NASA/TM-2001-210720

Data Synchronization Discrepancies in a

Formation Flight Control System

Jack Ryan, Curtis E. Hanson, Ken A. Norlin, and Michael J. Allen

NASA Dryden Flight Research Center

Edwards, California

November 2001

https://ntrs.nasa.gov/search.jsp?R=20020008226 2018-05-15T10:46:02+00:00Z
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NASA/TM-2001-210720

Data Synchronization Discrepancies in a

Formation Flight Control System

Jack Ryan, Curtis E. Hanson, Ken A. Norlin, and Michael J. Allen

NASA Dryden Flight Research Center

Edwards, California

National Aeronautics and

Space Administration

Dryden Hight Research Center

Edwards, California 93523-0273

November 2001
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(703) 487-4650
DATA SYNCHRONIZATION DISCREPANCIES IN A FORMATION

FLIGHT CONTROL SYSTEM"

Jack Ryan,* Curtis E. Hanson, _;Ken A. Norlin, '_and Michael J. Allen, ¶

NASA Dryden Flight Research Center, Edwards, California

ABSTRACT

Aircraft hardware-in-the-loop simulation is an invaluable tool to flight test engineers; it reveals

design and implementation flaws while operating in a controlled environment. Engineers,

however, must always be skeptical of the results and analyze them within their proper context.

Engineers must carefully ascertain whether an anomaly that occurs in the simulation will also

occur in flight. This report presents a chronology illustrating how misleading simulation timing

problems led to the implementation of an overly complex position data synchronization guidance

algorithm in place of a simpler one. The report illustrates problems caused by the complex

algorithm and how the simpler algorithm was chosen in the end. Brief descriptions of the project

objectives, approach, and simulation are presented. The misleading simulation results and the

conclusions then drawn are presented. The complex and simple guidance algorithms are

presented with flight data illustrating their relative success.

NOMENCLATURE

AFF

ARTS

e

G

GPS

i

INS

Autonomous Formation Flight

Airborne Research Test System

error signal

low-pass filter

global positioning system

flame number

inertial navigation system

GPS relative position error (high frequency)

nl

INS relative position error (low frequency)

n2

PCM pulse code modulation

"No copyright is asserted in the United States under Title 17, U. S. Code. The U. S. Government has a royalty-free

license to exercise all rights under the copyright claimed herein for Governmental purposes.

* Aerospace Engineer

* Aerospace Engineer

Aerospace Engineer

Aerospace Engineer
PSFCC

S

SRA

t

UTC

Y

X

XI

Xz

Z

At

production support flight control computer

Laplace operator

Systems Research Aircraft

time

coordinated universal time

velocity

position

GPS relative position measurement

INS relative position measurement

true relative position

time difference

INTRODUCTION

Flight testing often is an iterative process of testing, modifying, and retesting. Even with the use

of high-fidelity simulations, the iterative nature persists. In most cases, simulation testing

reduces the number of iterations; however, misleading simulation results can have the opposite

effect. This report presents a chronology illustrating the effects of such a problem experienced

by the Autonomous Formation Flight (AFF) project.

The AFF project is attempting to realize fuel savings by autonomously flying an aircraft in the

induced vortex of a leading aircraft, which necessitates accurate relative position estimates. The

AFF project reaches these estimates by combining global positioning system (GPS) and inertial

navigation system (INS) information using a complementary filter. Time delays, inherent in the

combined system, require the use of a position synchronization algorithm. The project initially

used a simple algorithm; however, complexity was added to the synchronization algorithms in

response to erroneous simulation test results. The modified algorithm failed in flight as a direct

result of the added complexity. The simulation error then was discovered and the original

algorithm was reimplemented.

This report provides brief descriptions of the AFF experimental platform, simulation, and

relative position estimation method. The initial position synchronization algorithm is presented

with the erroneous simulation results that indicate an algorithm deficiency. The second, more

complex algorithm is presented with flight data and discussion illustrating its deficiency. The

erroneous simulation results and successful flight tests results of the reimplemented initial

algorithm are discussed.

