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(NASA-CB-17786g) A LiFINITIC K STUD Y OF AN

ADVANCt D DAT A CCHECTICN AMD ICCAIION SYSTEM

(ADCIS) Final ieport (Ecosystems

Ittercaticndl, Ice.) 126 p HC AC7/MF A01

CSCL 05B G3/82

N86-2

Unclas

42923
FINAL REPORT

A DEFINITION STUDY OF AN ADVANCED DATA

COLLECTION AND LOCATION SYSTEM (ADCLS)

PREPARED FOR:

GODDARD SPACE FLIGHT CENTER

GREENBELT, MARYLAND 20771

CONTRACT NO. NAS5-28791

BY:

ECOSYSTEMS INTERNATIONAL, INC.

P.O. BOX 225

GAMBRILLS, MARYLAND 21054

JANUARY, 1986
TABLE OF CONTENTS

SECTION TITLE PAGE

1 .0

2.0

3.0

4.0

5.0

0

LIST OF TABLES i

LIST OF FIGURES

EXECUTIVE SUMMARY

FOREWORD

PHILOSOPHY OF THE APPROACH

DATA AND DATA LIMITATIONS

USER CONSTITUENCY

5.1 APPROACH

5.2 CONSISTENCY OF CONVENTIONAL USERS OF

SERVICE ARGOS

5.3 TEST OF SERVICE ARGOS FORECASTS OF

CONVENTIONAL USERS-MAJORS U.S. AGENCIES

AND INSTITUTIONS

5.4 POTENTIAL CONSTITUENCY OF LATENT USERS....

5 . 5 CONSTITUENCY OF PEAK USERS

5.6 CONSTITUENCY OF EOS USERS

5.6.1 ILLUSTRATION: CALIBRATION OF

MICROWAVE RADIOMETERS BY IN-SITU

DATA

5.6.2 ILLUSTRATION: CALIBRATION OF THERMAL

INFRARED RADIOMETERS BY IN-SITU

DATA

5.6.3 DESIRABILITY OF CALIBRATION

5.6.4 ASSESSMENT OF THE EOS USER

REQUIREMENTS FOR IN-SITU DATA

5 . 7 INTEGRATION OF USER CONSTITUENCY

THE CAPABILITY OF ARGOS TO SERVE THE USER

CONSTITUENCY

6.1 APPROACH

6.2 THE TOAL IMMUNITY (OPTIMISTIC)

ASSUMPTION

6.3 THE ZERO IMMUNITY (PESSIMISTIC)

ASSUMPTION

6.4 THE PARTIAL IMMUNITY (REALISTIC)

ASSUMPTION

ii

V

1

4

5

7

10

10

11

16

30

41

45

47

49

49

50

53

60

60

62

69

72
TABLE OF CONTENTS (CONTINUED)

SECTION TITLE PAGE

6.5 THE CASE OF TWO ARGOS SATELLITES 78

6.6 THE LIMITING PERFORMANCE 79

6.7 THE CASE OF THE POSITION FIX FOR

DRIFTERS 80

7.0 ADCLS REQUIREMENTS 86

7.1 LIMITATIONS OF ARGOS AND OPTIONS FOR

IMPROVEMENT 86

7.2 OPTIONS IN THE SPACE DOMAIN 87

7.2.1 RESTRICT THE FIELD OF VIEW 87

7.2.2 PROVIDE SPACE DIVERSITY

RECEPTION 87

7.3 OPTIONS IN THE INFORMATION EXTRACTION

DOMAIN •. 90

7.3.1 NARROW THE ACQUISITION AND

TRACKING BANDWIDTH 90

7.3.2 MODIFY THE TRANSMISSION RATE 91

7.3.3 EXPLOIT PHASE INFORMATION 95

7.4 OPTIONS IN THE FREQUENCY DOMAIN 95

7.4.1 INCREASE THE SYSTEM'S BANDWIDTH 96

7.4.2 USE OF PLATFORM POLLING POLICY 97

7.5 SYNTHESIS OF THE ADCLS REQUIREMENTS 99

7.5.1 SCREENING OF OPTIONS 99

7.5.2 COMPARISON OF "BEST" OPTIONS 102

8.0 ADCLS SPECIFICATIONS AND GENERAL CONFIGURATIONS 108

8.1 ADCLS SPECIFICATIONS 108

.8.2 GENERAL CONFIGURATION OF ADCLS 109

8.2.1 PHYSICAL CHARACTERISTICS 112

8.2.2 COST ESTIMATES 113

REFERENCES 118

PERSONAL CONTACTS 119

QUESTIONNAIRE RESPONDENTS 1 20

11
LIST OF TABLES

TABLE TITLE PAGE

5-1 CONSISTENCY OF ARGOS SUBSCRIBERS AS OF

AUGUST 1985 12

5-2 TRAFFIC REQUIREMENTS OF ARGOS SUBSCRIBERS AS

OF AUGUST 1985 13

5-3 SERVICE ARGOS HISTORICAL STATISTICS AND

FORECASTE 18

5-4 ARGOS SUBSCRIBER CONSTITUENCY VERSUS

GEOGRAPHIC LOCATION AND VERSUS TIME 19

5-5 BUOY PLATFORM CONSTITUENCY OF PRINCIPAL U.S.

AGENCIES AND INSTITUTIONS 26

5-6 SUMMARY OF PROJECTIONS OF PLATFORM CONSTITUENCIES BY U.S. AGENCIES AND INSTITUTIONS 29

5-7 PROJECTION OF PLATFORMS CONSTITUENCIES BY U.S

AGENCIES AND INSTITUTIONS-UPGRADED TO REFLECT

REDUCTION IN PLATFORM COSTS 32

5-8 ENVIRONMENTAL MONITORING ACTIVITIES AS OF 1979

BY FIXED SURFACE STATIONS 34

5-9 DISTRIBUTION OF GOES DCS DATA COLLECTION

PLATFORMS BY USING AGENCY AUGUST 1985 35

5-10 DISTRIBUTION OF GOES DATA COLLECTION PLATFORMS

BY APPLICATION AUGUST 1985 35

5-11 TYPICAL COSTS OF DATA RELAY SYSTEMS FOR INS ITU PLATFORMS-GROUND PORTION 42

5-12 NUMBER OF PLATFORMS FORECASTED TO BE

DEPLOYED BY PEAK USERS 44

5-13 ESTIMATED NUMBER OF PLATFORMS THAT WILL BE

DEPLOYED BY PEAK SUBSCRIBERS, INCLUDING

ADDITIONS FOR PROGRAMS NOT YET IDENTIFIED 46

5-14 IN-SITU CALIBRATION REQUIREMENTS OF EOS

SCIENTIFIC USERS 51

5-15 NON-REDUNDANT IN-SITU PLATFORM REQUIREMENTS

OF EOS SCIENTIFIC USERS 54

5-16 INTEGRATED USER FORECAST-PESSIMISTIC APPROACH.. 56

5-17 INTEGRATED USER FORECAST-OPTIMISTIC APPROACH... 57

6-1 ARGOS SYSTEM SATURATION THRESHOLD IDEAL

CASE - 4 CHANNELS 68

6-2 TWERLE/RAMS SYSTEM SPECIFICATIONS 73

iii
LIST OF TABLES (CONTINUED)

TABLE TITLE PAGE

6-3 ALLOWABLE MAXIMUM ONE-SHOT PROBABILITY OF

INTERFERENCE PARTIAL IMMUNITY, REALISTIC

ASSUMPTION 77

6-4 MAXIMUM ALLOWABLE ONE SHOT PROBABILITY OF

INTERFERENCE AS A FUNCTION OF THE ALLOWABLE

DATA LOSS - TWO SATELLITES 78

6-5 MAXIMUM ERLANG TRAFFIC DEMAND PER FOOTPRINT

THAT CAN BE HANDLED BY 2 ARGOS II SATELLITES

HAVING 8 CHANNELS EACH 79

7-1 TRADEOFFS FACTORS OF ADCLS OPTIONS 107

8-1 PHYSICAL CHARACTERISTICS ESTIMATES OF VARIOUS

ADCLS COMPONENTS 114

IV
LIST OF FIGURES

FIGURE TITLE PAGE

A FORECASTED GROWTH OF IN-SITU PLATFORMS AND ESTIMATED ARGOS SATURATION LEVELS.... 2

5-1 ARGOS PLATFORM GEOGRAPHIC DISTRIBUTION

DECEMBER 1 983 15

5-2 ARGOS PLATFORM POPULATION PER FOOTPRINT

DECEMBER 1983 17

5-3 ARGOS PLATFORM POPULATION AND TRAFFIC DEMAND

PER FOOTPRINT YEAR 2000 20

5-4 DRIFTING BUOY MISSION SPECTRUM (COURTESY

NDBC) 24

5-5 EFFECT OF COST REDUCTION ON NUMBER OF PLATFORMS 31

5-6 EXPECTED REDUCTION OF PLATFORM COSTS WITH

TIME 31

5-7 HISTORICAL GROWTH OF GOES/DCS DATA COLLECTION

PLATFORMS (DCP) 37

5-8 ESTIMATED LOGISTIC GROWTH OF GOES DCS

PLATFORMS 39

5-9 TOTAL USER PLATFORM POPULATION AND TRAFFIC

DEMAND PER FOOTPRINT YEAR 2000-MEAN FORECAST... 59

6-1 POWER LEVEL ALONG RADIUS OF MAJOR DIAMETER

OF ARGOS FOOTPRINT 63

6-2 CHANNEL BLOCKAGE VERSUS TRAFFIC DEMAND-FIRST

ATTEMPT TOTAL IMMUNITY, OPTIMISTIC ASSUMPTION.. 66

6-3 PROBABILITY OF LOSS OF FIX VERSUS PROBABILITY

OF ONE SHOT INTERFERENCE DURING ONE SATELLITE

PASS 82

6-4 PROBABILITY OF LOSS OF FIX VERSUS PROBABILITY

OF LOSS OF DATA FOR DRIFTERS 83

7-1 AVERAGE RECURRENCE INTERVAL VERSUS FOOTPRINT

DIAMETER FOR VARIOUS LATITUDES 88

7-2 EFFECT OF VARYING PLATFORM TRANSMISSION INTERVAL-PARTIAL IMMUNITY (REALISTIC) ASSUMPTION.... 94

8-1 THE OVERALL ADCLS SYSTEM 110

8-2 MAJOR ELEMENTS OF ADCLS CONFIGURATION 111

8-3 ELEMENTS OF THE COST MODEL 116
1.0 EXECUTIVE SUMMARY

The purpose of this effort is to assess the technical and

economic advantage of developing an Advanced Data Collection and

Location System (ADCLS) to operate within the Earth observation

System (EOS) planned for Polar Platform, as a replacement and/or

augmentation of the existing ARGOS data coleection system. The

cost/effectiveness of ADCLS with respect to ARGOS hinges on the

trafffic and quality of service demand of the future user

constituency.

The latter falls into four categories: 1) Conventional

users, that are currently subscribing to ARGOS, and their

expected future growth; 2) Latent users, that currently use data

collection systems other than ARGOS, but that may become future

subscribers to ADCLS for reasons of improved quality and lower

costs; 3) Peak users, that conduct international experiments

utilizing massive numbers of in-situ platforms for limited

periods of time; 4) EOS users, i.e.', scientists that will use EOS

data and that need "surface" or "atmospheric" truth to calibrate

their data sets.

A middle-of-the-road forecast of the aggregate number and

traffic requirements of these user's platforms indicates the

following world-wide totals as a function of time:

1990 1995 2000

Number of platforms 7,860 15,800 18,500

Traffic demand, erlangs 61 94 107

These totals are distributed unevenly over the globe: in year

2000, for example, the densest satellite footprint (over Europe

and the Mediterranean) will contain about 3,000 platforms and

require about 20 erlangs in traffic demand. The least dense

(over the south Indian Ocean) will contain less than 30

platforms, generating a traffic demand less than 0.2 erlangs.
Number

of Users

Densest

Footprint

Saturation

600

1985 1990 1995 2000

Year

Exhibit A. Forcasted Growth of Insitu Platforms and

Estimated ARGOS Saturation Levels
Current users are by and large satisfied with ARGOS performance. ARGOS's principal future drawback is that it will saturate, i.e., will not be able to meet the requirements of the platform's traffic demand. Exhibit A depicts the ARGOS saturation

and estimated users by year 2000. The figure shows that ARGOS

system may saturate by 1990 if the system is used for data or

location only. For a fifty-fifty distribution of data and location platforms the ARGOS saturation will also be by year 1990.

