOlXN CONTROL BUS (ARINC 429) 

WXI-711 

Df SPUY 

4 RESEARCH SYSTEM DATA BUS (AUINC 453) 

< AIRCRAFT SYSTEM DATA BUS (ARXNC 453) 

FIGURE 2 AIRCRAFT CONTROL Us0 DISPLAY SUBSYSTEM 

* CONTROL MIS (ARINC 429) 

e DATA BUS (ARINC 453) 

FIGURE 3 GUOUNO CONTROL AN0 OISPUY SWISYSTUl 

974 
TRAVELING WAVE TUBE AMPLIFIER 

WLIFIES WRT TRANSMIT OUTPUT 

2650 WATTS PEAK 

PROVlOES RECEIVE SlGNAL PATH, ANTENNA TO WRT 

FLATPUTE RADIATOR WITH SUPPORTING PEDESTAL 

POINfSHG fS CONTROLLED BY THE COMPUT€R IN THE URT-701XN 

RECEIVER TRANSHITTER 

STABILIZED WITH AIRCRAFT' ATTITUDE INPUTS 

SELECTABLE HORlZOWTAL OR VERTICAL POURlUTION 

975 
AC ATTITUOE OUTPUT 

DATA 8USES 

CONTROL eus 

AUXILIARY 

INPUTS 

AND 

OUTPUTS 

L 

HPA ONfOFF AUX I LIMY 

AUX OUTPUTS PROCESSOR 

- r- MAIN 

RECEIVER 4 

c - -- .L 

1 

WRT-tOlXN 

l---l 

F -G+ ANTENNA 

FIGUR€ 4 SIMPLIFIED BLOCK DIAGRAM, WRT-7OlXN RECEIVER TRANSMITTER 

976 
(FIGURE 4) 

CONTROL BUS INPUT (MIINC 429 BUS) ESTABLISHES THE OPERATING CONFIGURATION. 

INTERNAL COMPUTER (8088 CPU) CONFIGURES THE SYSTEM VIA THE COMPUTER BUS. 

TRANSMITTER - SELECT FREQUENCY, PULSE WIDTH PRF, LOU OR HIGH PEAK 

POmR 

DISPLAY ENCODER - SELECT ENCOOINC BASE0 UPON OPERATING WE 

AUXILIARY RECEIVER PROCESSOR - SELECT GAIN, INITIAL SfC FOR HATCHED 

BANDWIDTH, STC SLOPE 0, 6 OR Q 

d6lOCfAK 

ANTENNA - SETS UP AW EXECUTES REQUESTED POINTING ROUTINES, USES 

AIRCRAFT PITCH I, ROLL TO COWWTE POINTING POSITION, ISSUES 

DRIVE ComAwoJ AND MONITORS AMTEW POSITION. 

977 
[CONTINUED] (FIGURE 4) 

AUXILIARY INPUTS: 

HPA ON/OFF 

RECORD GATE 

AUXI LIMY OUTPUTS; (* NASA PROCESSOR INPUlS) 

* FIRST IF 

* TRANSMIT SYNC 

* 2N0 WGE SYNC 

* 4 MHz CLOCK 

* COHERENT R€f OSCILLATOR 

URT XMIT PEAK PWR MONITOR 

AUX SECOND IF STC 

AUX SECOMD IF RAN6E VIDEO 

AUX SECOWO IF QUMRATW (Q) RETORN 

AUX SECOND IF fH-WS€ (I) RETURN 

HPA Powul EMABLE 

HPA SlAnoev/~RATE 

HPA VIM0 QAT€ 

HPA 777.7 WlJt REFERENCE 

HPA PUS€ MTECTOR 

WA PEAK POWER WITOR 

978 

TOTRL P. 09 
979 

GENERAL QUESTIONS AND ANSWERS 

Q: SCO7T GRIFFITH (Allied Pilots Association) - In view of present FAA regulatory 

requirements, what economic incentives do the airlines have to explore new wind shear 

measurement technologies i.e., predictive andor combined systems? 

A: GUICE TINSLEY (FAA) - The expected benefit from predictive systems would be 

safety benefits and the expanded capabilities resulting from the detection of clear air 

turbulence. However, there is a long term economic benefit resulted from improved safety. 

Q: FRANK DREW (Lockheed Austin Division) - Has the FAA committed to regard 

current reactive systems as compliant once predictive systems are real and affordable? If 

not, what kind of reaction time will the industry be given once predictive systems are real 

and affordable? 

A: GUICE TINSLEY (FAA) - It is impossible to clearly forecast the future. However, 

based on past experience and assuming no catastrophic events that would require change of 

the wind shear equipment rule, both reactive and predictive systems are allowed and 

considered in compliance with the rule. 

Q: ED LOCKE (Therm0 Electron Technologies) - Wa there be any new LIDAR device 

R & D funding available in '91 and '92 for better and cheaper LIDAR concepts? 

A: ROLAND BOWLES (NASA Langley) - There is not likely to be any out-of-house 

funding. There is the possibility of in-house funding to accelerate the 2 micron work. We 

also would want to leverage that 2 micron work against space applications which is 

another significant need from a NASA perspective, other than just airborne wind shear 

detection. 

Q: WALT OVEREND (Delta Airlines) - How are we to reconcile that all of the airline 

airrraft or a great majority will be equipped with reactive wind shear systems? For a fleet 

of 450 airplanes the cost will be, or is, $25 to $30 million dollars. Research efforts are 

now far behind the requirements established some 5 years ago. 

A: ROLAND BOWS (NASA Langley) - NASA can't reconcile that. You, the industry, 

perhaps have something to say about that. I think that the way to answer this is that the 

FAA in showing a great deal of flexibility and has decided to waiver the equipment rule for 

four U.S. carriers. Frank Tullo from Continental stated who those people were. That 

gives an additional period of time for the technology to mature, for you guys to get out and 

work and see what can bc put in the marketplace that will satisfy a requirement for 

predictive wind shear detection. My feeling is that we've got 8 months to write a TSO for 

this equipment, if we ain't got it in 8 months, forget it. I think what we need to do is write 

an aviation system requirement and the sensor technology that fits will surface. It's a 

question of performance for acceptable cost Our program in NASA is to get out and make 

those kinds of measurements, with systems that represent at least the class of technology 

that is on the horizon, and to provide that data uniformly to the industry and you make your 

decisions. 

Q: PAT ADAMSON (Turbulence Prediction Systems) - Will you give me that Doppler 

radar is inferential and is not a direct measure of velocity? 