AIRCRAFT SYSTEMS

The AFF experiments are flown onboard the NASA Systems Research Aircraft (SRA). l The

SRA is an F/A-18 airplane that has special research computers known as production support

flight control computers (PSFCCs). The PSFCCs consist of a research processor, containing
researchcontrol laws,interconnectedthroughdual-portrandomaccessmemory to a production

processorcontainingproductioncontrol laws. ThePSFCCsallow thepilot to selectthe research

processorand automatically revert to the production processorwhen any flight limits are

exceeded. 2

For formation flight experiments,a secondNASA F/A-18 acts as the leading aircraft and

transmits its state and navigationalinformation through a pulse code modulation (PCM)

telemetry system to the SRA. The guidancealgorithmsthen compute and pass the relative

positions to a controller using 20-Hz proportional-plus-integral-plus-derivativewith state

feedbackto maintainthe desiredrelativeposition. The controller inputs arerelativeposition

error,relativevelocity error, trailing aircraft roll angle,andtrailing aircraft normal acceleration.

The outputs areroll stick and pitch stick commands;they are used in place of pilot stick

commands.

The formationflight guidanceandcontrol algorithmsarehostedon the Airborne Research Test

System (ARTS) computer. A real-time embedded system, the ARTS gathers the aircraft sensor

data used in the guidance and control functions and sends computed pitch and roll stick

commands to the inner-loop controller contained in the PSFCCs. The PSFCCs, in turn,

command aircraft actuator deflections. Figure 1 shows a basic system interconnection.

Leading aircraft

I Qpsh

recelverl _ PCM L_I

I INS I.J-I b°ard Ir ITransmitter 1

--I

1553 Interface I

010193

Figure 1. Basic AFF system interconnection.

Ground station-corrected, carrier phase, differential GPS position data are also provided by the

SRA. These data are used as a "truth source" with which to compare the algorithm-calculated

relative positions. Ground station-corrected data are not used as inputs to the AFF guidance

algorithms to avoid reliance upon ground station availability.

THE FORMATION FLIGHT SIMULATION

The NASA Dryden Flight Research Center (Edwards, California) F/A-18 simulator provides a

full six-degree-of-freedom, hardware-in-the-loop, nonlinear, real-time simulation. The simulation

models the aerodynamics, actuators, sensors, engines, and aircraft telemetry and all pertinent

3
aircraft systems.3 The simulation interfaceswith a fixed-basecockpit, mission computers,

PSFCCs,andanARTS computer.In addition,telemetry,anIEEE 1553bus,and computational

delaysareincludedin thesimulationwith estimatednoisein the aerodynamicsurfacecommands

andmovements.

The simulationwasexpandedto a two-ship formation flight simulationby addingthe capability

to recordandreplayanaircraft trajectory. Using atelemetrymodel,trajectorydataarebroadcast

to thesimulatedtrailing aircraft,simulatingair-to-airtelemetry.The simulatorpassesthe datato

the ARTS computercontainingthe guidanceand control algorithmsthat computethe roll and

pitch stick commandsrequiredto maintainformation flight. Thesecommandsarepassedto the

PSFCCsthatretumcomputedsurfacecommandsto thesimulator.

The simulationtelemetrymodelemulatesthe leadingaircraft instrumentationtelemetry stream.

A PCM simulatorboard is used for output of a serialPCM-encodedbit streamusingdatafrom

the simulationcomputercurrentvaluetable. The bit streamis passedto the ARTS computer

that containsthe formation flight guidanceand control algorithms. The ARTS functions in

concertwith thePSFCCcomputersidenticallyto how it functions onboardthe SRA. Figures1

and2 showtheaircraftandsimulationsysteminterconnections,respectively.

"_mulated trailing aircraft

Simulated leading aircraft

I Recorded [_b_]+ __/m,__

trajectoryJ I tabUeI

m

I Aircraft _ RS-422 1553 _

I dynamics I I_ I_1 interface

010194

Figure 2. Basic AFF simulation system interconnection.

RELATIVE POSITION ESTIMATES

Close formation flight of aircraft can achieve substantial fuel savings by flying each aircraft in the

upwash field generated by all other aircraft in the formation. 4 Requiring a pilot to maintain the

required precise relative position during long-distance flights, however, is unreasonable. In such

circumstances, an automatic controller is necessary to maintain the formation. To allow good

performance of the controller, accurate relative position measurements are needed.