This constraint will manifest itself in two ways: i)

excessive loss of platform-derived data—users indicate that they

will not tolerate more than 5%-10% loss; and ii) loss of position

fixes--future users will require no more than 20% loss of fix

data. Some alleviation of the saturation problem can be achieved

if the proposed ARGOS II is deployed: however, this will extend

the saturation date to no later than 1995.

The principal, optimal remedial measures to ARGOS saturation

are: i) use of a broad-footprint interferometer, capable of

providing a position fix with one platform message per satellite

pass instead of the five messages currently required; ii)

increase of the r.f. bandwidth to ~ 100 kHz from the current

25 kHz. These measures will not require modifications to the

current design of platform transmitters, thus will add no burden

to the users. With these modifications the ADCLS will be able to

accommodate up to 5,000-7,000 platforms per footprint, leaving

margin for further growth in the number of platforms beyond year

2000.
2.0 FOREWORD

The purpose of this report is to provide the Goddard Space

Flight Center with an assessment of the technical and economic

desirability of developing an Advanced Data Collection and

Location System (ADCLS), as part of the Earth Observation System

(EOS) planned to be installed aboard the Polar Platform; to

document tradeoffs between ADCLS and the existing ARGOS data

collection system; to specify the characteristics and to

structure a top-level configuration of an ADCLS.
3.0 PHILOSPHY OF THE APPROACH

The purpose of this effort is to assess the overall cost

effectiveness of developing, implementing, and deploying an

Advanced Data Collection and Location System (ADCLS) for use in

relaying world-wide data from in-situ platforms to scientific

users, either directly or through the intermediary of suitable

ground stations and data dissemination networks.

NASA is currently in the process of defining an Earth

Observation System (EOS) to be deployed on the Polar Platform (an

element of the Space Station system) approximately in 1992,

intended to provide the international scientific communities the

opportunity to investigate global phenomena related to assessing

and forecasting key environmental processes affecting life and

well-being on earth.

The ADCLS is being considered by NASA as a potential

addition to EOS, to supplement the data provided by EOS remote

sensors through data gathered in-situ from land and oceanic

surfaces and atmospheric platforms. Additionally, ADCLS could

take over selected portions and the overflow of the traffic

generated world-wide by fixed in-situ platforms that perform

environmental measurements on a routine or ad-hoc basis.

Two systems for relaying in-situ data are currently

operational. The GOES Data Collection System (DCS) relays data

only, and is best suited to relaying information collected by

fixed platforms of known position. The ARGOS system relays data

and can provide position location, and is thus suitable for use

with moving or drifting platforms, where the data need to be

correlated with the location in which they are gathered.

The need for the service that ADCLS can provide depends upon

two factors: a) will the growing user constituency eventually
exceed the traffic handling capability offered by ARGOS and GOES,

thus requiring a supplementary data throughput capacity; and b)

will future users require a quality of service not currently

supplied by ARGOS and/or GOES.

The cost effectiveness of ADCLS hinges upon what is the

"value" of these added services with respect to its cost to the

user community, and the cost of the ADCLS system to NASA.

Our approach proceeds along the following logical steps:

• Assess the future traffic demand and quality of service

desired by users of in-situ data, up to year 2000.

• Assess the factors that drive the users' willingness to

expand their in-situ data collection systems—assess how

these factors evolve with time, and the consequent

increase in user constituency.

• Assess whether ARGOS and/or GOES, or future improvements

thereof, can meet the requirements of the future traffic

demand.

• In the event that ARGOS and/or GOES should turn out to

be deficient with respect to users' needs, assess the

technical/operational improvements needed to meet the

future users' demands.

• From these, develop and apply criteria to define an

optimal configuration for the ADCLS instrument.
4.0 DATA AND DATA LIMITATIONS

Key to the technical choice of ADCLS versus ARGOS is the

credible forecast of future traffic demand on the part of the

users. To construct our forecast, we have sought the best and

most reliable data that are available. This was done by three

methods: i) by querying the users and the ARGOS systems'

operator; ii) by analyzing historical data to uncover internal

evidence of growth trends; and iii) by estimating the future

evolution of the factors that govern the number of in-situ

platforms, key among which is cost. Our forecast assumes

conditions of continued steady state evolution of the U.S. and

international situation, and continued interest in science on the

part of the various governments involved. The forecast cannot

and does not take into account the occurrence of "breakthroughs"

or of a radically changed international situation—events that

are not predictable.

The sources of data that we used, together with a value

assessment for each, are as follows.

• The current constituency of ARGOS subscribers, and the

forecast of future subscribers, were obtained from

Service ARGOS. Since Service ARGOS is the "owner" of

the system, and is supported by the system's revenue,

the presumption is that their forecast represents a

thoughtful, reliable source of data.

• To validate the forecasts supplied by Service ARGOS, the

current consistency of subscribers, their

characteristics, budgets, anticipated growth, degree of

satisfaction with ARGOS, and future needs, were obtained

by querying fourteen principal U.S. agencies and

academic institutions currently availing themselves of

the ARGOS service. The data collected offer a good

assessment of current numbers, characteristics and
desires of users of in-situ platforms. The forecasts by

this community, however, are generally limited to the

short range. Most of them do not extend beyond 5 years,

a few go as far as 1995.

The historical constituency and composition of

subscribers of the GOES/DCS system was obtained from

NESDIS. Our objective was to determine the saturation

level of GOES/DCS, in order to assess whether the

growing constituency of GOES/DCS users could and. would

eventually spill over onto other services, e.g. ADCLS.

The NESDIS data are excellent, and sufficiently detailed

to allow computing the "logistic growth" of GOES/DCS

users.

The historical cost reduction of platform systems were

obtained from historical series (some dating back to the

1950's), and from detailed investigation of recent

prices of platform components -- that, we found,

substantially confirm the historical trends. This data

serves to gage the additional number of platforms that

users can be expected to procure as a result of lowered

platform costs. These data appear to be highly

reliable.

The expected deployment of in-situ platforms on occasion

of future major international scientific programs--

primarily dealing with the oceans—was obtained from

NOAA and NSF. Our objective was to assess the extra

number of platforms—above and beyond conventional uses-

-that such major programs would generate. While the

descriptions of the proposed experiments are excellent,

their funding status and era of realization are in most

cases not quantified precisely. The corresponding

forecasts ought therefore to be viewed with a degree of

reservation.
• The in-situ needs of prospective EOS experimenters were

derived from queries to scientists making up the EOS

steering committee. The responses were supplemented by

discussions with NASA scientific investigators. In view

of the fact that the EOS is still undergoing definition

of its functional requirements, these data ought to be

considered indicative rather than final.

In summary, we believe that the significant number of the

data collected, their methodical crosschecking, and the fact that

they were collected from numerous independent sources—thus

overestimates and underestimates among sources tend to compensate

statistically—supplies a reasonable estimate of the future

constituency and traffic demand within which a potential future

ADCLS will have to operate.
5.0 USER CONSTITUENCY

5.1 Approach

The purpose of this effort is to assess, up to year 2000,

the volume of traffic, as a function of time and geographic

location, expected to be generated by potential users of ARGOS

and/or ADCLS.

The following user groups are considered as actual or

potential candidates for ARGOS or ADCLS up to year 2000:

= Conventional users, i.e., the scientific user community

that is currently utilizing ARGOS, and that plans to

continue utilizing any future expansion thereof—and

that may eventually "switch over" to ADCLS should the

future ARGOS system be unable to meet their

requirements—or offer substantially lower costs.

= Latent lasers, i.e., additional users that may subscribe

to the system by virtue of quality advances or of

reduced costs (either costs of the terrestrial equipment

and/or service charges).

Latent users fall into the two subcategories of

scientific and commercial applications.

= Peak users, representing unusually large deployment of

surface sensors for limited time periods on special

occasions, e.g. international cooperative scientific

programs.

EOS users, i.e., scientists planning to analyze data

from the EOS polar platform and who require calibration

of EOS sensors by means of "surface truth" or

"atmospheric truth", as well as supplementary in-situ

data that cannot be gathered remotely.

10
There is no single source of data that provides a completely

reliable forecast of the numbers of these users and the traffic

that they are likely to generate. We have gathered the best

available forecast data, compared them, reconciled discrepancies

and filled in the gaps by means of reasoned extrapolations,

correlations and adjustments.

5.2 Consistency of Conventional Users of Service ARGOS

Forecasts produced by the system's operator and revenuegetter (Service ARGOS) ought to be regarded as a highly

authoritative source of data.

The highlights of the forecast by Service ARGOS are as

follows.

Table 5-1 depicts the August 1985 constituency of ARGOS

subscribers, as supplied in personal communication to Mr. Lalit

Wanchoo of ECOsystems by Mr. Michel Taillade, Director, Service

ARGOS.

Table 5-2 shows these subscriber's total erlang traffic

demand.<a>

b )

(

a

) The erlang unit is the ratio between the length of the message and the

• time available for its transmission, both expressed in the same units.

For example, a message lasting one minute, transmitted during one

available hour, represents 1/60th of an erlang (16.6 millierlangs).

(b) The traffic demand was derived from data supplied by Service ARGOS through

personal communication and through the ARGOS User's Guide, as follows.

The length of the fixed portion of the message is 160 msec, of unmodulated

carrier (to allow the ARGOS onboard receiver to lock onto the carrier),

plus 48 bits @ 2.5 msec. = 120 msec., for a total of 280 msec. The length

of the variable portion of the message, that conveys sensor data, ranges

from 32 bits = 80 msec, up to 256 bits = 640 msec. Thus the total message,

lengths vary from 280 msec, for "dumb" drifters without sensors (position

location only) up to 920 msec, for sophisticated drifters or moored

buoys. The repetition rates are comprised between 50 and 60 seconds: we

assume 55 seconds in our computations.

11
TABLE 5-1

CONSISTENCY OF ARGOS SUBSCRIBERS AS OF

AUGUST

TYPE OF PLATFORM PLATFORM CONSTITUENCY

Number

Drifter Buoys

Moored Buoys

Fixed Land Stations

Ships

Balloons

Service ARGOS (in-house test purposes)

Miscellaneous Data Relay

(fisheries, wildlife , etc. mostly on land)

TOTAL

DISTRIBUTION

BY OWNERSHIP

GOVERNMENT

PRIVATE

BY FUNCTION

LOCATION

DATA COLLECTION

BY NATIONAL APPURTENANCE

U.S.

NON-U.S.

(France, Canada, FRG, South Africa,

Australia, Norway, U.K., Denmark)

384

72

241

14

1

7

.34

753

670

83

75T

500

253

T5T

414

339

75T

\

a) The number of users active at any one time

number of subscribers.

Percent

(rounded)

51

10

32

2

0

1

4

100

89

1 1

100

66

34

TOD"

55

45

TOTT

equals 80% of the

SOURCE: Service ARGOS Data

12
TABLE 5-2

TRAFFIC REQUIREMENTS OF ARGOS SUBSCRIBERS

AS OF AUGUST 1985^

TYPE OF PLATFORM MILLIERLANGS

PER PLATFORM

Drifter Buoys 6.5

Moored Buoys 17

Fixed Land Stations 6

Ships 17

Balloons 6.5

Service ARGOS in-house tests 17

Miscellaneous 6.5

Total

'

a'The user traffic, i.e., the traffic active

equals 80% of the subscriber's traffic shown in

TOTAL ERLANGS

2.496

1 .224

1 .446

0.238

0.006

0.119

0.221

5.75

at any one time ,

the Table.

SOURCE: ECOsystems elaboration of Service ARGOS Data

13
We distinguish between "subscribers" and "users". The term

subscribers connotes the total constituency of platforms that

enlist into the ARGOS service. The term users connotes the

number of platforms that are active at any one time. It is the

latter that the ARGOS system must service in terras of traffic

handling capability.

Service ARGOS estimates the average user-to-subscriber ratio

to be 0.8. This means that if, say, ARGOS had 1,000 subscribers,

its data relaying segment would need to accommodate 800 users.