98 1 

T 
A: ROLAND BOWLES (NASA Langley) - We've been arguing about this. I have made 

many comments that one of the things that was difficult to grasp was the inferential nature 

of an IR device in terms of estimating a wind. From my View point, the impedance match 

there is not very clear. But the physics now are supporting that kind of inferential 

measurement. It's got to be validated over a whole range of atmospheric conditions and 

other things. I'd like to get the radar and the laser people into this because I have often said 

that these are direct measurement devices and Pat argues that they are still inferential. 

You've got to understand pretty carefully the motion of the raindrop as it's forced by the 

wind. It has its own dynamics. And the aerosol, who knows what it's doing. Are pulse 

Doppler active measurement devices.direct measurement devices or is there still some 

inferential nature to the characteristic of the meas 

BRUCE MATTHEWS (Westinghouse) - I'm not going to exactly mat the question but I'm 

going to try to take it somewhere. The idea of inference may not be as direct as you've 

stated your question here. I think in a more general sense all sensors are going to make 

some inference about the hazards along the glide slope and that may be more the point. 

Roland was Wng yesterday about the antenna beam being lifted as the airplane came 

down in altitude. That means that the radar is going to be pointing its main beam in a path 

near where the airplane is going to fly. It's going to infer what the hazard is along that 

glide slope from measurements made near the expected trajectory of the airplane. That will 

be an inference. Categorically that seems just as much an inference as the IR is making 

about a down draft inferred from tempture applying to the glide slope of the airplane. 

UNKNOWN - If we understand the question right, the question is can we get a direct 

measure of the wind velocity. As the wind is coming down there is this a down draft 

which before it hits the ground, starts spreading out. Now, how long will it take before the 

rain drops pick up the velocity of the wind? We did some studies that showed that the time 

constant was of the order of 2 or 3 seconds. So the rain drops are following the wind 

velocity very closely. So based on that, I would say that the radar would give a direct 

measure. 

PAT ADAMSON (Turbulence Prediction Systems) - Not to carry this too far, but with 

Doppler you've got the size of the volumetric sample, the pulse repetition frequency which 

determines the aliasing, and the turbulence or the vortex within the bin that's measured. 

I'm not saying it's not a good estimate, I don't mean that and I haven't argued that at all. 

But it is by no means a direct measurement of the velocity of the winds. It's a mean 

estimate of the spectral dismbution returned to the receiver. Over most cases that's 

probably pretty good I have a real problem with direct measurement with any remote 

sensor. It is not a direct measurement. It's an inference based on some physical principle. 

There are a lot of errors as we saw on the talk just a little while ago. As you get low signal 

to noise those inferences and those assumptions tend to go down. 

Q: RICHARD DOBINSKY (Sky council) - There are three basic techniques that are being 

discussed to detect wind shm, radiometric techniques, laser and radar. Are there any other 

techniques, and if so elaborate on these. 

A: ROLAND BOWLES (NASA Langley) - There has been work done by the French on 

sound detection and ranging, large low frequency, infra-sound. We've done some work at 

the center on infra-sound. We can sit at Langley Research Center and listen to the shuttle 

take off at the Cape using low frequency sound. I think that is beyond the scope of what 

we're trying to do in our program. Typically you would think they would be ground 

based, so it's FAA's problem. 

002 
trade off comparisons, 

according to the plan Mike Lewis laid out, we're going to have a lot to say about these at 

the next conference. I would like to point out one other thing. If you listened carefully you 

could see a little bit of an anomaly in some of the questions I was raising with regard to 

reactive systems. We raise questions about wether and have 

cedified them really have a convincing case that can . That'san 

open question. I do believe it is possible to engineer devices and that the industry has 

engineered devices that make very good energy change measurement systems for airplanes. 

Reasonable men can then debate at what level of energy change we annunciate alerts and 

how do we trade it off. In NASA's program, we're not building a reactive warning 

system, we're building a reactive measurement system for airplane energy change that will 

become a standard by which we try to assess, to some degree, the validity of our forward 

look devices. It seems to me that it is imperative in our pmgram that we establish that what 

a forward look sensor sees at time f the airplane will experience at t +z seconds, where z is 

positive. If not, the whole concept of prediction is flawed. You would have to make 

decisions on information that would not be a reliable indicator or aend setter for what 

would happen to you if you elected to continue. It's just fundamental. I think the Orlando 

experiment is the first ever a demonstration that that hypothesis may be me for one 

particular electro-optical technique. That's a winner. In other words, reactive systems 

when properly implemented should satisfy Newton's law and I'm going to stay with 

Newton. He hasn't been wrong yet if you treat him right. 

Q: RICHARD DOBINSKY (Sky Council) - Can you choose an optimum configuration or 

technique to focus R & D upon? 

A: ROLAND BOWS (NASA Langley) - In other words, what will be NASA's criteria 

to reject a technology. Within the time and money we've got to work the program, if it 

don't work we're going to reject it. It's got to provide measurement performance that at 

least satisfies what we would consider a success criteria for measurement performance. I 

think all three of these technologies are going to work to some degree. There is always 

going to points on the envelope where you can fool the instrument perhaps. But then that 

raises the question of how many missed alert are too much and how many nuisance alerts 

are too much? I think an example for us to learn from is the trials and tribulations that the 

TDWR guys have gone through. They've done a remarkable job of sorting that out. Look 

at what they're doing, they're getting out in the field year in and year out and collecting 

data. It's the only way you can refine answers to those kinds of questions. You've got to 

get out and collect data. 

Q: SUSAN KIM (Boeing) - With regards to the extension obtained requested by the four 

airlines what happens if when the extension period is up, the new forward looking 

technology is not defined sufficiently to equip those aircraft which don't have wind shear 

alerting systems? (Will they then be required to equip with reactive systems while the 

forward looking effort continues?) 

A: HERB SCHLICKENMAIER (FAA) - As I understand it, if at the end of the evaluation 

period there does not seem to be "sufficient progress", then the program for that wavered 

airline turns into a reactive schedule starting up as if it happened on that date. 

983 
ROLAND BOWS (NASA Langley) - I would like to make a comment on that. Given 

the current cost of money, that policy could save somebody a fair amount of bucks. One 

might wonder why some or all of the airlines didn’t leap in. 

Q: MIKE TAYLOR (Boeing) - Can the airborne Doppler radar distinguish between a 

microburst event and a tornado? 

A: STEVE CAMPBELL (MI” Lincoln Laboratory) - It is worth noting that the TDWR in 

our test bed and I believe also the Mile High radar, have been running a prototype tornado 

vortex signature algorithm. 

have very few data points. er in 1987 or ‘88. In 

fact, as one of the microburst algorithm developers I was proud to announce that we 

detected some of those tornadoes as microbursts as well. I would think you should be able 

to do it with a technique similar to what’s done for the TVS algorithm. 