The AFF project estimates relative aircraft position by combining two independent relative

position measurements with a complementary filter. The resulting estimate and aircraft state

information are input to an automatic relative position controller. The controller then computes

4
roll andpitch stickcommands.Thesecommandsaresentto inner-loopflight controlsthat were

developedfor previousprograms.2

The first relative position measurementis obtained by differencingthe 2-samples/secGPS

position measurementsfor both aircraft. With commonsatellitesand close aircraft proximity,

ephemerisdataerrors, satelliteclock error_,and atmosphericdistortion errors are practically

eliminated. Reference5 providesdescriptionsof eachof theseerrors. The remainingdominant

erroriscausedby the2-samples/secdatabeingprocessedby the 20-Hz algorithm. The resulting

GPSrelativepositionmeasurementcanthereforeberepresentedas:

xl(t)=z(t)+nl(t ) (1)

where x,(t) is the GPS-measured position, z(t) is the true position, and nI(t) is the measurement

error.

A second relative position measurement is obtained using the onboard INS. The primary INS

measurement errors are caused by its low-frequency drift and biases. The INS relative position

measurement can therefore be represented as:

x2(t ) -- Z(t) + nz(t ) (2)

where XE(t ) is the INS-measured position, z(t) is the true position, and n2(t ) is the

low-frequency INS errors.

A complementary filter combines the two independent relative position measurements to provide

an accurate relative position estimate. Figure 3 shows the filter. By subtracting one measurement

from the other, x 2 - xj, the error e -- n 2 - n_ is obtained. A low-pass filter,

G(s)- 7t/4 (3)

s+_t/4

tuned to remove nj from e, provides n2. Subtracting this result from the original measurement

z + n 2 leaves an accurate position estimate that is used as an input to the formation flight

controller. Reference 6 provides a more detailed explanation of complementary filters.

i

x 2 +f-._

-',Je - I "'1 n 2

Z

r

010195

Figure 3. Complementary filter.

POSITION SYNCHRONIZATION LOGIC

Inherent time delays associated with transmitting GPS data from one aircraft to another cause the

AFF guidance routines to asynchronously receive positional data. Without time correlation, this

asynchronous data leads to large jumps in the relative longitudinal GPS position that the

complementary filter is unable to remove. Relative position jumps in the lateral and vertical axis

also exist, but these are much smaller than in the longitudinal axis. This characteristic is no

surprise; the longitudinal axis has the largest velocity component. The complementary filter is
muchmoresuccessfulin eliminatingpositionjumps in the lateral andvertical axesthan in the

longitudinalaxis.

Figure4 showstheresultsof asimulatedtime delay. In thisexample,theformationwas flying at

approximately600 ft/sec and had a 0.1-sec transport delay betweenthe trailing and leading

aircraftGPSupdates.Thetimedelay,in combinationwith the 2-samples/secGPSsignal,caused

thetrailing aircraftto appearto moveaheadof the leadingaircraft. The relativeposition appears

to jump more than 300 ft. These jumps are too large for the complementary filter to

satisfactorily correct.

20O

Complementary filter

estimate

------ GPS measurement

........ INS measurement

I I I I I

Longitudinal

relative

position, ft

100

-100

-200

" t

,11

I

-I

.....

Fi /-_ F_ !-! rq -

I [ I i !I ! _ :I

I _ i I _ I i ! ._ I

I I m I i I ! i ! I

I I ! I 1 -- I I I I

! I I I I ! I I I I

I I i I I --

I ! ! i ! i

-___ .......L__ J j, F"......... "T"........ -r........... I F .,

2000 I I i I

1500 --

Longitudinal 1000 --

absolute

position, ft 500 --

-500

0 .5

_- 0.1-sec delay _ i

.... ,

GPS-measured

posltion

Leading aircraft

------ Traillng aircraft --

I I I .... I I

1.0 1.5 2.0 2.5

Time, sec

3.0 3.5

0101_

Figure 4. Uncorrected relative position estimates.

Data synchronization logic has been developed to make the combined system robust to such

asynchronous GP_3 data and temporary signal loss. The logic uses the GPS coordinated universal

time (UTC) to align the two aircraft position measurements. The logic assumes the UTC and

positional measurements are taken at the same time, contained in the same telemetry message,

and concurrently received by the algorithm. If the trailing aircraft UTC is larger than the leading

aircraft UTC, the leading aircraft position is extrapolated as:

x I - xi_ l + v, At (4)

where x is the position, v is the velocity as reported by the INS, i is the flame number, and At

is the time difference between the trailing and leading aircraft updates. Figure 5 shows the

UTC-based synchronization algorithm, which compares the leading and trailing aircraft UTC

values and extrapolates the position estimate if one is lagging behind the other.