With reference to Table 5-2, these users would generate, in

August 1985, world-wide, a total traffic demand of 5.75 x 0.8 =

4.6 erlangs, at any one time.

A curtailment of the ARGOS data handling requirement occurs

because of the geographic spread of the platforms with respect to

the ARGOS's footprint.

Figure 5-1 from Service ARGOS shows the platform's

geographic distribution, in December 1983, by cells measuring 10°

Latitude by 1 o° Longitude.

The area in Km2 subtended by each cell is:

1,110 x 1,11 0 x cos (lat)o =

= 1,232,000 x cos (lat)°

To evaluate the traffic within each footprint, the

subscriber constituency occupying each 10 x 10 cell needs to

be integrated with that of neighboring cells aggregating the

total area subtended by an ARGOS footprint. Assuming a minimum

elevation of the DCP-to-satellite line of sight of 5 (for

adequate signal reception), simple trigonometric computations

yield that the radius of the "footprint" subtends:

14
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15
22.5° in latitude

22.5° x cos (lat)° in longitude

A synthetic representation of the footprint can be obtained

by replacing the ellipsoid with a rectangle having the same

area. The synthetic footprint subtends 40° in latitude (in the

north-south direction), 40° in longitude at the equator (in the

east-west direction), and an increasing longitude arc at the

higher latitudes. This is represented schematically in Figure 5-

2 (for December, 1983).

The subscriber count per footprint was upgraded by the

growth in the number of subscribers after December 1983, by using

Table 5-3 which shows the Service ARGOS forecasts to year 2000.

Assuming that the "mix" of platform traffic, Table 5-2, as well

as the subscriber-to-user ratio, remain constant throughout

geographic regions and with time, Table 5-4 shows the number of

subscribers and their traffic demand per footprint as a function

of time.

Figure 5-3 depicts the estimated number of ARGOS

subscribers, and their traffic demand, in 2000, by geographic

distribution.

5.3 Test of Service ARGOS Forecasts of .Conventional Users -

Major D.S. Agencies and Institutions

The intent here was to perform a "reasonableness test" of

the service ARGOS forecasts. To this effect, we analyzed and

compared the projections of major U.S. agencies that utilize

ARGOS-addressable platforms.

16
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20

ORIGINAL PAGE IS

OF POOR QUALITY
NDBC has experienced a growth in the number of moored buoys

from 10 in 1976 to 59 in 1984 <a) » equivalent to a yearly

compound growth rate of 25%. Although the number of moored buoys

is not large with respect to that of drifters, each moored buoy

generates considerably more traffic than a drifter. Thus the

moored buoy's "traffic weight" is higher than that of the

drifters (by approximately three times).

According to NDBC, much of the reason for the growth

experienced up to 1984 is that, in the 10 years elapsed from 1974

to 1984, costs of the electronics have dropped by a factor of 10,

buoy system reliability has increased tenfold (thus further

contributing to reducing overall costs), and the utility of

moored buoys has been amply validated and recognized, so that

increasing uses have been developed for their services. As an

example, the Coast Guard has recently begun to implement its own

moored buoy system, designated C-MAN (Coastal Marine Network),

that is managed by NDBC.

As a "reasonableness test" on extrapolating the moored buoy

population, we observe that the drop in electronic equipment

costs reported by NDBC (factor of TO in 10 years) parallels the

historical cost decrease of sophisticated electronic equipment

(e.g., computers), that since the 1950's has averaged

approximately 0.8/year compound (that .is, if the cost in the

first year is 1, in the second it becomes 0.8, in the third 0.8 x

0.8 = 0.64, and so forth). The costs of the buoy's mechanical

structure have dropped at a lesser rate, approximately a factor

of 3 over the 1974-1984 time span (equivalent to a yearly

decrease of 0.9).

(a) NDBC FY 1984 Annual Report, January 1985, U.S. DOC/NOAA

National Data Buoy Center, NSTL, MS39529.

21
Currently, the respective cost ratios are of the order of 60-70%

for the electronics, 30 to 40% for the structure. Assuming that

the historical cost reduction will continue at the same rate

experienced in the past (there appears to be no reason to the

contrary) , the year 2000 buoys ought to cost approximately one

tenth of current costs. In theory then, and assuming constant

NDBC budgets, the year 2000 NDBC moored buoy population ought to

approximate ten times the 1985 population, (estimated at 59 x

1.25 = 73), or roughly 730: not counting additional "growth

factors" such as increased budgets (as national wealth increases,

and as more applications of greater utility are developed). This

would represent a compound yearly growth rate of 17%. We observe

that the past growth rate has been 25%. We thus extrapolate the

moored buoy population at two compound growth rates: minimum of

17%; maximum of 25%. The extrapolation yields the following

numbers:

1985 1990 1995 2000

Minimum

Maximum

73

73

150

225

330

680

730

2000

We observe that a significant number of NDBC moored buoy

transmissions are currently effected through the GOES DCS.

However, as discussed later in this report, the GOES DCS system

is now saturating, and the development of a more capacious system

does not currently appear to be included in any future funding

plans. If an improved GOES DCS is not funded, moored buoys could

eventually become candidate subscribers for ARGOS and/or ADCLS.

As regards drifters, NDBC's primary responsibility is their

technical improvement, and to act as a procuring agency for users

that so request (several users procure directly from

manufacturers, without passing through NDBC). NDBC buoy

procurements are effected via RFP's to buoy and/or sensor

22
manufacturers. To meet their statutory responsibility, NDBC is

engaging in a thorough program of technical innovation,

reliability improvement, and cost reduction of drifters and

associated sensors and electronics.

Drifters are used in two major categories of applications:

• Measurement of ocean currents: this involves no

sensors, only a transmitter to enable determining the

buoy's location.

• Measurements of ocean parameters (in addition to

location): sea surface temperature; atmospheric

temperature; sea subsurface temperatures (100 to 150

meters, and down to 600 meters); atmospheric pressure

at the ocean's surface; absolute wind speed; wind

direction; subsurface currents (either by means of a

drogue immersed at a desired depth, and that is

entrained by the current at that depth, thus overcoming

the entraining effect of surface currents on the buoy

— or via an immersed string of velocity meters, each

of which conveys its own depth measurement to the

buoy); solar irradiance.

Figure 5-4, courtesy of NDBC, depicts the drifter's mission

spectrum. Drifters are designed to be as economical as

possible: acquisition costs trade off against survival rates.

Typical survival rates quoted by NDBC are: after 3 months-70%;

after 6 months-56%; after 9 months-50%; after 12 months-40%;

after 15 months-34%. A fairly novel technology is represented by

aircraft-dropped drifters. NDBC delivered 90 drifter buoys for

TOGA in 1985. Future plans for deliveries are: 150 drifters in

spring of 1986 (for TOGA), followed by 75 to 100 TOGA drifters

per year for the next 10 years.

23
P_ = Atmospheric Pressure a

|W|= Absolute Wind Velocity

Ta=Atmospheric Temperature

U=Subsurface Current

To=Sea Surface Temperature

SOLAR=Solar Irradiance

Tz=Subsurface Temperature

W=Vector Wind Velocity

IRLS. NIMBUS-6. TIROS-N, NOAA-A, NAV-SAT

POLAR ORBITING SATELLITE

AIDJEX/POLEX/GARP CATE/NORPAX/FCCE/EPOCS/OCS STUDIES/OTEC STUDIES/

SCIENTIFIC STUDIES

• P

1971

1973 197« 1976 1977 1978 1979 1980 1981 1982

Figure 5-4. Drifting Buoy Mission Spectrum

(Courtesy NDBC)

24
Other principal U.S. institutions, queried by telephone and

personal contacts, supplied the current and future platform

constituencies reported in Table 5-5.

Integration of the projections expressed by the

"conventional" U.S. users yields the results shown in Table 5-

6. Note that the projections do not extend much beyond 1990.

This is due to the respondents' natural inability to perceive

what will happen in the more distant future. Two key factors

contained in the user's responses allow us to project the user

constituency further into the future:

• most users assert that the number of platforms that

they will procure and deploy is principally conditioned

by their budgets. The effect is evidenced in Table 5-

5, whence it can be seen that the number of platforms

times their costs approximately equals the user's

budget. Thus, a reduction in platform costs will

result in increased platform numbers. To quantify the

relationship, we observe that the increase is not

strictly proportional to the cost reduction of the

hardware, because some of the user's budget is spent in

data analysis. From user responses, see Table 5-5, we

see that approximately 0.11 data analysis persons are

needed per sophisticated ($15,000) buoy. Assuming an

hourly salary of $20 including benefits, this yields a

yearly burden of $0.11 x 2,080 x $20 = $4,600 per

platform. An orientative ratio of data analysis labor

to capital costs is thus (4,600) * (15,000) = 0.30.

25
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28
TABLE 5-6

SUMMARY OF PROJECTIONS OF PLATFORM CONSTITUENCIES

BY U.S. AGENCIES AND INSTITUTIONS

AGENCY/ INSTITUTION

POLAR SCIENCE CENTER

U.S. COAST GUARD

R&D CENTER

NOAA/ATLANTIC OCEANIC

MARINE LABORATORY

USN OCEANOGRAPHIC

OFFICE

U.S. COAST GUARD

INTERNATIONAL ICE

PATROL

NATIONAL CENTER

FOR ATMOSPHERIC

RESEARCH

VIRGINIA INSTITUTE

FOR MARINE SCIENCE

NOAA/PMEL

NDBC

WOODS HOLE

OTHER (@10%)

TOTAL

1985

22

7

50

3

12

10

3

14

90

50

30

291

(

a) UNFILLED SPACES INDICATE THAT

PROJECTIONS

1987 1990 1995 2000

30 30

7 7

70 100

15 25

12

100 100+

20

15 15 15

1 10 110 110

40 40

40

459

RESPONDENT COULD NOT SUPPLY

29
Assuming this ratio to remain constant for the less

sophisticated platforms, Figure 5-5 shows the effect on

the number of platforms of reducing platform costs.

• platform costs can be confidently forecasted to

decrease with time. Figure 5-6 portrays the trend of

the cost reduction: it is consistent with the cost

trends experienced by NDBC during the last 10 years, by

the scientific community over the last 3 to 4 years,

and by the electronic market since the 1950's.

Combining the factors of Figures 5-5 and 5-6 yields the

upgraded forecast shown in Table 5-7. The Table also shows our

forecast for foreign platforms, on the assumption that these will

continue to maintain a 45% proportion of the total platform

population.

Comparing Table 5-7 with the Service ARGOS forecast of Table

5-4 (repeated at the bottom of Table 5-7) shows that the two

projections are within the same "ballpark"; they differ by only

about _+13% from their common average, although they were derived

by independent methods. We favor the higher forecast, because we

do not believe that Service ARGOS has taken into complete account

the effects of future price reductions.

5.4 Potential Constituency of Latent Users

These are Agencies, industrial concerns and private persons

engaged in gathering in-situ data, on a routine and/or and ad-hoc

basis, and who find it necessary, or convenient and costeffective to have these data transmitted automatically to a

central repository rather than gathered manually.

An example of "necessary" data transmission are the Corps of

Engineers' (COE) rivergage levels in flash-flood-critical areas,

where rapid data conveyance is of the essence. An example

30
Normalized Number

of Platforms

4

I

0.9 0.8 0.7

Figure 5-5.

0.6 0.5 0.4 0.3

Normalized Cost

Effect of Cost Reduction on

Number of Platforms

0.2 0.1

Normalized

Cost

1

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0

Assumptions:

Fractional Costs of Electronics 1985: 65%

Yearly Reduction Coefficient: 0.8

Fractional Costs of Structure 1985: 35%

Yearly Reduction Coefficient: 0.9

I

1985 1990 1995 2000

Figure 5-6. Expected Reduction of Platform

Costs with Time

31
TABLE 5-7

PROJECTION OF PLATFORM CONSTITUENCIES BY

U.S. AGENCIES AND INSTITUTIONS - UPGRADED TO

REFLECT REDUCTION IN PLATFORM COSTS

TOTAL U.S.