UNKNOWN - From a cockpit perspective, a tornado has a classic signature on a weather 

radar. I don’t think that Doppler is really necessary for that, assuming we keep weather 

radar in the aircraft. 

roblem you have running th 

were some tornadoes out in 

course, that you 

ROLAND BOWS (NASA Langley) - We should never take weather radar out of the 

cockpit, rll agree with you there. 

984 
986 
985 
CLOSING REMARKS 

ROLAND BOWS (NASA Langley) - There is a lot of sensitivity about stand alone 

forward look versus not stand alone. My feeling is, and I've always said it, many people 

have said it, and I've heard myself say it many times, "reactive systems technology is non 

throw away". Policy gets in the question here at some point. But it's non throw away 

technology. That doesn't mean that there may not end up a predictive technology that may 

stand alone. What gets involved here is corporate policy, airline operations, how industry 

wants to respond to it, a lot of different things. I think progress is being made in all three 

areas of the sensor technology. I think what can be done by an appropriate synthesis of the 

ground based technology, as LLWAS and TDWR gets integrated, and how we can move 

those kinds of products to the flight deck to the benefit of both operations and safety, the 

prospects are very bright in that. I think the point is our task is simple for the next year. 

We're going to put these sensors on. We've decided what they are. The hardware is being 

cut. This is the last big funding bulge in our program because hardware tails off next year 

and then it's mainly operating the airplane, making measurements and hopefully doing a 

thorough analysis and presentation of results to you, the industry. The course is set for us, 

a lot of work to be done on the NASA side. I still would feel that somehow a process has 

to be put together to really write down the aviation system requirement for predictive 

systems. We can't linger on that one. It's got to be done here in the next 8 to 10 months. 

I appreciate all of you coming. I think it has been a good conference. By the way there 

were 188 people cumulative, not maybe 188 in a mom at any one given instant, but most of 

them, some of them stayed in the bar a lot. This has been a real good turn out. It's been 

the largest tum out of any of these conferences to date. I think the one thing that 

encourages me is that at the first meeting a few years ago, NASA and the FAA were doing 

all the talking by and large. Now we're to the point where, if you looked at the agenda 

carefully, there was a 50/50 split between industry speaking and other government agencies 

speaking and people like NCAR and Lincoln Labs. Perhaps next time it will even be 

dominated by an industry response. The problem is really one where we owe you technical 

answers to well understood and well posed technical questions. But eventually its 

marketplace dynamics and manufacturers willing to bite the bullet, take the risk, build and 

certify, that's going to do it. 

PAT ADAMSON (Turbulence Prediction Systems) - From the industry standpoint, I just 

want to reemphasize that if we're not active we will not have predictive sensors. It's going 

to take more than the government side or the NASA side or the FAA side. It's going to 

take the people that arc in this room and others to not go home and forget and say, well 

somebody else will deal with it It needs to be dealt with if you want predictive sensors. 

The product is driven by whether you can sell it. The retrofit market is one of the 

incentives for people like myself and others to get into this thing. So we've got to get after 

this problem. Not just not talk about it but do something about it 

ROLAND BOWLES (NASA Langley) - One final precaution here. You know we've 

declared victory at least twice or so on this problem and it always comes back. We ought 

to be very careful here, with the capital investment we've alI made in this, not to declare 

victory prematurely and walk away from it. I think that this time we ought to have some 

answers that ought to stand the test of time. 

HERB SCHLICKENMAIER (FAA) - I harken back to when I was one of the advisors in 

the National Academy of Sciences review of low altitude wind shear, coming down to a 

place in Tidewater, Virginia, where they kind of know something about airplanes, and 

987 
talking with an expert panel of people on the airplane side of the problem. There were 

heads of research organizations that were giggling at the concept in 1982 and '83 of 

remotely detecting a hazardous wind shear phenomena. I'll humbly submit there was still 

the question on the table of what does hazardous mean. There were questions about the 

size, there were questions about the concept. A program was borne in '86 where we 

finally sat down and decided to just answer the question that the National Research Council 

posed. If radar won't work then we'll write that up. Over the come of time we were 

fortunate enough to expand our horizon and take a look at the technologies available from 

LIDAR and infrared. We are now to the point where the last question in a conference on 

airborne wind shear detection technology is not will, but can the airborne Doppler radar 

distinguish between a microburst and a tornado. There's an inference there that we've 

already solved the problem. We've come a tremendous way and as Roland has indicated 

there is more to go. Yes, I have been associated with other programs where success was 

declared early and came back to have to eat those words. You're going to make this work. 

It's a safety program that I think we can pull the national resources together to address. 

And, baning certain shortfalls in travel funds I trust that we and the rest of the FAA will be 

able to partake wholeheartedly in this very exciting and last venture in aviation safety. 

Thank you very much. 

PAUL KELLY (21st Century Technology) - Herb, I think I speak for everybody when I 

say we'd like to ask you and Roland to communicate to your respective chains of command 

the appreciation and gratitude of all of us who have attended this conference. We have 

been real impressed with the material that's been presented and we want you to know that 

you guys, in our opinion, did a very good job. We want also not to forget all your staff 

and the Bionetics personnel who assisted you. We are really very grateful and you are to 

be wholeheartedly commended. 

989 
Appendix - List of Attendees 

99 1 
OWBINED MANUFACTURERS' AND TEC~OL~ISTS' 

AIRBORNE WIND SHEAR REVIEW MEETING 

OCT 16 - 18, 1990 

Mr. David Aalfs 

Electrical and Computer Engineering Clemson University 

Clemson, SC 29634-0915 

Msr. Bernard Ades 

Direction Generale de 1 'Aviation Civile 

DGAC/SFACT/P 

246 rue Lecourbe 

75732 Paris CEDEX 15 

FRANCE 

Mr. Farzin Amzajerdian Litton Aero Products 

Mail Station 6 

6101 Condor Drive 

Moor ark, CA 93021-2699 

805 - g78- 2643 

Mr . Zachary A pl in 

NASA Langley esearch Center 

Hampton, VA 23665-5225 

803-656-3190 

33-140434264 

Hr. P. Douglas Arbuckle 

NASA Langley Research Center 

MS 489 

Hampton, VA 23665-5225 

804-864-4072 

Mr. Sheldon Baron 

BBN Systems & Technologies 10 Moulton Street 

Cambridge, MA 02138 

61 7-873 -3235 

Hr. John A. Bartlm 

Smiths Industry 

255 Great Valle Parkway Malvern, PA 193 J 5 

2 15- 296- 5000 

Mr. H. Patrick Adamson 

Turbulence Prediction Systems 

3131 Indian Road 

Boulder, CO 80301 

Mr. Orville J. Alitz 

Rockwell International 

Collins Air Transport Div. 