6
REVISED POSITION SYNCHRONIZATION LOGIC

Implementation of the guidance and control algorithms into the simulation revealed an apparent

flaw in the guidance logic. The GPS relative position measurements spiked, causing poor

complementary filter estimates. The cause indicated by the simulation was that the assumption

of concurrent positional and UTC information was invalid. The guidance logic therefore had

calculated the relative positions with asynchronous GPS positional information, which caused

the spikes.

[ Extrapolate ]

trailing aircraft ]---

I poeit,onI

[ ':xtrapo,ate I

_,=lii._ _ leading aircraft ]---

_n_'. _£'U]'__C_ [ position ]

I 'C om_p ute I

T N° I [ relative I

I position J

010197

Figure 5. UTC-based synchronization logic.

A general algorithm, based directly on the position information, was then designed to be

independent of the UTC. More complex than the UTC-based logic, this position-based

algorithm works directly with the GPS positional data. The new logic, as with the old,

extrapolates missing positions using velocity information until both trailing and leading aircraft

updates are acquired.

Figure 6 shows the logic. For example, upon receiving a GPS position update for the leading

aircraft, the position-based logic checks whether a GPS position update for the trailing aircraft has

also been received. If not, the logic determines if it has received the trailing aircraft GPS position

update in a previous frame by checking whether a logical flag, the trailing aircraft bit, has

previously been set high. If the bit is not high, a second logical flag, the leading aircraft bit, is set

high to indicate that a leading aircraft update has been received. The trailing aircraft position then is

extrapolated using velocity information and the known GPS sampling rate. If a trailing aircraft

update is received in a subsequent frame without a leading aircraft update, the logic checks whether

the leading aircraft bit is high. If the bit is high, as it is in this example, both the leading and

trailing aircraft bits are reset to low and the relative position calculation continues without

extrapolation.

7
Yes

Yes

No

Yes

Set leading I

aircraft bit

high

i

trailing aircraft

position

l

1 :TI

[°°-I relative

position @

No

Yes

aircraft

Yes

aircraft bit

No

Set trailing

aircraft bit

high

alrcraft bit

Yes

Extrapolate I

trailing aircraft

position

aircraft bit

Yes

Extrapolate Extrapolate

leading aircraft leading aircraft

position

Figure 6. Position-based synchronization logic.

No

010198

The new logic was tested in the simulation and appeared to work flawlessly. No relative

position spikes existed, and the complementary filter successfully combined the INS and GPS

measurements. The software then was promoted to the aircraft and used in flight.

POSI_ON-BASED ALGO_THM FLIGHT TEST RESULTS

Upon execution of the new software in flight, large, unexplained, relative position biases became

apparent. Figure 7 shows a 300-ft relative position bias reported by the complementary filter

that disappeared when the guidance algorithm was reset.
-300

-400

-500

Relative

longitudinal

position, ft -600

-7OO

-800

I I I I I I I I

/

I

/

I

I

I

I

I

I

I

I

I

I

Position bias Algorithm reset

I I. I

Position

Estimated

------ Actual

I I I I I I I

0 20 40 60 80 100 120 140 160 180 200

Time, sec 010199

Figure 7. Position bias in flight data.

Close analysis of the data revealed a flaw in the position-based synchronization logic

initialization routine. The logic assumes that the system will initialize only when both aircraft

are waiting for GPS updates; it does not account for the situation in which one aircraft already

has received a GPS update and the other has not. Therefore, the bits upon which the logic relies

are initialized into incorrect states. When the algorithm begins in this asynchronous state,

unneeded position extrapolations are completed, resulting in a relative position bias. The only

way to eliminate the bias is to reset the algorithm until it initializes in a synchronous state.

To correct the algorithm, adding more complex logic to account for the asynchronous

initialization state would have been necessary. The same flight, however, revealed that the

air-to-air telemetry simulator did not correctly model the PCM message structure. The air-to-air

telemetry system puts the positional information in the same message as the UTC, which

indicates that the original simulation results are invalid. Not only is the UTC-based algorithm not

flawed, it is immune from initialization issues found in the position-based algorithm.