TOTAL FOREIGN

WORLD TOTAL

SERVICE ARGOS

PROJECTION,

WORLD TOTAL

AVERAGE

NUMBER OF SUBSCRIBERS

(a)

1985 1987 1990 1995 2000

341

279

630

753

691

DEVIATION 9

FROM AVERAGE.

PERCENT +

509 1,000 2,600 3,000

416 800 2,000 2,500

925 1,800 4,600 5,500

980 1,300 2,400 4,200

952 1,500 3,500 4,850

16 31 13

Multiply by 0.8 to obtain number of users active at any one time.

32 r
of "convenient" data transmissions are the U.S. Geological

Survey's (USGS) rivergage levels in non-critical sites. These

data are needed for historical-statistical purposes with no

particular urgency constraints: in hard-to-access sites, the

cost of automatic data gathering is often less than that of

manual retrieval.

Table 5-8 lists the numbers of such data stations currently

in existence in the U.S., and estimates their total number worldwide.

Most of these users currently employ semi-manual data

retrieval. An example are the USGS river stage gages. Most of

these are instrumented with an automatic recorder, that punches

the river's stage (in feet and fractions thereof) on paper

tape. Approximately half the automated U.S. rivergages effect

this measurement at quarter-hour intervals: one quarter, at

hourly, and another quarter at semihourly intervals. The punched

paper tape is retrieved periodically (typically at one to two

month intervals) by technicians, that also, on that occasion,

perform preventive and/or corrective maintenance.

About 7% of the USGS rivergages are instrumented with data

telemetry over telephone lines. USGS's tradeoff between manual

retrieval and telemetry (other than in cases where real-time data

retrieval is necessary) is based strictly on cost considerations:

i.e., does the actuarial cost of capital telemetry equipment and

telephone service offer savings versus the cost (salary, travel)

of periodic visits to the measurement station by technicians.

A fraction of the data produced by the sensors enumerated in

Table 5-8 is currently telemetered via the GOES DCP system.

Tables 5-9 and 5-10 show the distribution of the GOES DCP usersby Agency and by application.'3' Two elements affect the

question of whether these users are potential future candidates

for ARGOS and/or ADCLS: a) what is the expected growth rate of

33
TABLE 5-8

ENVIRONMENTAL MONITORING ACTIVITIES AS OF 1979

BY FIXED SURFACE STATIONS

UNITED STATES

MEASUREMENT PARAMETERS

Surface Water

Surface Water Quality

Groundwater and Groundwater

Quality

Snowmelt/Soil Moisture

Meteorology

Air Quality

Seismic

Total United States

REST OF THE WORLD

WORLD

APPROXIMATE NUMBER OF

MEASUREMENT STATIONS INSTRUMENTS (SENSORS)

24.800

16,200

51,200

2,000

21,700

9,500

2,200

127,600

125,000 (Est.)

253,000

59,600

162,000

51,200

4,000

65,200

38,000

4,400

384,400

360,000 (Est.)

745,000

SOURCE: Adapted from Report "Modular In-Situ Environmental Sensor System" by

ECOsystems International, Inc., contract NAS5-0-25441.

34
TABLE 5-9

DISTRIBUTION OF GOES DCS DATA COLLECTION PLATFORMS

BY USING AGENCY

AUGUST 1985

AGENCY

CORPS OF ENGINEERS (MOSTLY REAL-TIME NEEDS)

uses

BUREAU OF RECLAMATION

USDA - FOREST SERVICE

STATE GOVERNMENTS

NATIONAL WEATHER SERVICE

BUREAU OF LAND MANAGEMENT

UNIVERSITIES

OTHERS

NATIONAL PARK SERVICE

TOTAL

PERCENT

. . . . 46.00

. . . . 18.00

. . . . 11 .00

. . . . 7.00

. . . . 6.50

. . . . 3. 50

. . . . 2.50

. . . . 2.00

. . . . 2.90

. . . . 0.60

100.00

TABLE 5-10

DISTRIBUTION OF GOES DATA COLLECTION

PLATFORMS BY APPLICATION

AUGUST 1985

APPLICATION PERCENT

HYDROLOGY (MOSTLY RIVERSTAGE, REAL TIME NEEDS) 77

METEOROLOGY (MOSTLY REAL TIME NEEDS) 18

SEISMIC 2

OCEANIC 2

MISCELLANEOUS 1

35
GOES DCS users; b) to what extent can the GOES DCS system meet

the requirements of the user's demand. A reasonable answer to

the first question can be sought by analyzing the historical

pattern of growth of GOES DCS users. Figure 5-7 ^a^ depicts this

historical growth.

We note firstly that the curve is "flattening". The reason

is that GOES DCS, as currently configured, saturates at a level

of utilization of approximately 5,000 users. In fact, between

October 1984 and April 1985, over 900 users were withdrawn or

rejected from the system by NOAA. According to NOAA, the current

saturation is due not to DCS channel availability, but to

insufficiency of the ground processing system. With the

currently planned update of the ground system, NOAA expects the

saturation level to increase to 10,000 users, i.e., the

saturation level of the DCS itself. Thus the saturation trend

indicated in Figure 5-7 is apparent and not real: it is due to

system saturation rather than to "market saturation".

Secondly, we note that the growth trend has been

significant: between 1980 and 1983 (when incipient saturation

set in), it averaged 45% compound per year.

Thirdly, we note that the historical growth curve exhibits

the behavior typical of a "logistic" curve. Logistic behavior

characterizes most growth phenomena, e.g., from automobiles to

radios to passenger-miles of travel. A relatively slow initial

growth is followed by a faster, sustained increase, and ends

finally by flattening out at a certain level known as "market

saturation". The above holds true if there are no constraints to

growth--e.g., the inability of the supply to meet the requirements of the demand (for example, because of system saturation) . The "market saturation" connotes the maximum number of

Courtesy of NESDIS

36
Number of DCP't

5000

4500

4000

3500

3000

2500

2000

1500

1000

500

1978 1979 1980 1981 1982

YEAR

1983 1984 1985

Figure 5-7. Historical Growth of GOES/DCS Data

Collection Platforms (DCP)<a>

(a) Current GOES/DCS saturates at 5,000 users because of ground

system Limitations. Ultimate saturation Level with

unconstrained ground system is ~10,000 users.

37
users that will acquire the product or service, almost regardless

of price. Above the market saturation level, users essentially

say "we do not need any more, even if offered free (or almost

free)". The market saturation level for any commodity is

assessed by means of the "logistic growth curve":

1 + ae-bT

where:

N = number of units at time T

Ns = saturation number of units

a,b = coefficients

T = future time (years)

The parameters a, b, Ns are computed from historical data such as

are shown in Figure 5-7. The computation excludes any portion of

the curve that is "flattening" due to system saturation. It is

clear that the accuracy of the computation is affected by the

consistency of the available data. Logistic growth curves

exhibiting good accuracy are typically constructed from

historical series of 20 years or more. With five years of

available data, the expected accuracy, estimated to be of order +_

30%, is however still adequate for the purposes of this study,

i.e., a 15-year forecast.

The logistic parameters derived from the internal evidence

of the data of Figure 5-8 are approximately:

Ns = 25,000

T90 = 1992 (year of 90% saturation)

a = 50

b = 0.45

Figure 5-8 depicts the expected logistic growth in the absence of

constraining factors. It indicates that approximately 25,000 US

38
Number of

Platforms

25,0001

20.000

15.000

10.000

5.000

0

1975

N <

25.000

1+50e

-0.45T

NaNumber of Platforms

T = Tlme'. Year s

Current Saturation Level,

Current Ground System Limited

1978 1980 1985 1990 1995 2000

Figure 5-8. Estimated Logistic Growth of

GOES DCS Platforms

39
users can be expected to wish to access the GOES DCS system by

year 1995. For the rest of the world, a conservative estimate is

an additional number of users equaling the US users, i.e., a

total of 50,000 users. It is worth repeating that, because of

the shortness of the available historical series, these data are

not more accurate than jK30%.

Three questions are key in assessing the possible role of

ARGOS/ADCLS in this "market":

• Firstly, will GOES/DCS (and its foreign counterparts)

be able to meet the requirements of the anticipated

user demand for service

•

• Secondly, can the discontinuous temporal coverage

provided by ARGOS or ADCLS satisfy the user's

requirements

• Thirdly, what would be the effect on the user's

constituency caused by the fact that the GOES/DCS

service is free, while ARGOS charges a fee

The outlook for the first question is that a more capacious

GOES/DCS system does not currently appear to be included in any

US or European funding plan. The prognosis for the realization

of such a system is at present uncertain. If it is not realized,

a significantly improved ARGOS or a timely ADCLS could address

and aspire to capture a major portion of the GOES/DCS user

"overflow".

As regards the second question, most candidate users do not

require real-time data. For example, most USGS strearagage

records are retrieved once every month or two. Timeliness of

retrieval, i.e. in a matter of hours, is important to certain

users — this can be provided by an improved ARGOS or an ADCLS. If

no advanced GOES/DCS is in the cards, an obvious split would be

40
for the GOES/DCS to accommodate the users requiring real-time

data (minutes to fractional hours), while a polar low earth orbit

(LEO) system such as ARGOS or ADCLS would address the other

users.

With respect to the third question related to the price of

service, we note that currently, the ARGOS service prices are

modest with respect to the capital cost of the telemetry data

formatter, transmitter, and related elements such as power

supply. Table 5-11 compares these costs and indicates that,

while the "free" price of GOES DCS is attractive, it is not an

overwhelming economic determinant. The major determinant for

using GOES DCS appears to be either the real-time need for the

data, or the fact that automatic data retrieval is less costly

than manual collection.

5.5 Constituency of Peak Users

These represent unusually large deployments of surface

sensors, occurring upon occasion of major national and

international cooperative programs.

The principal such programs, planned for the time era up to

year 2000, are:

TOGA (Tropical Ocean Global Atmosphere) will run from 1986

to 1996 in the Southern hemisphere. Principal measurements will

be sea surface temperature, subsurface temperature profile, air

temperature. The International TOGA Project Office in Boulder,

CO. estimates the number of TOGA drifters at 150 per year through

1996, of which 80 to 100 will be U.S. - owned: 60 of these will

be procured through NDBC. NDBC expects that TOGA will experience

a major increase in 1993, with from 300 to 400 new drifting buoys

deployed by several U.S. agencies.

41
TABLE 5-11

TYPICAL COSTS OF DATA RELAY SYSTEMS FOR IN-SITU

PLATFORMS—GROUND PORTION

1985 DOLLARS

CAPITAL COST OF DCP

(Signal Conditioner, Logic

Circuits, Modulator, Transmitter, Antenna)

YEARLY COST OF DCP

(Interest, depreciation,

maintenance)

COST OF DATA LINK, YEARLY

GOES/DCS

ARGOS @ 10% DUTY CYCLE

TYPE OF PLATFORM

SIMPLE

$2,500

$700

0

$250

SOPHISTICATED

$4,000

$1 ,350

0

$360

Source: Adapted from Report "Modular In-Situ Environmental

Sensor System" by ECOsystera International, Inc.,

contract NAS5-0-25441 .

42
OHTSE (Ocean Heat Transport and Storage Experiment) is

being run by NOAA's Environmental Research Laboratory, Miami,

Florida. NOAA estimates about 50 drifters per year from 1987 to

1989, possibly 100 per year by 1990. Budget for buoys is $1

million.

STORM EAST is expected to operate off the U.S. East Coast

beginning circa 1993, using approximately 100 drifters.

STORM WEST is planned to operate off the U.S. West Coast

beginning circa 1996, using between 100 and 200 drifters.

.WOCE (World Ocean Circulation Experiment). Still in the

planning stage by the WOCE Planning Office, with NSF the lead

agency, NOAA and NASA contributing, this major experiment's

budget is proposed at $55 million. Current plans are for a 1990-

1994 yearly deployment of:

• 2,000 current-measuring drifters

• 1,800 pop-up drifters

• 150 temperature-profile drifters

• 350 flux drifters

• 600 acoustically tracked drifters

The program plans to use four satellites, none of which are as

yet launched: N-ROSS, TOPEX, OCI, CRN.