400 Coll ins Road, NE Cedar Rapids, IA 52498 

Dr. Willard W. Anderson 

NASA Langley Research Center 

Guidance and Control Division 

MS 479 

Hampton, VA 23665-5225 

Capt. Ed Arbon 

Fli ht Safet Foundation 

2208 Wilson hvd., Suite 500 

Arl in ton, VA 22201-3306 

703-512-8300 

Ur. Yves Aurenche 

ONERA 

Service DES/80 

BP M072 

92322 Chat i 11 on Cedex 

FRANCE 

Dr. Joseph 3. Barrett 

Allied-Si nal Inc. 

Morristown, NJ 07960 

Wr. James Bash 

Honeywell, Inc. 

MS 2G27ES 

P.O. Box 21111 

Phoenix, A2 85036-1111 

602-869-6493 

303 -443-8157 

M/S 124-111 

3 19-395-3885 

804-864- 1718 

33-45-34-75-01 

P.O. Box 4 021R 

201 -455-5149 

993 
nr. 6. Don Bateman 

Sundstrand Data Control, Inc. 

15001 N.E. 36th Street 

P.O. Box 97001 

Redmond, WA 98073 -9701 

Mr. Rod Benoist 

Li tton Aero Products 

MS 6 

6101 Condor Drive 

Moomark, CA 93021-2699 

805 -378- 2018 

nr. Cleon Biter 

National Center for Atmospheric Research 

Research Appl ications Program P.O. Box 3000 

Boul der, CO 80307 -3000 

nr. L. Thomas Bleasdale 

Manager Marketing RF Products 

Honewe! 1 

303 -497-8437 

P.O.-Box 21111 

Phoenix, AZ 85036 

602-86912396 

Dr. Roland 1. Bowles 

NASA Lan ley Research Center 

Vehicle 8 perations Research Branch 

MS 156A 

Hampton, VA 23665-5225 

804 -864- 2035 

Hr. Ruy L. Brandao 

A1 1 ied-Signal Aerospace Co. 

Bendi x/Ki ng Air Transport Avionics Di v. 

2100 NU 62nd. Street 

Fort Lauderdale, FL 33309 

305-928-3408 

Hr. Phili Brockran 

NASA Lang f ey Research Center 

MS 468 

Hampton, VA 23665-5225 

Dr. Steven D. Campbell MIT Li ncol n Laboratory 

244 Wood Street 

804-864-1554 

MS HW-16 

P.O. Box 73 

Lexin ton, MA 02173-0073 

61 7 -9% -3386 

Prof. Ernest 6. Baa, Jr. 

Electrical and Computer Engineering C1 emson University Clemson, SC 29623-0915 

Us. 6audy H. Bezos 

NASA Langley Research Center 

Subsonic Aerodynamics Branch 

803-656-5900 

MS 286 

Hampton, VA 23665-5225 

804-864- 5083 

MS 286 

Hampton, VA 23665-5225 

804-864- 5083 

Dr. David L. BJorndahl 

Li tton Aero Products 

MS 12 

6101 Condor Drive 

Moorpark, CA 93021-2699 

nr. Jean Louis Boulay ONERA 

Service OP 

BP MO72 

805 - 378 - 2004 

92329 Chat i 11 on cedex 

FRANCE 

Hr. Emedio H. Bracalente 

NASA Langley Research Center 

MS 490 

Hampton, VA 23665-5225 

804-864- 7975 

Hr. James R. Branstetter 

Federal Avi at i on Admi n i s t r a t i on 

FAA/ADS- 142 

NASA Langley Research Center 

MS 250 

Hampton, VA 23665-5225 

UP. Ramnd S. Callway NASA Langle Research Center 

HamDton. VA 23665-5225 

Mail Stop 4 $ 1 

804r864r1679 

Hr. Thomas 6. Campbell NASA Lan ley Research Center 

MS 490 

Hampton, VA 23665-5225 

Antenna P Microwave Research Branch 

804-864-1772 

993 
nr. Bryan Cam bell 

Subsonic Aerodynamics Branch 

MS 286 

Hampton, VA 23665-5225 

NASA Langley R esearch Center 

Hr. Ralph Cokeley Lockheed Aeronautical S stems Company Dept 98-10, Bldg 608, Pfant 10 

1011 Lockheed Way Palmdale, CA 93550 

805-572-2452 

nsr. Philippe Conti 

Dassaul t Avi at i on 

Flight Test 

B.P. 28 

13801 Istres Cedex 

FRANCE 

42 - 56 - 91 - 10 

nr. Robert C. Costen 

NASA Langley Research Center 

MS 493 

Hampton, VA 23665-5225 

nr. H. Leslie Crane 

MITRE Corporation MS W376 

7525 Colshire Drive 

McClean, VA 22102 

Hs. Lucille H. Crittenden 

Research Triangle Institute 

610 Thimble Shoals Blvd. 

Suite 2038 

Newport News, VA 23606 

Ur. Jams Daily tiiig;:, Inc. 

2111 N. 19th Avenue 

Phoenix, AZ 85027 

804-864- 1413 

703-883-7243 

804-864-1776 

602 - 869 - 1 7 58 

Hr. John B. Carocari 

BEND IX/KING 

Allied-Signal Inc. 

400 N, Ro ers Road 

Olathe, K! 66062-1212 

Us. Rachel Colleu 

913- 782-0400 

Aerospat i a1 e 

E/DET/SY/AVIC 

316 Route de Bayonne 31060 Toulouse Cedex 03 

FRANCE 

Ur. Larry Corrnnan 

National Center for Atmospheric Research 

Research Appl ications Program P.O. Box 3000 

Boulder, CO 80307-3000 

01 1-33-61 -937404 

303-497-8439 

nr. Norman L. Crabill 

Aero S ace Consultants 

Newport News, VA 23603-1431 

Dr. Jeremiah F. Creedon 

NASA langley Research Center 

F1 i ht Systems Directorate 

MS 713 

Hampton, VA 23665-5225 

105 In ! and View Dr. 

804-887-9339 

nr. Harold Curtis 

Kol 1 sman 

403 Sage Bluff Circle 

San Antonio, TX 78216 

51 2 -494-5652 

Ur. Ernie Dash 

ST Systems Cor oration 

1919 Coarnerce 6 rive, Suite 100 

Hampton, VA 23666-4269 

a04 -825-0292 

994 
Or. Victor E. Delnore 

Lockheed Engineering & Sciences 

NASA Langley Research Center 

MS 490 

Hampton, VA 23665-5225 

Mr. Thomas D. Deriso 

Delta Air1 ines Inc. 