The simulation has been corrected to provide concurrent information from the current value table,

and the algorithm has been retested. No relative position spikes were observed, and the algorithm

performed well. The complex algorithm therefore has been abandoned and the simpler

UTC-based algorithm has been promoted to the aircraft.

9
TIME-BASED ALGORITHM FLIGHT TEST RESULTS

The guidance algorithm with the UTC-based synchronization algorithm also has been tested

onboard the SRA. Throughout the flights, no relative position spikes were observed. The

complementary filter successfully combined the GPS and INS relative position measurements

returning position estimates with less than a 7-ft error. Figure 8 shows postflight, carrier phase,

ground station-corrected differential GPS relative positions compared with the complementary

filter outputs.

-250

Complementary filter

---- Ground station--corrected

Longitudinal -300

relative

position, it -350

-4O0

-40

.____kAI 1 I I I I I

-50

Lateral

relative -60

position, ft

-70

-80

60

5O

Vertical

relative 40

position, ft

3O

20

I ,_ I IA _ I I I

V ?

I JI I I I i: I !

0 20 40 60 80 100 120 140 160

Time, sec 010200

Figure 8. Filter output and ground station-corrected position.

Figure 9 shows the complementary filter inputs and output; figure 10 shows an expanded scale

plot with more detail. The plots clearly demonstrate the need for the complementary filter. The

GPS measurements are updated only at 2 samples/see, and the INS-derived measurements slowly

drift over time. Alone, each measurement is insufficient. The complementary filter, however,

maintains the low-frequency component of the GPS signal and the high-frequency component of

the INS signal, producing accurate position estimates.

10
GPS-measured relative position

------ INS-measured relative position

........ Filter output

-250I-- I I I I I --

Longitudinal -300

relative

position, It -350

-400 I I I I I -

Lateral

relative

position, ft

400

3OO

2OO

IO0

0

-100

I I I i I

..,.,

Vertical

relative

position, ft

60

40

20

I I I I I

I [ I i I

20 40 60 80 100 120

Time, sec 010201

Figure 9. Complementary filter inputs and output.

The effects of the synchronization algorithm are apparent in figure 10. The GPS position

estimates are dominated by the nature of the 2 samples/sec, but small changes in relative position

estimates are also apparent. These changes are the result of imperfect position extrapolations.

When the algorithm is waiting for an aircraft GPS position update, it imperfectly extrapolates the

position. When the position update is provided, a small step occurs as the algorithm switches

from the estimated to the true position.

The INS-derived relative position drift is caused by small differences in the INS-reported

velocities of each aircraft. The velocity difference is integrated to obtain relative position

estimates, which exacerbates the velocity differences. A ramping bias is the net result. The drift

is especially clear in the lateral axis; a 300-ft drift occurs over a period of 2 rain.

11
-380

-385

Longltudlnal -390

relative

position, tt -395

-400

-405

GPS-measured relative position

------ INS-measured relative position

........ Filter output

_..I I I I I 1 I _

"!::"---::i::::-..,. ....... ..............................

I I L I -"--"l---:r I -1---''_

Lateral

relative

position, ft

-50

-60

-70

-80

I I I I I I I

............... °'° .... ,-,,i.,°. ......... ,o...oo.oo°,, ..... °°°D=I°, ...... .°° ...... " ....... ° ...... ° .... ° ..... ° .......

l ] I ] I I I !

Vertical

relative

position, ft

31

30

29

28

27

26

2.0

I I I I _ ....

i I I -

2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0

Time, uc 010202.

Figure 10. Complementary filter inputs and output (expanded scale)

CONCLUDING REMARKS

This report presented an overview of the Autonomous Formation Flight (AFF) program and its

objectives, approach, and use of a complementary filter to obtain relative position estimates.

The effects of misinterpreted simulation data on the flight test program were demonstrated.

When the AFF simulation indicated a flaw in a position synchronization algorithm based on

coordinated universal time (UTC), the project switched to a position-based algorithm. Tested in

the AFF simulation, the position-based algorithm showed potential to work well in flight. The

simulation testing, however, did not consider variations in initial states of global positioning

system (GPS) updates. Relative position biases caused by initializing in asynchronous states

therefore were not detected until flight.

To correct the position-based algorithm, additional complexity would have had to been added.