Table 5-12 summarizes these program's data pertinent to

ARGOS and/or ADCLS, based on current plans by the various

Experiment Program and Planning Offices. We note that the WOCE

program dominates the scenario in terms of number of drifters,

but is currently planned to last only 4 years, from 1990 through

1994. Historically, large experiments have been launched at

intervals of 6 to 10 years. Further, the anticipated reduction

in drifter costs will act to encourage additional programs as

time progresses. It is thus reasonable to assume that the number

43
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44
of platforms will not drop suddenly beyond 1994, as Table 5-12

indicates, but will continue at relatively sustained levels.

Table 5-13 aggregates the data and includes a reasonable estimate

for programs, not yet identified, but likely to be implemented in

the 1995-plus time frame.

5.6 Constituency of EOS Users

These are scientists that are planning to analyze data from

the Earth Observing System to be located on Polar Platform—an

element of NASA's Space Station System.

The Working Group Report TM 86129 on Science and Mission

requirements of August 1984, updated by the Report "Earth

Observing System: Implementation Strategy", slated for

publication in February 1986, set forth requirements of the

scientific community for observations from EOS.

We expect that these requirements are subject to change, as

the thinking of the Working Groups and Steering Committee

continues to evolve, and as requirements from the International

Scientific Community are gradually integrated with U.S.

requirements. Nevertheless, the information supplied by the

Working Group can be used as a preliminary "benchmark" to assess

ADCLS requirements.

These requirements stem primarily from the need to calibrate

the earth-observing sensors with in-situ reference data, in order

to enhance the space sensor's absolute and/or relative

accuracy. By absolute accuracy is meant the actual value of the

parameter measured, e.g., ocean surface temperature in degrees

Kelvin; by relative accuracy is meant the differential between

parameters, either as a function of time or between different

geographic locations. Examples of the latter are the difference

in the surface temperature of a given location between noon and

midnight, or between different locations at the same time.

45
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The residual inaccuracies of remote sensors, hence the

desirability of their calibration, derives from two major

causes: i) the fact that the radiation entering most remote

sensors is a combination of desired and extraneous elements,

whose mix varies with location and time. Appropriate calibrators

(e.g., reference electromagnetic generators) are provided onboard earth observing spacecraft to compensate for sensor

drift: however, these calibrators in most cases cannot separate

the desired from extraneous signals, nor can they correct for

measurement biases. Moreover, even the best calibrators are

themselves subject to some drift; ii) the radiation received by

the sensor often is a function of certain target parameters that

are only poorly known, e.g., surface emissivity. Imperfect

knowledge can and frequently does give rises to biases that can

only be eliminated by in-situ calibrations.

The need for calibration varies as a function of the

particular sensor. Let us illustrate the calibration needs of

typical sensors, then recapitulate the various requirements.

5.6.1 Illustration: Calibration of Microwave Radiometers

by In-Situ Data

According to the Working Group reports, References 9, 10,

use of microwave radiometers is planned primarily to measure

surface temperature (ocean and land), soil moisture, the extent

and thickness of sea and land ice, snow depth. For certain

measurements, especially ocean temperature, the data from

microwave radiometers are generally complemented by data from

thermal IR sensors (TIR).

Microwave radiometers operate by sensing the "tail" of the

emission spectrum radiated in the microwave range from the "gray"

body representing the surface.

47
A major advantage of microwave radiometry is its ability to

"penetrate" clouds--becau.se the microwave absorption of water

vapor, as well as of other atmospheric constituents, is

relatively small, especially at the longer wavelength below

approximately 3 centimeters.

A disadvantage of microwave radiometers is that their

accuracy is affected by: a) the apparent emissivity of the

surface, which varies significantly as a function of surface

objects' dielectric constant (for land sensing) and as a function

of sea state, winds, foam cover (for ocean sensing), b) the

radiation scattered from the atmosphere; c) the residual

absorption by the atmosphere and clouds, especially at the higher

frequencies. As such, there is no "best band" for microwave

radiometry. Advanced systems seeking good accuracies employ

several, strategically located microwave bands, typically lying

in the range between approximately 24 centimeters and 6

millimeters (some advanced experiments operate at frequencies as

high as 180 GHZ). Each of these bands suffers from its own

limitations which induce inaccuracies; the idea is to combine the

"limitations" in such as way that they serve to "calibrate" each

other.

For example, a highly variable influence on microwave

sensing of ocean surface temperature is sea state. If the ocean

surface is smooth, it acts as a reflecting mirror and thus

appears relatively "cool". If the surface is rough, it acts as a

diffused emitter and thus will appear warmer. In the latter

case, an error of measurement will result. Experimental data

show that significant levels of dispersion, thus of apparent

"warming", begin to occur when the wave height approaches one

quarter wavelength of the microwave radiation. Thus sea surfaces

which appear smooth, thus cooler, at one wavelength can look

rough and thus "warmer" at another. Well designed microwave

radiometers tend to reduce these errors by utilizing the slope

functions occurring at different microwave bands—for example,

48
6.6, 10.7, 18, 21, 37 GHZ. To achieve high accuracies, the

residual bias error can be corrected from knowledge of sea state,

or actual sea surface temperature, from an in-situ sensor.

State-of-the-art Microwave Radiometers operating in a single

band experience errors in ocean surface temperature of order 10°

to 14°K. Multi-band microwave radiometers typically can reduce

this error to the order of 1° to 2°K.

5.6.2 Illustration: Calibration of Thermal Infrared

Radiometers by In-Situ Data

This category of instrumentation is used primarily for

measuring the temperature of the ocean and land surfaces.

Thermal Infrared (TIR) Radiometry is in principle more

accurate than microwave radioraetry because it operates at or near

the peak of the black or gray body radiation of the earth's

surface. Another advantage is that by virtue of the much smaller

wavelength, in contrast with microwaves, TIR can provide much

higher surface resolutions. TIR measurements are much less

sensitive to sea state than measurements from passive microwave

radiometry. Errors are induced by atmospheric absorption,

principally water vapor. A major impediment is that TIR

radiation is opaque to clouds, thus a TIR sensor will not operate

over cloud cover. Statistical data indicate that, on the

average, world-wide, one might expect approximately 50% cloud

cover. For this reason, TIR sensors operate in conjunction with

microwave radiometers: where the TIR is "blind", the microwave

sensor will provide data, albeit at somewhat lower accuracy.

5.6.3 Desirability of Calibration

Quite apart from sensor drift, we see that environmental

conditions induce inaccuracies. Strategically located, accurate

49
In-situ sensors can provide data to "calibrate out" the errors.

It is clear that, in non-real time scientific applications, these

"calibration" data need not be supplied very rapidly: they

should be available to the scientific investigator as a data set,

adjunct to the main sensor data set, when the investigator is

performing his analyses.

5.6.4 Assessment of the EOS User Requirements for In-Situ Data

The assessment of the requirements for in-situ measurements

was accomplished in two ways: a) by discussions with

knowledgeable scientist/users; and b) by computation based on

accuracies desired and achievable from remote sensing and scale

factors of the phenomena involded.

Discussions with involved scientists indicate certain

approximate requirements for in-situ sensors for various elements

of the EOS program. The requirements are intended to be for

world-wide coverage.

The summary results are shown in Table 5-14. The following

summarizes the philosphy underlying the values shown in the

table.

From an EOS standpoint, the most important measurements are

those conducive to improve our understanding of the hydrologic

cycle--i.e., how water moves around the world.

From the scientific standpoint, a major reason for seeking

this knowledge is to assess whether man-made activities (e.g.,

generation of C02) will affect the climate and the sea level.

For example, if we knew that the increasing content of

atmospheric C02 would eventually raise the sea-level with

deleterious consequences for coastal areas and ports, we could

begin planning modifications of our energy generation pattern in

such directions as to ward off major deleterious effects. For

50
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instance, we could use more nuclear fission energy in place of

coal; accelerate R&D in nuclear fusion; minimize the processes of

coal gasification; accelerate R&D in electric automotive

transportation. The hydrologic cycle, moreover, is key to

agricultural production, the availability of water resources,

etc. The principal measurements of interest to track the

hydrologic cycle are:

• Soil moisture—key to estimating evaporation from water

surfaces and evapotranspiration (ET). These estimates

are in turn important to determine how much moisture

will be evaporated into the atmosphere, hence how much

precipitation to expect.

• Water vapor content of the atmosphere. Important to

compute the evaporation from the oceans.

• Measurement of precipitation. On land, this is

accomplished by rain gage networks, on the oceans, what

needs to be perfected are good unattended, oceanic,

precipitation gages.

• Determination and measurement of soil cover, principally

to assess runoff from snow and ice. With current and

foreseeable microwave techniques, this measurement is

qualitative and needs to be integrated with empirical,

in-situ measurements.

• Sea surface temperature (SST). Somewhat secondary to

the hydrologic cycle, it is key to climate measurements.

• Ice measurements. The degree of net ice accumulation or

disappearance is an indicator of future sea level rise

and fall, and an important parameter in climate

assessment.

52
Other important scientific measurements are included in

Table 5-14.

It is clear from Table 5-14 that many of the required

measurements can be accomplished by using multiple sensors

located in the same in-situ platform. Table 5-15 coalesces these

multiple requirements into non-redundant requirements, i.e. the

number of individual in-situ platforms needed to accomplish the

EOS program.

5.7 Integration of User Constituency

We have thus far assessed separately and independently the

expected future data traffic for ARGOS and/or ADCLS, for the

following categories of users: Conventional, Latent, Peak, and

EOS users.

We now proceed to aggregate the traffic requirements of the

users, employing the following criteria:

• Our pessimistic approach assumes that 1) the GOES DCS

system will be upgraded, thus none of the forecasted

"latent" GOES DCS users will seek ARGOS data relay

services; 2) in view of the projected high costs of

space station, the EOS funding will not include as many

in-situ platforms as the EOS users desire--thus we have

reduced the EOS requirements by a factor of two; 3) the

lower, service ARGOS forecast is correct, rather than

our higher forecast based upon discussions with the

U.S. user community, and extrapolation of the

community's traffic demand.

• Our optimistic approach assumes that 1) an improved

GOES DCS will not be implemented by year 2000 (but the

ground segment will be upgraded) , thus the traffic
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54
spillover above the saturation limit of 10,000 users

will be captured by ARGOS and/or ADCLS; 2) that such a

spillover will occur for U.S users only; and 3) that

all users will deploy their maximum forecasted number

of platforms (equal to 0.8 x number of subscribers).

Tables 5-16 and 5-17 synthesize the two approaches. From

these tables, the following conclusions can be drawn:

• With reference to Table 5-3 and Figure 5-2, that show

that there are 29 equivalent footprints, the average

user constituency, and corresponding average erlang

traffic demand per footprint are:

1990 1995 2000

Pessimistic Case - per footprint

Average Number of Platforms 154 251 314

Average Erlangs 1.6 2 2.5

Optimistic Case - per footprint

Average Number of Platforms 388 840 960

Average Erlangs 2.6 4.5 4.9

Mean Case (average between 271 545 637

optimistic and pessimistic) 2.1 3.25 3.7

Our analysis and discussions with users counsel the

adoption of the Mean Case for our "best" forecast. This

is because: 1) the "optimistic" assumption that NOAA

will not upgrade its GOES DCS spaceborne data relay

segment by year 1995 or so is somewhat unrealistic; 2)

the "optimistic" assumption that the EOS users will be

55
TABUE 5-16

INTEGRATED USER FORECAST - PESSIMISTIC APPROACH (a)

User Category

Conventional

(Service ARGOS forecast)

Latent

Peak

EOS

TOTAL

Number of Platforms-Total Krlangs

1985 1987 1990 1995 2000

602-4.6 784-6.0 1,040-7.9 1.920-14.7 3,360-25.7

3,440-37.6 2,800-30.8 3,200-35.2

2,560-12 2,560-12

602-4.6 784-6.0 4,480-45.5 7,280-57.5 9,120-72.9

Assumes that 80% of the subscribers are users, i.e., are active at any one time.

56
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57
granted all their wishes for in-situ data also appears

somewhat extreme; 3) the full realization of the

"optimistic" forecast implies a growth by a factor of 40

in the number of platforms in the decade 1985 to 1995.

This is equivalent to a yearly compound growth rate of

45%, thus departing markedly from the best historical

growth rate (NDBC's moored buoys) of 25% per year--

factor of 9 in ten years).