Hart sf i el d Ai rport ODerations Center, Dept 044 

804-864-1812 

A'tlanta, GA 30320- 

404-765-4020 

Mr. Charles Dobbs 

Techno1 ogy P1 anni ng , Inc. 

51 Monroe Street 

Suite 1609 

Rockville, MD 20850 

Mr. Frank n. Drew 

Lockheed Missiles and Space Company, Inc 

6800 Burleson Road 

Austin, TX 78744-1016 

301 -340-9310 

5 1 2 - 386 - 2 188 

Hr. R. Earl Dunham 

NASA Langley Research Center 

F1 i ht Research Branch 

MS !47 

Hampton, VA 23665-5225 

Dr. Peter J. Eccles 

The MITRE Corporation Principal Engineer, W194 

7525 Colshire Drive 

McLean, VA 22102-3481 

Hr. Lawrence 3. Englert Kol 1 sman 

2121 Spring Creek Parkway Suite 220 

Plano, TX 75023 

ns. Kaete S. Erskine 

The MITRE Corporation MS W276 

Civil S stems Division 

703-883-7817 

214 -618-3454 

7527 Co Z shire Drive 

Mr. Lawrence M. Denton 

Ray t heon 

1501 Crystal Dr, # 1028 

Arlin ton, VA 22202 

703-435- 1177 

Dr. Hanohar D. DeshDande 

Vi yan, Inc. 

MS 490 

NA 4 A Langley Research Center 

Hampton, VA 23665-5225 

Mr. Alain Donzier 

REMTECH 

P 0 Box 2423 

Longmont, CO 80502 

804 -864 - 1774 

303- 772 -6325 

Dr. Richard N. Dubinsky Sky Council 

689 Indian Road, 3rd Floor 

Toronto, Ontario 

CANADA 

M6P 2E1 

ns. Dana J. Dunham 

NASA Langley Research Center 

Subsonic Aerodynamics Branch 

MS 286 

Hampton, VA 23665-5225 

nr. Chester L. Ekstrand 

The Boeing Company 

P.O. Box 2707 

Seattle, MA 98124-2207 

nr. Carl W. Erickson 

Boei ng Conmerci a1 Ai rpl ane Company 

P.O. Box 3707 

Seattle, WA 98124-2207 

4 16 - 767- 51 56 

M/S 24-23 

206 - 655 -6969 

MS 47-31 

Hr. Steven A. Faltt 

MS 490 

NASA Langley Research Center 

Hampton, VA 23665-5225 

804-864- 1850 

McLean, VA 22101 

703-883-7298 

995 
Dr. W. Michael Farmer 

The Bi onet i cs Corporation 4309 Mission Bell 

Las Cruces, NM 88001 

505-521-1121 

Mr. 6eor e W. Flathers, I1 

HS W376 

7525 Colshire Drive 

McLean, VA 22102-3481 

Mr. Andres Fraga 

Eastern Airl ines 

Mi ami International Airport Miami, FL 33148 

The MITR e Corporation 

703-883-6707 

305-873-2438 

Mr. John F. 6arren 

NASA Langley Research Center 

F1 i ht Management Division 

MS 753 

Hampton, VA 23665-5225 

Mr. K. Scott Griffith 

Allied Pilots Association of 

American Airl ines 

12160 Penderview Terrace #1104 

Fairfax, VA 22033 

Mr. William A. Buenon, Jr. 

Rayt heon Company Suite 1500 

1215 Jefferson Davis Hi hway 

703- 4i6- 5400 

Hr. Robert W. Hal 1, Jr. 

Air Line Pilots Association 

En ineerin & Air Safety 

P.!. Box 1869 

Herndon, VA 22070- 1169 

703 -385-7684 

Arlin ton, VA 22202-325 i! 

703 -689-4205 

Ur. Fred Faxvog 

Manager of Sensors 

Honeywell SRC 

3660 Technology Drive 

Mi nneapol 5 s , MN 55418 

MN 65-2600 

612-782-7704 

Mr. Paul B. Forney Lockheed Missiles & Space Company Mail Stop 97-20/281 

3251 Hanover Street 

Palo Alto, CA 94304 

Hr. C. Hike1 6ale 

American Airlines, Inc. 

Avionics En ineering, MD X567 

Tu1 sa, OK 74158-2809 

415-424-2121 

P.O. Box 58 i! 809 

918-292-2188 

Hr. Jeffrey M. 61 11 berg 

Honeywell Inc. 

Systems and Research Center 

3660 Technology Drive 

MN65-2500 

Minnea olis, MN 55418 

6 12 - 78! - 7572 

Mr. Hichael M. Grove 

Sundstrand Data Control, Inc 

15001 NE 36th St 

Redmond, WA 98073 -9701 

206-861 -3084 

Hr. 6re ory P. Haeffele 

P.O. lox 3707 

Boei n E omnerci a1 Ai rpl ane Group 

MS 7H-92 

206-865-6425 

Seatt 1 e, WA 98124-2207 

Prof. R. John Hansnan 

Massachusetts Institute of Technology kpt. of Aeronautics - & Astronautics 

Room 33-115 . 

Cambridge, MA 02139 

996 
Mr. Avi Harpaz SET1 Inc. 

430 Stump Road 

Mont omeryville, PA 18936 

2 15-i55-8522 

Mr. Michael K. Harris 

Lockheed Aeronautical Systems Co. 

P.O. Box 551 

Blda 636. Deot 75-53 

Plait A-i 

Burbank, CA 91510 

Mr. Brian Hill 

720 Boush St 

Norfolk, VA 

8 18-847 - 5686 

WTKR-TV 

Hr. Ray Hood 

Nat i onal Aeronautics and Space Admi n . Code RC 

Washin ton, DC 20546 

202-453-2745 

Dr. R. Milton Huffaker 

Coherent Technologies, Inc. 

3300 Mitchell Lane, Suite 330 

Boulder, CO 80301 

Mr. Patrick W. Johnson 

American Electronics, Inc. 