The same flight, however, indicated that the UTC-based synchronization flaw was nonexistent; it

was caused by a simulation error. The air-to-air telemetry simulation used a current value table

that did not provide concurrent positional and UTC information. The UTC-based algorithm,

which was immune from the initialization problem, therefore was reimplemented, tested, and

taken to flight. The system was successful in obtaining relative position estimates with less than

a 7-fl error.

12
REFERENCES

I Sitz,JoelR.,F-18Systems Research Aircraft Facility, NASA TM-4433, 1992. (Also published

as SAE-922063.)

z Carter, John, Production Support Flight Control Computers: Research Capability for F/A-18

Aircraft at Dryden Flight Research Center, NASA TM-97-206233, 1997.

3 Norlin, Ken A., Flight Simulation Software at NASA Dryden Flight Research Center, NASA

TM-104315, 1995. (Also published as AIAA-95-3419.)

4 Beukenberg, Markus and Dietrich Hummel, "Aerodynamics, Performance and Control of

Airplanes in Formation Flight," Proceedings of the 17th Congress of the International Council of

the Aeronautical Sciences (ICAS), vol. 2, Sept. 1990, pp. 1777-1794.

5 Parkinson, Bradford W. and James J. Spilker, Jr., eds., Global Positioning System: Theory and

Applications, vol. I, American Institute of Aeronautics and Astronautics, Inc., Washington, D.C.,

1996, pp. 478-481.

6 Brown, Robert Grover and Patrick Y. C. Hwang, Introduction to Random Signals and Applied

Kalman Filtering, John Wiley & Sons, New York, 1997.

13
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1. AGENCY USE ONLY (Leave blank) 2. REPORT DATE 3. REPORTTYPE AND DATES COVERED

November 2001 Technical Memorandum

4. TITLE AND SUBTITLE

Data Synchronization

System

Discrepancies in a Formation Right Control

6.AUTHOR(S)

Jack Ryan, Curtis E. Hanson, Ken A. Norlin, and Michael Allen

7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(E'S)

NASA Dryden Right Research Center

P.O. Box 273

Edwards, California 93523-0273

9.SPONSORING/MONITORING AGENCYNAME(S)ANDADDRESS(ES)

National Aeronautics and Space Administration

Washington, DC 20546-0001

5. FUNDING NUMBERS

710-70-14-E8-28-00-AFF

8. PERFORMING ORGANIZATION

REPORT NUMBER

H-2470

, ,, ,,

10. SPONSORING/MONITORING

AGENCY REPORT NUMBER

NASA/TM-2001-210720

1i. SUPPLEMENTARY NOTES

Presented at the 32nd Annual Society of Right Test Engineers Symposium, 10-14 September 2001.

12a.DISTRIBUTION/AVAILABILITY STATEMENT

Unclassified--Unlimited

Subject Category 04

12b. DISTRIBUTION CODE

13. ABSTRACT (Maximum 200 words)

Aircraft hardware-in-the-loop simulation is an invaluable tool to flight test engineers; it reveals design and

implementation flaws while operatingin a controlled environment. Engineers, however, must always be skeptical of the results and analyze them within their proper context. Engineers must carefully ascertain whether an

anomaly that occurs in the simulation will also occur in flight. This report presents a chronology illustrating

how misleading simulation timing problems led to the implementation of an overly complex position data synchronization guidance algorithm in place of a simpler one. The report illustrates problems caused by the complex algorithm and how the simpler algorithm was chosen in the end. Brief descriptions of the project

objectives, approach, and simulation are presented. The misleading simulation results and the conclusions then

drawn are presented. The complex and simple guidance algorithms are presented with flight data illustrating

their relative success.

14. SUBJECTTERMS

Global Positioning System, Inertial navigation,

simulation, Universal time

17. SECURITY CLASSIFICATION 18. SECURITY CLASSIFICATION

OF REPORT OF THIS PAGE

Unclassified Unclassified

i

NSN 7540-01-280-5500

Automatic control, Flight

19. SECURITY CLASSIRCATION

OF ABSTRACT

Unclassified

Available from the NASA Center for AeroSpace Information, 800 Elkridge Landing Road,

Linthicum Heights, MD 21090; (301)621-0390

15. NUMBER OF PAGES

]6

16. PRICE CODE

AO4

20. LIMITATION OF AB,'_TP,ACT

Unlimited

Standard Form 298 (Rev. 2-89)

Prescribed by ANSI Std_ Z39-18

298-102