• With reference to Figures 5-2 and 5-3, we readily see

that the world distribution of platforms is far from

uniform. Platforms are highly concentrated in certain

footprints, e.g. footprint Nos. 1, 10, 11, 12, 26, see

Table 5-3. These "dense" areas correspond to Europe and

its coastal areas, the U.S. and its coastal areas, the

Arctic region, and the South Atlantic. Our analysis

thus far shows no overwhelming reason why this pattern

of concentration ought to change drastically, especially

under the "optimistic" assumption of capture of the

latent GOES DCS users, that are essentially contained

within the U.S. (already a "dense" area). Under the

reasonable assumption that the concentration pattern

will remain approximately similar to the current user

pattern shown in Figures 5-2 and 5-3, Figure 5-9 shows

the distribution by footprint estimated for year 2000

for the mean case.

The preceding provides the traffic forecast. In the next

section, we address ARGOS' capability to meet the requirements of

the forecasted traffic.

58
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59
6.0 THE CAPABILITY OF ARGOS TO SERVE THE USER CONSTITUENCY

6.1 Approach

The ARGOS system provides two types of services; i) data

relay; it) position fixing.

In what follows, we treat first the capability of ARGOS to

meet the requirements of the user's demand for data (Sections 6-2

through 6-6); next we address ARGOS1 capability to deal with the

user's demand for position fixing (Section 6-7).

In common with any communications service, two principal

parameters affect the performance of the ARGOS data relay system:

• Loss of data from system "line blockage" (in radio

systems also known as "interference"): this occurs

when the demand for service exceeds the system's

capability.

• Delay in data delivery, above and beyond what the

subscribers are willing to tolerate. This can be

caused, in part by the effects of line blockage

(requests for free channels are not honored right away,

the messages must be repeated till the next satellite

pass, with consequent time delays); and, in part, by

insufficient data processing capability of the ground

segment.

As regards the line blockage, the factor that expresses the

level of the system's saturation is the "grade of service".

By this is meant the fraction of attempted messages that is

able to "get through" (in the first attempt). For example, a

grade of service of one in ten (1:10) means that, out of ten

attempted calls, one will not get through in the first attempt.

Repeated messages will eventually "get through" -- the "price" is

60
longer access time. An example of the grades of service

customary in telecommunications is offered by the U.S. telephone

service (including satellite relays), where the standard is 1:200

(one call out of 200 is blocked) ; the "threshold of discomfort"

(at which users begin to feel uneasy) is approximately 1:50; and

the "threshold of disservice" (at which complaints begin arriving

at the telephone company) lies between 1:20 and 1:10. In the

case of data transmission, some services "hold" the outgoing data

until a transmission channel becomes free. The corresponding

grade of service can be expressed as the average delay between

the transmitting user's forwarding the data and the receiving

user's obtaining them. In the case of U.S. radio paging systems,

for example, this delay is typically on the order of 10

minutes. The "hold" feature is not used in the current ARGOS

system.

The grade of service experienced by any multi-user

communication system is a function of: the number of available

channels; the traffic demand, conventionally expressed in

erlangs(a); the way in which the channels are made available to

the incoming message traffic(b); and the manner in which

"competing" messages are handled. In hardwire and radio cellular

systems, the first message finding a free channel is accepted,

subsequent messages are rejected until the first message is

completely delivered. In radio systems, this message exclusion

/ ~\ v ' The erlang unit is the ratio between the length of the

message or messages and the time available for their

transmission, both expressed in the same units. For

example, a message lasting one minute, transmitted during

one available hour, represents 1/60th of an erlang (16.6

millierlangs).

^ ' If the interconnection is such that any one of the available'

channels can be made available, on a "first come first

served" basis, to any one of the incoming messages, the

system is known as "trunked". This is the case with ARGOS.

61
policy is "softer", because "hard" switches are absent. In most

well-designed radio receivers, once a signal is acquired and

locked on, interference by subsequent competing signals is

reduced—typically from 6 to 12 db. The reason is that the

signal acquisition process generally involves uncertainty as to

the signal's exact characteristics—thus a certain bandwidth is

needed, encompassing the region of uncertainty. Upon reception

and lock, the uncertainty is reduced, thus a narrower bandwidth

is sufficient. If competing signals are not overpowering, this

results in a degree of immunity against interference. In the

ARGOS system, all platform transmitters emit approximately the

same peak power. As shown in Figure 6-1 , the relative signal

strengths arriving at the satellite from platforms lying along

the footprint's diameter will differ in power by no more than

10db. We can therefore assume that the ARGOS receiver is (or can

be made) to a significant extent "immune" to interference by

signals competing with the "first come, first served" signal. We

note that the assumption of complete immunity is "optimistic",

meaning that the resulting ARGOS performance estimates are the

best achievable or upper limits dictated by the laws of nature.

We note that the "ideal" case can be closely approximated in a

"perfect" polling system, where each platform is queried

separately by the satellite, and transmits only in response to

the query.

We will later compare this "optimistic", ideal performance

with the assumption of "zero immunity", i.e. where any signal

overlap causes interference, hence loss of both signals; and with

the assumption of "partial immunity", i.e., where interference is

reduced by realistic factors.

6.2 The Total Immunity (Optimistic) Assumption

From the aforegoing, the "best possible" or "ideal" or

"limiting" grade of service for ARGOS can be expressed by means

of the Erlang B formula:

62
Normalized

Power, db

0

-10

2500

Edge

2000 1500 I 1000 500

Midway

Kilometers Along Radius of Major Diameter

0

Center

Figure 6-1. Power Level Along Radius of Major

Diameter of ARGOS Footprint

63
n

E / n!

where:

P^j = probability of line blockage (on first attempt)

E = traffic demand, Erlangs

n = number of trunked channels

The Erlang B formula applies to the case in which a given

request for access to a channel is "cleared" (not held) should

the channel turn out to be unavailable (if it reappears later, it

is considered as a "new" call) . This is the case with ARGOS

under the postulated assumption of no interference with the first

accepted signal by subsequent messages.

Strictly speaking, 6-1 is valid for the case of a large

number of message sources (theoretically infinite). In practice,

the departures are quite small down to ten or so sources. Since,

moreover, we are interested in the ARGOS performance near

saturation, i.e., in the presence of numerous sources, we can

disregard the cases of very few sources.

In the ARGOS system, the number of channels, n, equals 4 per

satellite ^a'. There are 8 channels for both satellites:

however, the 8 channels are not trunked, because they are not

available simultaneously within the same footprint. We treat the

case of a single 4-channel system first.

The single 401 MHz channel, approximately 24 kHz wide, is

actually "split" into 4 "pseudochannels" (data recovery

units) by ARGOS1 spaceborne receiver. These are available

on a first come, first serve basis. To the user, this

arrangement looks like 4 trunked channels.

64'
Figure 6-2 shows the grade of service versus traffic demand

for a "single" attempt at communicating. The significance of

"single" attempt can be visualized in two ways: 1) imagining

that each transmitter signals but once during the satellite's

passage; or, equivalently , 2) as the probability of any one

transmitter finding a free channel on the first try.

It can be seen, for example, that if we wished to maintain

the signal loss at a low level, say 2% (signal throughput 98%),

no more than 1 Erlang ought to be processed by the system (on a

one-query basis). We note in passing that the one-query case is

of interest for very sophisticated platforms transmitting very

long messages, for example some of the oceanic platforms

currently being planned by Woods Hole.

Conventional platforms repeat their message during the ARGOS

satellite's passage, with typical repetition rates of the order

of 50 to 60 seconds.

Each attempt at transmission represents an "independent

experiment". Thus if the traffic statistics remain the same

between attempts, the probability of any one transmitter "getting

through" in k attempts is :

P

k " 1 -

 Pb

 (6-2)

and

P

bk= ' - <1 -

P b> * Pb (6'3)

where :

= probability of successful message conveyance in k

repeated attempts

= probability of channel blockage (one-shot)

= number of attempts

65
Probabllty of

Blockage on

First Attempt

too

90

80

70

60

50

40

30

20

10

0

I I I I I

3 4 5 678 9 10

Traffic Demand. Erlangs

4 Channels - Erlang B Policy

Probability of

Throughput on

First Attempt

0

10

20

30

40

50

60

70

80

90

100

20

Figur e 6-2, Channel Blockage Versus Traffic

Demand - First Attempt

Total Immunity, Optimistic Assumption

66
P^k = cumulative probability of channel blockage in k

attempts

The diameter of the ARGOS footprint at 5" elevation, is

5,000 Km; the satellite's orbital speed at 800 Km altitude is

such that on the average a footprint passage lasts approximately

600 seconds. We use the term "on the average" to mean that,

although platforms lying towards the edges of the footprint will

dwell less time within the ARGOS field of view in that particular

pass, they will experience full or close to full dwell time

during a subsequent pass.

The repetition rate of the drifter platform is of order 50

to 60 seconds. Hence, the maximum number of attempts possible

during a satellite overpass is 10 to 12, thus k equals 10 to 12.

For fixed land platforms, that have average repetition rates,

of the order of 150 seconds, k = 4.

Inverting 6-3, the required one-attempt probability of

channel blockage turns out to be:

P

b

 = (P

bky v«-*y

Knowing the number of attempts at communicating, k, and the

"grade of service" (in terms of allowable data loss rate) desired

by the user, Pbk» expression 6-4 in conjunction with expression

6-1 allows computing the ARGOS saturation level, i.e., the value

of Pb at which the traffic demand will begin to exceed the

system's capability to handle it (loss of data becomes

excessive). Discussions with users indicate that an acceptable

value of sensor and/or positional data loss from drifters and

fixed platforms lies between 1% and 10% during any one pass.

This yields the figures shown in Table 6-1 , where we have

assumed, for an advanced ARGOS system, a degradation of 30% from

67.
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68
"perfect" operation: i.e., 8 and 3 attempts at communicating

instead of 11 and 4, for drifters and fixed buoys respectively.

The 30% degradation is based on current statistics of ARGOS

message losses (positional) published by the World Meteorological

Organization (WHO). These report that 24% of attempted position

locations are dropped due to inadequate satellite-platform

geometry; 13% are eliminated due to excessive short and mediumterm frequency deviation (if greater than 2.10"' or 4 Hz/minute

Q

over 10 minutes, or greater than 10~° over 0.1 seconds, the

computation aborts); and 58% are lost from other reasons due

mostly to deficiencies of the ground processing segment.

Thus, according to WHO, approximately only 21% of the

possible positional fixes per pass are achieved by the current

ARGOS system, representing a degradation of order 80%.

In our analysis, we assume that an improved ARGOS system

operating in conjunction with more stable platform transmitters

would obviate most of these- difficulties, except possibly those

connected with satellite-platform geometry. Hence our choice of

30% degradation.

Let us now compare the results derived above for the ideal

case of "complete immunity" with the results obtained by using

the standard assumption that any two signals, overlapping in time

and frequency, do interfere, with consequent loss of both.

6.3 The Zero Immunity (Pessimistic) Assumption

This "worst case" assumes that any two signals received by

ARGOS, that overlap in whole or in part, either in time or

frequency, interfere with each other and therefore are lost.

69
The expression for interference without any immunity is^a':

)N-i (6_5)

T F

where:

P^ = probability of mutual interference (on first attempt)

t = duration of signal transmission

T = time between successive transmissions

Af = bandwidth of the receiving channel

F = total available reception bandwidth

N = number of platforms transmitting within footprint

We note that, in the hypothesis that any interference means

loss of data, P^ = P^. In highly sophisticated systems (not in

ARGOS), some data can still be extracted despite mutual

interference. Hence, we prefer to keep the two notations P^ and

P|j separate: where P^ connotes the channel blockage in a system

operating in the Erlang B mode, P£ the mutual signal interference

in a system operating with a radio link.

Expression 6-5 assumes implicitly that all platforms

transmit identical message lengths and repetition frequencies.

If this is not the case, 6-5 needs to be corrected to reflect the

non-uniform transmission patterns. For values typical of the

ARGOS platforms, and under conditions of high traffic

(approaching saturation) that we are concerned with, the

differences are not great and can be neglected.

t

From (6-5), T is clearly the erlang traffic demand for

transmitting platforms, see Table 5-2 for representative

values. —p— is the inverse of the number of available channels

(4 in ARGOS). Thus for ARGOS, -~- = 0.25 .