9332 Anna 01 is Road 

Lanham, Mi 20706-3113 

Dr. Wayne H. Keene 

Raytheon Company El ec t ro -0p t i cs/Str at eg i c Systems Di r . MS 1K9 

528 Boston Post Road 

Sudbury, MA 01776 

301 -459-4343 

508- 440- 256 1 

Mr. Steven D. Harrah 

NASA Lan ley Research Center 

MS 490 

Hampton, VA 23665-5225 

Mr. Tom Henry 220 Daniel Webster Highway Merrimack, NH 03054 

Antenna P Microwave Research Branch 

804-864-ia05 

Mr. David A. Hinton 

NASA Lan ley Research Center 

MS 156A 

Vehicle II perations Research Branch 

Hampton, VA 23665-5225 

804-864-2040 

Mr. Eugene A. Howell 

Uni ted Techno1 ogi es Optical Systems P.O. Box 109660 

West Palm Beach, FL 33410-9660 

407 - 775-4299 

Mr. Robert L. Ireland 

Resident Representative at Boeing United Airlines c/o Boeing Mail Stop 65-34 

P.O. Box 3707 

Seattle, WA- 98124 

206 - 433 -4 105 

Mr. Claude R. Keckler 

NASA Langley Research Center 

MS 479 

Hampton, VA 23665-5225 

Mr. Roy Ke11 

Rosemount Aeros ace 

Burnsville, MN 55337 

804 -864 - 17 18 

14300 Judicial li oad 

6 12 -892 - 4546 

997 
Mr. Paul P. Kelly 

21st Century Technology International Square 1825 Eye Street, N.W. 

Suite 400 

Washin ton, 0,C. 20006 

Ms. Susan C. Kim 

Boeing Comnercial Airplanes Renton Division Avionics/Fl ight Systems P.O. Box 3707 

Seattle, WA 98124-2121 

Mr. Kapriel V. Krikorian 

202-42 8 -2079 . 

206-393-8097 

M/S RE/R-11 9025 

HU hes’ Aircraft Company 

Los An eles, CA 90009-2426 

2 13 -603 -5491 

P. 8 . Box 92426 

Mr. James L. Kurtz 

Georgia Tech Research Institute 

Radar and Instrumentation Dev. Lab. 

Atlanta, GA 30332 

Mr. William 6. Laynor National Transportation Safety Board 

TE-2, Rm. 824C 

800 Independence Ave., SW 

Washington4 DC 20594 

404-528-7690 

Hr. James F. Lemon 

Hu hes Aircraft Company P.8. Box 92426 

Los An eles, CA 90009-2426 

2 13 - 33? - 3 284 

Hr. Edward V, Locke 

Them Electron Technologies 74 West St. 

M/S RE/R-10/12036 

Wal tham, MA 02254-9046 

6 17 -622 - 1378 

Hsr. Jac ues Mandle 

SEXTANT lvionique, ON 

25 Rue J. Vedrines 

26027 Valence CEDEX 

FRANCE 

3375798776 

Mr. Bruce M. Kendall 

NASA Lan ley Research Center 

MS 490 

Hampton, VA 23665-5225 

Antenna 3 Microwave Research Branch 

804-864-1795 

Hr. Hichael C. Krause 

Raytheon Com any Mail Stop 16h 

528 Boston Post Road 

Sudbury, MA 01776 

508-440-3 17 1 

Mr. Daryal Kuntman 

A1 1 ied-Signal Aerospace Company Bendix/King Air Transport Avionics Div. 

2100 NU 62nd Street 

Fort Lauderdale, FL 33309 

Hr. Julian H. Kushnick 

Allied-Si nal Inc 

305-928-34 17 

PO Box 10 4 1R 

Morristown, NJ 07962-1021 

201-455-2361 

Hsr. Christian Le Roux 

DGAC/STNA 

246 rue Lecourbe 

75738 Paris 

FRANCE 

33 - 1 -40434849 

Hr. Michael S. Lewis 

NASA Langley Research Center 

Mail Stop 265 

Hampton, VA 23665-5225 

804-864-7655 

Hr. James 6. Hages Northwest Air1 ines, Inc. 

E7400 

Mols - St. Paul IAP St. Paul, MN 55101 

612-726-8819 

Hr. Bruce 0. Hathews 

Uestinahouse DEC 

Box 746 

MS 1157 

Baltimore, MD 21203 

301-765-6236 

998 
Ca t. Alvah S. Mattox Jr. 

A1 ! ied Pilots Association 

Rt 1 Box 258 

Weyers Cave, VA 24486 

Mr. Mike H. McClendon 

American Airlines 

MD 843, Fli ht Academy 

DFW Airport, TX 75261-9617 

Mr. W. Edward nelson 

NASA Goddard Space Flight Center 

Wallops Flight Facility W llops Island, VA 23337 

P.O. Box 61 8 617 

81 7 -967 - 5253 

884-824- 1306 

Ur. Robert W. Ueyer Raytheon Company 430 Boston Post Road 

MS CClO 

Wayland, MA 01778 

Mr. Bruce C. nontag Southwest Research Institute 

6220 Culebra Road 

San Antonio, TX 78251 

Mr. Sandee nulgund 

D202 Engi neeri n Quadrangle 

508-440-1018 

512- 522-5001 

Princeton e niversity 

Princeton, NJ 0 Et 544-5263 

609- 258- 5340 

Dr. Loren 0. Nelson 

OPHIR Corporation Suite 100 

3190 South Wadsworth Blvd. 

Lakewood, CO 80227 

303 - 986- 15 1 2 

nr . Cornel i us 0 ' Connor 

MS 343 

NASA Langley Research Center 

Hampton, VA 23665-5225 

Or. John UcCarthv 

National Center for Atmospheric Research 

P.O. Box 3000 

Boulder. CO 80307-3000 

303-497L8422 

Dr. Burnell T. UcKissick 

NASA Lan ley Research Center 

MS 156A 

Hampton, VA 23665-5225 

Capt. William Melvin 

Air Line Pilots Association 

1101 W. Morton 

Denison TX 75020 

Vehi cl e 9, perat i ons Research Branch 

804-864-2037 

Mr. Ernest W. Uillen 

Director 

Chancelwyn Research 

390 Rivers Ridge Circle 

Newport News, VA 23602 

Ur. Samuel A. Uorello 

NASA Langley Research Center 

F1 i ht Management Division 

MS 753 

Hampton, VA 23665-5225 

Ur, Hans Uuller 

Sundstrand Data Control 

PO Box 97001 

Redmond, WA 98073-9701 

Hr. A. H. H. Nieuwpoort 

Fokker Aircraft B.V. 

P.O. Box 7600, Dept. EDAA (SO29-32) Schiphdpyk 231 

THE NETHERLAIDS 

Ur. Saburo Onodera 

Ja an Air lines 

2-!-1 Hanedakuko Ohta-Ku 

804-888-0880 

206-891 -3069 

1117 23 Schi hol-OOst 

3 1 - 20-6052149 

Tokyo 144 

JAPAN 0 81-3-747-3357 

999 
ns. Rosa M. Oseguera 

NASA Lan ley Research Center 

Vehicle B perations Research Branch 

MS 156A 

Hampton, VA 23665-5225 

804-864-2039 

MS 156A 

Hampton, VA 23665-5225 

804-864-2039 

Mr. W. J. Overend 

Del ta Ai rl i nes 

C/O Engineering Dept. Atlanta International Airport 

Atlanta, GA 30320 

Hr. Walter W. Patterson 

404 - 765- 3 103 

Westin house Electric Corporation 

MS 129! 

P.O. Box 746 

Baltimore, MO 21203 

Hr. Bill Peltola 

Sundstrand Data Control, Inc. 

15001 N.E. 36th Street 

P.O. Box 97001 

Redmond, WA 98073-9701 

Mr . Jeff Pi err0 

NASA Langley Research Center 

Hampton, VA 23665-5225 

301 -765-3459 

206-885-8625 

Dr. Fred Proctor 

MESO, Inc. 

28 Research Drive 

Hampton, VA 23666 

804 -865 - 7800 

Dr. Hark A. Richards 

Geor ia Institute of Technology 

GTRI~Wl./SPB/CCRF/S - 206 

Atlanta, GA 30332 

Mr. Ro E. Robertson 

404- 528- 771 1 

Rockwe T 1 International 

Collins Air Transport Division 

400 Coll ins Road. NE 

M/S 124-111 

Cedar Ra ids, IA' 52498 

3 19- 395- f990 

Dr. Robert 6. Otto 

Lockheed Missiles and Space Co., Inc. 

3251 Hanover Street 

Palo Alto, CA 94304-1191 

Hr. Eric C. Palmer 

McDonnell Doug1 as 

3855 Lakewood Boulevard 

Long Beach, CA 90846 

0/97-01, 201, 2 

4 15 -424 - 2 148 

213 - 593 - 3298 

Mr. Andy Peczalski 

Honeywell 

10701 Lyndale Ave., S 

B1 oomi ngton, MN 55420 

MN 09-8100 

Mr. Ian W. Philpott M/S 106-207 

Rockwell International 

400 Coll ins Road, NE 

Cedar Ra ids, IA 52498 

3 19 - 3 95 - 088 1 

Hr. 6re Piesinger 

MS 02104 

P.O. Box 21111 

Phoenix, A2 85036 

Hr. Fred Remr 

University of North Dakota 

De artment of Atmospheric Science P.1. Box 8216 

Uhi vers i t Stat i on 

Honeywe 3 1, Inc. 

602-869-6168 

Grand For z s, NO 58202 

701 -777-2291 

Hr. Terry H. Riley 

Serv-Air, Inc. 

P.O. Box 6669 

Greenville, TX 75403-6669 

Hr. Paul Robinson 

F1 i ht Management Division 

NASI Langley Research Center 

MS 156A 

Hampton, VA 23665-5225 

2 14-454-2000 

804-864-2031 

1000 
Dr. Donald R. Rogers Turbulence Prediction Systems 

3131 Indian Road 

Boulder, CO 80301 

303-443-8157 

Mr. Robert N. Romine 

Lockheed Missiles & %ace Comoanv, . -. Inc. 

6800 Burleson Road 

Austin, TX 78744-1016 

512-386-2255 

Capt. Brian I(. Ryder United Airl ines F1 ight Center 

Stapleton International Airport Denver, CO 80207 

303-780-5201 

Mr. 6re Salottolo 

800 Independence Ave., SW 

Washington, DC 20594 

Nationa 3 Transportation Safety Board 

Mr. Phili R. Schaffner 

MS 490 

Hampton, VA 23665-5225 

Mr. Blaine Schmidt 

E-Systems En ineering 2268 South 3%70 West 

Salt Lake City, Utah 84119 

Mr. Nelson Seabolt 

NASA Langley Research Center 

Hampton, VA 23665-5225 

NASA Lang P ey Research Center 

804-864-1809 

801-973-4300 

Mr. Syed T. Shafaat 

Boei ng Comneri cal Ai rpl ane Corp 

Seat t 1 e, WA 98124-2207 

PO BOX 3707, MS01-82 

206 - 342 -3 12 1 

Mr. Robert R. Roll 

Lockheed Missiles & Space Company 

3251 Hanover Street 

Palo Alto, CA 94304-1191 

Mr. Robert A. Rosen 

415-424-3042 

M/S RE/R-11/8035 

Hu hes' Aircraft Company P.8. Box 92426 

Los Angeles, CA 90009-2426 

213-334-3284 

Mr. Samuel P. Saint 

Safe Flight Instrument Corporation She1 ter Harbor 

Westerly, RI 02891 

Dr. Wayne Sand 

National Center for Atmospheric Research 

Research Appl i cat i ons Program P.O. Box 3000 

Boulder, CO 80307-3000 

303 -497 -8454 

Mr. Herbert W. Schl ickenmier 

Federal Aviation Admi ni strati on 

ARD-LOO, Room 712 

800 Independence Ave., SW 

Washington, DC 20591 

Hr. Lyle C. Schroeder 

NASA Langley Research Center 

MS 490 

Hampton, VA 23665-5225 

nr. Andrew Serrel 1 

Air Safety Foundation 

809 Ocean Pines 

Berlin, MD 21811 

CAPT Samuel L. Shirck 

Continental Airl ines 

P.O. Box 92044 

Los An eles, CA 90009 

2 13-64j- 3947 

804 -864- 1832 

CW 6-162 

1001 
Mr. Bernard B. Silverman 

Active EO System Analysis 3075 Rivera Drive 

Delray Beach, FL 33445 

Mr. Ni el P. Slack 

Airlines Division 

Comet Way Hatfield, Hertfordshire ALlO 9TL 

ENGLAND 

Mr. David Soreide 

Boeing Corporation 

P.O. Box 3999 

Seattle, WA 98124 

407-265-3860 

Bri ti s ii Aerospace Ltd 

707-62345-3744 

MS 75-05 

206-865-3144 

Or. Leo D, Staton 

NASA Lan ley Research Center 

MS 490 

Hampton, VA 23665-5225 

Mr. Stephen A. Stoll 

2805 Warbler Pi 

Wi 11 i amsburg, VA 23185 

Antenna i! Microwave Research Branch 

804-864-1793 

Mr. 0. Alex Stratton 

Princeton University 0202 Engineerin Quadrdngle Princeton, NJ 0 8 544-5263 

609-258-5340 

Mr. Michael W. Taylor Boei ng Comnerci al- Ai rpl ane Company 

MS 2T-61 

P.O. Box 3707 

Seattle, WA 98124-2207 

207-544-5203 

Dr. Peter C. Sinclair 

Colorado State University Atmospheric Science Department Fort Collins, CO 80523 

303-491 -8679 

Mr. David Sobota 

144 Research Dr 

Hampton, VA 23666 

Dr . H. 6. Stapel broek Rockwell International Corporation Science Center D/781, 031-BC17 