See also James L. Coates, "The Nimbus F Random Access

Measurement System (RAMS)", IEEE Transactions on Geoscience

Electronics, Vol. GE-13, No. 1, January 1975.

70
Substituting these values, (6-5) becomes:

P^ 1 - (1 - E)N"

1 (6-6)

Where E is the traffic demand per platform in erlangs.

Let us illustrate by example, for a case of low erlang

demand. Say we had 10 platforms each requesting 17

millierlangs. Expression 6-6 yields:

P.^ = 1-(1-0.017)9 = 0.14

This means a 14% chance of interference on the first

attempt. On the other hand, expression 6-1 ("ideal system") with

n=4, E = 0.017 x 10 = 0.17 erlangs yields:

p =

b ni n n 24 n

I E/ n! E (0.17)

 n/ n!

o o

= 3 x 10" = 0.003%

As an example for a case of high erlang demand, say 300 platforms

each requesting 17 millierlangs (total of 5.1 erlangs), the two

expressions yield respectively:

For the zero immunity (worst) case: P^ = 0.99

For the full immunity (ideal) case: P^ = 0.4

The differences are significant. However, neither the ideal

(optimistic) nor the worst (pessimistic) case are correct in

practice. We next investigate the realistic case of partial

immunity.

71
6.4 The Partial Immunity (Realistic) Assumption

Discussions with service ARGOS personnel, and diligent

search of the literature, failed to reveal tests on other

experimental findings relative to the ARGOS system's degree of

immunity.

We thus analyzed a data set, supplied by Mr. Charles Cote of

GSFC, pertaining to a series of tests performed by Texas

Instruments, in 1976, on the TWIRLE/RAMS System. TWIRLE/RAMS is

a random-access data relay system, installed on the NUMBUS F

satellite, and functionally akin to ARGOS.

The test's objectives were to determine "quality of service"

of RAMS, i.e., the probability of throughput of messages issued

by in-situ platforms and relayed through RAMS, under a variety of

conditions. The test was performed by simulating messages

typical of those transmitted by drifters (balloons) lying within

the satellite's footprint, and by measuring the ratio of messages

successfully received to messages transmitted.

For reasons of cost and expediency, the test did not exactly

simulate truly random platform emissions. Nevertheless, the

results allow a good assessment of the "immunity" factor.

The TWERLE/RAMS system's specifications pertinent to our

purpose are shown in Table 6-2.

Three tests were performed:

• Dynamic range test #1. All platforms transmitted at

equal power (600 mw). Frequency separation between

platform emissions was reduced down to 500 Hz over a

total r.f. bandwidth of 29,500 Hz. The measured

probability of success was approximately 95%,

indicating that no significant mutual interference was

72
TABLE 6-2

TWERLE/RAMS SYSTEM SPECIFICATIONS

Nominal Carrier Frequency

Allowable Carrier Frequency Excusion

Doppler Bandwidth

Total RF Bandwidth

Platform Transmitted Power, Nominal

Platform Message Duration

Platform Transmit Rate

Millerlangs Per Platform

Message Data Rate, Input

Bit Duration

Modulation/Encoding

Acquisition Bandwidth

Tracking Bankwidth

Number of Channels

401.2 MHZ

_+ 5 kHz

+_ 9.5 kHZ

_+ 14.5 kHz

600 raW

1 Second

One Per Minute

16.7

100 bps

10 msec

_+ 60°PSK, Manchester

150 HZ

18.5 HZ

8

73
experienced. It would have been interesting if the

test had reduced the frequency separation further, at

least down to values commensurate with TWERLE's

reported acquisition bandwidth of 150 Hz.

Unfortunately, the structure of the test did not allow

this.

We conclude that the system operated effectively at least

down to 500 Hz frequency separation between signals. This is

equivalent to stating that the effective number of channels

equaled at least: 29,500 Hz (total r.f. bandwidth) * 1,000 Hz

(separation) ~ 30. -

• Dynamic range test #2. One group of platforms

transmitted at 600 mw, the other at 4.8 watts (9 db

higher). Frequency separation was varied. The

probability of success dropped to about 56% for

separations of 500 Hz, but returned to normal at

separations of 700 Hz.

We conclude that, in the presence of 9 db interference-tosignal ratios, the effective number of channels equaled at least

29,500 *1,400 - 21 .

Within the limitation of the data, we can infer an

additional conclusion. If we can consider the higher-power

signal as the interferer, and if the system is linear, the

frequency separation at equal power ought to be reduced by the

signal voltage ratio corresponding to 9 db, namely 2.8 times,

yielding an equivalent separation of 700 Hz * 2.8 ~ 250 Hz.

At this separation, presumably, no significant interference would

occur if all the signals were emitted with the same power level.

• The random access test simulated 8 platforms, each

emitting 600 mw, quasi-randomly spaced in time, and

with varying frequency separations. The probability of

74
success did not reduce significantly down to mutual

separations of 500 Hz.

Similarly to Dynamic Test #1, we conclude that the number of

effective equivalent channels was at least 30.

Despite the fact that the tests did not "push" the frequency

separation below 500 Hz -- thus we are constrained to deduce

performances "at least as good as" -- these tests support

conclusions that can be derived theoretically from information

theory: .

• In a well designed random access system, the number of

effective equivalent acquisition channels ought to

equal at least the ratio of total bandwidth to

acquisition bandwidth. For TWIRLE/RAMS this ought to

approach 29,500 * 150 ~ 200. We note in passing

that the full advantage of the "equivalent number of

channels" is realized only if the receiving system

contains a sufficiently high number of Data Recovery

Units (DRU's). Contrarywise, some of the advantage is

"wasted".

• If the acquisition bandwidth operates over a fraction

of the signal's duration, and is subsequently replaced

by a narrower tracking bandwidth, the number of

effective equivalent system channels lies in between

the ratio of total bandwidth-to-acquisition bandwidth

and total bandwidth-to-tracking bandwidth.

Let us apply these results to a "well designed" ARGOS — not

necessarily as ARGOS is now, but as an improved version could be.

Repeating expression 6-5:

75
P. „ 1 - (1- _2l_ 2Af }N-1 , (6_7)

we see that the critical element is Af.

For an "improved" ARGOS, we can re-write 6-7 by introducing

9 A f

a (fractional) multiplier of — ^ — , h, that expresses the

number of effective channels. We can re-write 6-7 as follows:

For ARGOS, the bit rate is 400 bps, thus the tracking

bandwidth is of the order of 2 * 800 Hz = 1,600 Hz. The

corresponding maximum number of equivalent channels could then

equal the available sytem bandwidth (doppler excursion puls

inherent bandwidth), ie.e, 24 kHz, divided by the acquisition

bandwidth (1,600 Hz) or 24,000 * 1,600 « 15. Thus h in

expression 6-8 would become

 2 x j.>600

 — = — 24*000 - * °'13'

yielding:

= 1-O-0.26 E)

N-1 . (6-9)

We note that under conditions of equal received powers at

the. satellite, and improved schemes of modulation, h could be

lower. However, since signal strengths vary across the footprint

by about 10 db, see Figure 6-1, and for the moment we are limited

to PSK modulation, the chosen value h = 0.13 constitutes a

reasonable compromise—at least until such time as better

experimental data become available.

The allowable one-shot probabilities of interference as a

function of the data loss tolerable by the user are shown in

Table 6-1. They are recapitulated in Table 6-3 for the

"degraded" case of 8 attempts per footprint for drifters, 3

attempts for fixed platforms.

76,
TABLE 6-3

ALLOWABLE MAXIMUM ONE-SHOT PROBABILITY OF INTERFERENCE

PARTIAL IMMUNITY, REALISTIC ASSUMPTION

Allowable data loss per pass- Maximum Allowable One-Shot

Type of Platform Probability of Interference

1% - Drifter 0.56

1% - Fixed 0.21

5% - Drifter 0.68

5% - Fixed 0.37

10% - Drifter 0.74

10% - Fixed 0.46

Let us now apply 6-9 to the year 2000 platform populations

shown in Figure 5-9.

As an example, the densest footprint, over Europe, has 3,240

platforms active at any one time, generating a total traffic of

18.78 erlangs, equivalent to 5.7 raE per average platform.

Application of 6-9 yields:

Pi = 1-(1-0.26 x 0.0057)3239 = 0.99

By comparing with the maximum allowable values, Table 6-3,

this footprint will clearly saturate because the data loss will

exceed the maximum desired by the users. The probability of data

loss in 8 attempts will be (0.99)8 = 0.92. Thus on the average,

most of the data will be lost.

The threshold of saturation will depend on the allowable

data loss. It is- computed as follows.

Average erlangs per platform (from above), E = 0.0057

77
Allowable data loss per pass: 5%

This corresponds to values of P. = 0.68 for drifters,

P. = 0.37 for fixed platforms (from Table 6-3).

One-shot probability of interference (from 6-9):

P = 1-(1-0.26 x 0.0057)N"

1

 = 1-(0.9985)N"

1

Solving for N, the maximum allowable number of data only

platforms per footprint per pass is: for drifter platforms, ~ 770

and for fixed platforms ~ 310. For a 50-50 mix of these two

types of platforms, the saturating number of platforms is ~ 540.

6.5 The Case of Two ARGOS Satellites

The above conclusions have been derived for the case of one

ARGOS satellite. What happens if there are two? All indications

are that most users will tolerate the additional time needed for

double coverage (as long as the loss of data is contained to

within 5%.

Thus the net effect of the second ARGOS satellite is to

double the number of attempted collections: from 8 to 16

(degraded hypothesis) for drifters, from 3 to 6 for fixed

platforms -- at the cost of somewhat longer time delays. The

corresponding maximum allowable one-shot probabilities of

interference become as shown in Table 6-4.

TABLE 6-4

MAXIMUM ALLOWABLE ONE-SHOT PROBABILITY OF INTERFERENCE

AS A FUNCTION OF THE ALLOWABLE DATA LOSS--TWO SATELLITES

Allowable Data

Loss Per Double Pass

1% - Drifter

1% - Fixed Platform

5% - Drifter

5% - Fixed Platform

10% - Drifter

10% - Fixed Platform

Maximum Allowable One-Shot

Probability of Interference

0.74

0.46

0.83

0.61

0.87

0.68

78
The number of platforms that will saturate ARGOS, assuming an

allowable data loss of 10% per two passes, becomes 276. We see

from Figure 5-9 that even with two satellites, most footprints

will saturate.

We note that the saturation numbers of platforms computed

above are close to the number that Service ARGOS has announced

for the improved ARGOS, namely 200.

6.6 The Limiting Performance

It is of interest to compare our results thus far with the

performance of an ideal system obeying the Erlang B formulation. This represents the "ultimate" performance achievable,

i.e. the "limit" imposed by laws of nature.

We have seen that, in a system designed to fully exploit the

acquisition bandwidth (24 kHz), the possible number of equivalent

channels can theoretically go up to 30. We will however assume,

in line with the announced Service Argos policy for an improved

ARGOS II, 8 channels, and a double satellite pass. Thus the oneshot interference probabilities of Table 6-4 apply. Table 6-5

summarizes the computations.

TABLE 6-5

MAXIMUM ERLANG TRAFFIC DEMAND PER FOOTPRINT THAT CAN BE HANDLED

BY 2 ARGOS II SATELLITES HAVING 8 CHANNELS EACH

IDEAL CASE - ERLANG B POLICY

Allowable Data Maximum Allowable Traffic

Loss Per Double Pass . Demand, Erlangs

1% - Drifter 30

1% - Fixed Platform 18

5% - Drifter 35

5% - Fixed Platform 18

10% - Drifter 40

10% - Fixed Platform 23

79
Comparison with Figure 5-9 shows that an "ultimate" system

configured in this fashion could handle all the year-2000 data

traffic without saturating.

The preceding treatment applies to data. We proceed next to

investigate the situation as regards the successful achievement

of positional fixes.

6.7 The Case of the Position Fix for Drifters

In theory, the ARGOS doppler system could provide a position

fix for drifters (buoys or balloons) with a minimum of three

transmissions. In practice, five transmissions, occurring during

one pass, have been shown to be needed with the present system.

The need to achieve 5 successes per pass poses a more stringent

requirement on the system than is the case for message relays

only, that require only one successful attempt per pass.