3370-Mi ral oma Avenue 

P.O. Box 3105 

Anaheim, CA 92803-3105 

Dr. Robert F. Stengel Princeton University D202 Engineerin Quadrangle 

714-762-4528 

Princeton, NJ 0 1 544-5263 

609-258-5103 

Mr. Mark E. Stom 

ST Systems Corporation NASA Langley Research Center 

MS 474 

Hampton, VA 23665-5225 

Mr. Russell Targ Lockheed R&D 

3251 Hanover Street 

Pal o A1 to, CA 94304 

Hs. Des ina Tsouka 

Faculty of Civil Engineering 5 Iroon Polvtechniou Street 

0/97-01 

41 5-424- 2436 

Nationa P Technical University of Athens 

GR 15773 Athens 

GREECE 

01-777-4085 
Hr. Frank Tullo 

ATA 

6162 

7300 World Way West 

Los An eles, CA 90009 

213-64%-4195 

Msr. Jean-Claude Valentin 

DGAC/STNA 

246 Rue Lecourbe 

75732 Paris 

FRANCE 

33140434934 

Mr . Edward J. Vertaschi tsch 

Boein Aerospace & Electronics 

Seattle, WA 98124-2499 

P.O. % ox 3999 

MS 75-65 

206-865-3983 

Mr. Edgar 6. Waggoner NASA Langley Research Center 

Subsonic Aerodynamics Branch 

MS 286 

Hampton, VA 23665-5225 

Mr. Craig Wanke 

MIT 

Room 37-438 

77 Massachusetts Ave 

Cambridge, MA 02144 

Hr. Howard T. Williams 

61 7- 253 -0993 

Gul fstream Aerospace Corporation M/S D-04 

P.O. Box 2206 

Savannah, GA 31402-2206 

Or. Marilyn Wolfson 

MIT Lincoln Laboratory 

Room HW-25 

P.O. Box 73 

Lexin ton, MA 02173-0073 

617-9%1-3409 

912-964-3224 

nr. John Wri ht 

8451 Travelair, Building 8 

Houston, TX 77061 

Continental 1 irlines 

713-640-5108 

Hr . John Tuttl e 

Kol 1 sman 

5464 Villas Drive 

Bonsall, CA 92003 

619-945-1873 

nr. Everette E. Vermilion 

Sundstrand Data Control, Inc. 

15001 N.E. 36th Street 

P.O. Box 97001 

Redmond, WA 98073 -9701 

nr. Dan 0. Vicroy 

NASA Lan ley Research Center 

MS 156A 

Hampton, VA 23665-5225 

Hr. Robert Walkinshaw 

Vehicle 8 perations Research Branch 

804-864-2022 

Bendix/Kin Air Transport Avionics Div. 

Ft. Lauderdale. FL 33309 

P.O. Box 9 s 27 

305-928-2370 ' 

Hr. Norman White 

Kol 1 sman Corporation 

220 Daniel Webster Highway Merrimack, NH 03054 

Mr. Jason Witow 

0 tical Air Data Systems 

9g72 Topanga Canyon Blvd. 

Chatsworth, CA 91311 

MS 2-811-1 

603 -886- 2685 

81 8-997 - 3636 

nr. Daniel L. Woodell 

Rockwell International Corp. Avi on i cs Group 

400 Coll ins Road, NE 

Cedar Rapids, IA 52498 

Hr. Thomas J. Wright 

E-Systems, Inc. 

Monter Division 

2268 South 3270 West 

Salt Lake City, UT 84119 

M/S 106-207 

3 19 -395- 3090 

80 1 - 974 - 727 5 

1003 
Mr. John S. Uyler Smith Industries 

255 Great Valley Parkway Malvern, PA 19355 

215-296-5000 

Mr. Joe Youssefi 

Honeywell 

M/C N3003 

21111 N. 19th Avenue 

Phoenix, AZ 85027 

Mr. J. Allen Zak 

602 - 869 - 1557 

ST Systems Corporation NASA Langley Research Center 

MS 250 

Hampton, VA 23665-5225 

804-864-6397 

Mr. Carl H. Young 

Eastern Air Lines, Inc. 

Mqr., Flight Test 

8 dg. 30, MIAFR 

Miami, FL 33148 

Mr . Vincent Zahornasky Koll sman 

220 Daniel Webster Hwy. Merrimack, NH 03054-4809 

Hr. Terry Zweifel 

21111 N. 19th Avenue 

Phoenix, AZ 85027 

305 -873 - 7060 

M/S 1LO4-2 

603-595-6040 

602-869- 2979 

1004 
1. Repon No. 

NASA CP-10060, Part 2 

DOT/FAA/RD-9 1/2-11 

2. Government Accession No. 3. Reciptent's Catalog NO. 

Dan D. Vicroy; Roland L. Bowles; and 

Her be rt Sch lic ke n mai er, compilers 

NASA Langley Research Center 

Hampton, VA 23665-52225 

National Aeronautics and Space Administration 

Washington, DC 20546 

13. Type of Repon and P 

Conference Publicatior 

4 Title and Subtitle 

Airborne Wind Shear Detection and Warning Systems - 

Third Combined Manufacturers' and Tech no log i sts' 

Conference 

14. Sponsoring hgency Code 

5. Report Date 

January 1991 

6. Performing Organization Code 

I 

15. Supplementary Notes 

7 AuthorW 

Dan D. Vicroy; and Roland L. Bowles: NASA Langley Research Center, Hampton, Virgi 

Herbert Schlickenmaier: Federal Aviation Administration, Washington, DC 

16. Abstract 

8. Performing Organization Repon No. 

The Third Combined Manufacturers' and Technologists' Conference was hosted jointly 

by NASA Langley Research Center (LaRC) and the Federal Aviation Administration 

(FAA) in Hampton, Virginia, on October 16-18, 1990. The meeting was co-chaired by 

Dr. Roland L. Bowles of LaRC and Herbert Schlickenmaier of the FAA. The purpose 

of the meeting was to transfer significant ongoing results of the NASNFAA joint 

Airborne Wind Shear Program to the technical industry and to pose problems of current 

concern to the combined group. It also provided a forum for manufacturers to review 

forward-look technology concepts and for technologists to gain an understanding of the 

problems encountered by the manufacturers during the development of airborne 

equipment and the FAA certification requirements. The present document has been 

compiled to record the essence of the technology updates and discussions which 

followed each. 

19 Securiry Classif (of this report) 20. Security Classlf. (of this page) 

Unclassified Unclassified 

Microbursts Doppler Radar 

Wind Shear Infrared 

Aircraft Hazards LIDAR 

21 No. of pages 22. Price 

505 A22 

U nclassified-Un limited 

Subject Category: 03