If the transmission parameters are statistically

independent, the probability of loss of fix in s transmission

occurring during the same pass is:

R .

P. = 1-£ (I) d-Pj)1 (P,)

 L (6-10)

i=s ^ '

where:

Pg = probability of "line blockage" (non-acquisition)

in s attempts out of R possible attempts

P^ = one-shot probability of line blockage

Since R=8 (degraded case, see Table 6-1), s = 5, and

R R!

= —T-.—/n_- s \ »

 we can

 re-write 6-10 as:

Q

Pe = 1- z —i{ (lii\i— d-P^1 P^'1 (6-11)

80
Figure 6-3 shows the relationship between Pe and P^.

Figure 6-4 compares the probabilities of loss of data with

the chance of loss of fixes. We note that the latter is

considerably higher than the former: for example a 1% loss of

data corresponds to a 76% loss of fixes.

Our queries of the users did not show as great an urgency to

obtain successful fixes as is the case for successfully obtaining

data. A reasonable estimate for the user's tolerance is offered

by the WHO statistics quoted in Section 6.2: the "fix" data loss

is currently of the order of 80% per pass (of course, this is

remedied in successive passes). The user's attitude appears

reasonable when looking at the physics of the phenomena.

Currently, see Table 5-1, practically all drifters are buoys.

Since ocean currents are relatively slow (order of 0.25 to 1

knot), even as long as a 24-hour interval in position fixing

entails only a 6 to 24 nautical mile distance, not very large

compared to the geometric scale of ocean phenomena. We

anticipate that the case may be quite different if a significant

number of balloon users were to become ARGOS subscribers in the

future: this is because the drift velocities in the atmosphere

range from 10 to 100 times those of oceanic phenomena. A

prospective estimate of the number of balloons is given in Table

5-15.

We note that the "improved system" promised by Service ARGOS

for 1987 ought to reduce a portion of the losses in position

fixes.

Nevertheless, even assuming "perfect" ARGOS performance, the

computations—see Figures 6-3 and 6-4--show that ARGOS will

saturate much sooner in terms of position fixes than in terms of

data throughput.

81
Probability of

Loss of Fix , Percent (Pe)

100-1

90-

Partial immunity (realistic)

assumption. One satellite pass

8 possible attempts per pass.

5 successful attempts needed

10 20 30 40 50 60 70 80 90 100

Probability of One-Shot Interference, Percent (Pj)

Figure 6- 3. Probability of Loss of Fix Versus Probability

of One-Shot Interference During One Satellite

Pass

82
Probability of

loss of fix,

percent

100 -,

80 -

60 -

40 -

20 -

Partial immunity (realistic)

assumption. One satellite pass.

8 possible attempts per pass.

5 successful attempts needed

for fix.

Maximum

allowable

data loss

I

10

Probability of Data Loss, Percent

Figure 6-4. Probability of Loss of

Probability of Loss of

Drifters

Fix Versus

Data for

83
The question is: what would happen if the position fix were

to require 1 message instead of 5? In this case, the computation

of the saturation levels would be the same as that already

developed for data, see Table 6-3, from which we see that a 10%

loss of data (90% success) is achievable even if the one-shot

probability of interference is 74%, or quite highwith respect to

the 0.23 approximate probability needed with five messages per

fix, see Figure 6-3.

The maximum (saturating) number of drifters (requiring

position fix primarily, plus a minimum of data) per footprint can

be computed as follows:

Average millierlangs per platform, from Table 5-2 = 6.5

Required one-shot probability of interference, PI» f°r 10%

(0.1) loss in fixes, from Figure 6-3 = 23% (0.23).

The relationship between P^ and the number of transmitters

within a footprint, N, from 6-9 is:

Pt = 1-O-0.26 x 6.5 x 10~3)

 N~1

 =

= 1- (0.9983)N~

1

But, from Figure 6-3, PI equals 0.23.

Solving for N, we obtain N = 153.

Compare this with the "saturation level" of ~ 540 data platforms

per footpring computed at the end of Section 6.4. Compare

further with Figure 5-3 showing the number of platforms per

footprint in year 2000, and with Table 5-1 that indicates that

position locations represent 66% of ARGOS data requirements..

Assuming this ratio to remain roughly constant, we see that

saturation of fixes will be far more severe in the future than

that of data messages.
It is clearly the position fixing function that dominates

the saturation scenario.

In the next section, we investigate remedial measures to

alleviate and obviate ARGOS saturation.

85
7.0 ADCLS REQUIREMENTS

7.1 Limitations of ARGOS and Options for Improvement

In the preceding section we have seen that: 1) the key

problem with the ARGOS system is the fact that it will saturate

by year 1995-2000; meaning that the loss of data will exceed the

level that users find acceptable (between 5 and 10%). Other than

this factor, our extensive query of the users indicates that they

appear pleased with the ARGOS performance-- except for the desire

for faster data turnaround, that presumably will be met when

service ARGOS will have transferred its Central Station to

Suitland circa 1987; 2) particularly severe is the saturation of

the position fixes; 3) an ideal system operating in accordance

with the Erlang B policy, having eight channels and 24 kHz

bandwidth, could meet the requirements of the year 2000 data

traffic; 4) the current operational ARGOS system, even if it were

to be endowed with a strong degree of immunity commensurate with

current radio communication technology, will saturate by year

2000. This holds true even for the proposed "improved ARGOS"

featuring eight channels (meaning 8 DRU's, Data Recovery Units).

Clearly, the system needs to be improved in order to meet

the requirements of the traffic estimated to be present by the

end of this century. We will hereinafter designate such an

improved system as ADCLS.

In accordance with our methodology, let us now proceed to

set forth the requirements of an ADCLS capable of meeting the

requirements of year 2000 traffic demand.

We observe firstly that Polar Platform, operating at.

approximately 800 km orbital altitude, can subtend a footprint

diameter approximately the same as is the case for ARGOS. We

will assume this to be the case.

86
Three categories of options are available to upgrade system

performance: i) options in the space domain ii) options in the

information extraction domain; iii) options in the frequency

domain.

7.2 Options in the Space Domain.

The principal are:

1) Restrict the field of view (FOV) by providing higher

antenna gains

2) Provide space diversity reception

7.2.1 Restrict the Field of View

The effect of increasing antenna gains would be to reduce

the footprint area, thus the number of platforms within a

footprint, thus the receiver processing requirements. An

additional beneficial effect would be the possibility of lowering

the power transmitted by each platform. Countering these

advantages is the prolongation of the data collection interval.

Figure 7-1 shows the tradeoffs. It can be seen that, in view of

the users' desire for relatively rapid data turn around, this

option does not appear attractive-unless additional Polar

Platforms were to be deployed.

7.2.2 Provide Space Diversity Reception

This can be accomplished via a high-gain, relatively large

antenna aperture equipped with multiple feeds to provide several

distinct smaller footprints. The aggregate of the multiple,

footprints would provide the same larger footprint as the current

system. If a single receiver system having the current 24

kHz bandwidth were to service this type antenna, nothing much

87
Recurrence

Interval to

Sight the Same

Point, Days

1000 2000 3000 4000

Footprint Diameter, km

5000

(Current

ARGOS)

Figure 7-1 Averag e Recurrence Interval Versus

Footprint Diameter for Various Latitudes

88
would be gained. What is needed to exploit the space diversity

feature of a multi-beam system is a multiplicity of receivers.

The net result of such an arrangement would be, in practice, to

increase the "effective" bandwidth of the system by the number of

footprints divided by a "frequency reuse" factor -- at the cost

of a more complex antenna system and of multiple receivers. Two

"limit" cases are possible: i) frequency reuse factor

approaching 1; ii) "normal" frequency reuse factor.

The first case would require the generation of an antenna

pattern with very steep skirts, i.e., an oversized antenna

aperture. Calculations for a frequency reuse factor of 1, with

four beams, equivalent to a ~ 100 kHz bandwidth, yield an

approximate antenna aperture diameter of the order of 2.5 meters.

The second case would entail an antenna diameter of order 1

meter, and a frequency reuse factor comprised between 5 and 7.

As an example, if the antenna footprint were to subtend a

diameter of 1,000 kilometers at the earth's surface, instead of

the normal ARGOS footprint diameter of 5,000 kilometers, ~25

effective beams could be generated. With a frequency reuse

factor of ~ 6, this would be equivalent to approximately

quadrupling the effective receiver bandwidth (reducing the

bandwidth per footprint by a factor of 6, and maintaining the

overall bandwidth at ~ 24 kHz). Of course, the ADCLS downlink

bandwidth would have to be approximately quadrupled in this case.

• The advantages of this solution would be: less platforms in

a single FOV; lower platform transmitter power possible;

maintenance of the current 24 kHz bandwidth; maintenance of the

same platform transmitter configuration, hence the system would

be "transparent" to the users. The disadvantages are that the

design of the onboard receivers and data handling equipment would

become considerably more complex than is the case with the

current ARGOS. Moreover, the antenna system would become quite

complex and costly.

7.3 Options in the Information Extraction Domain

Maintaining the current wide-coverage antenna pattern, the

89
principal options are:

1) enhance the system's immunity by narrowing the

acquisition and tracking bandwidth

2) modify the transmission rate

3) exploit the phase information contained in the messages

7.3.1 Narrow the Acquisition and Tracking Bandwidth

The net effect would be to increase the system's immunity to

interference. In the ARGOS receiver, the signal is acquired

during the 160 msec duration of unmodulated carrier. In theory,

2

the bandwidth could thus be of the order of —n ,, = 12.5 Hz.

U. I b

Tracking is effected on the sequence of 2.5 msec, message bits.

Use of Minimum Shift Keying (MSK) could in theory reduce the

required tracking bandwidth to about 800 HZ (+_ 400 Hz), from the

1,600 Hz bandwidth, corresponding to PSK, assumed in expression

6-9.

The use of MSK and the actual acquisition bandwidth on the

unmodulated carrier need to be supported and verified by actual

test data.

A further potential improvement could be effected by

shortening the message length, in two ways:

1) reducing the length of the CW portion of the message.

Utilizing Chirp-Z techniques for rapid detection of

transmissions, this could be reduced to about 20

milliseconds 'a'.

C.P. Ashcraft and J. Marini, "A Combined Data Collection and

Search and Rescue Satellite Package", Report X-945-81-17,

GSFC, June 1981.

90
2) eliminating the "sensor data" portion of the message for

those platforms that require only position fix—the

"dumb drifters".

Sub-Option 1), applicable to all platforms, would reduce the

total message length by about 140 msec, resulting in total

message lengths of 220 to 780 msec (instead of the current 360 to

920 msec)--amounting to an average reduction of the order of 20%.

Sub-Option 2), applicable only to "dumb" drifters, when combined

with Sub-Option 1, would further reduce drifter messages from the

current 360 msec to 140 msec, for a total reduction by a factor

of 0.6.

The net effect of Sub-Options 1) and 2) combined would be a

reduction in the traffic demand by about 30% (assuming that

drifters will continue to represent ~50% of the total platforms,

and "dumb"- drifters about half of that) .

While interesting, this improvement would not suffice to

meet the requirements of the year 2000 traffic demand. A

disadvantage would be that the platform transmitters would have

to be modified, entailing increased costs to users during the

transition phase between the two systems. This disadvantage

would dwindle in time, as current transmitters would phase out,

and would be gradually replaced by the new design. The

spaceborne receiver design would become somewhat more complex--

the additional cost would however not be too significant.

7.3.2 Modify the Transmission Rate

By this we mean either to increase or decrease the

repetition interval at which the messages are transmitted.

Longer intervals (at constant message length) have the net effect

91
of reducing the number of erlangs being transmitted. Thus the

one-shot probability of access would increase: however, the

number of repeated attempts possible during one satellite pass

would also decrease. Shorter intervals would have the opposite

effect. The question is which of these factors is dominant to

the end of conveying messages to users with the least loss of

data.

Combining equations 6-8 and 6-3, repeated here for

convenience:

(7-1)

P.k= Pk (7-2)

where:

P^ =* one-shot probability of interference

P^k =» probability of interference with k repeated attempts

E = erlang traffic per platform

h = ratio of acquisition bandwidth to system bandwidth

N ' = number of active platforms

We obtain:

Pi=k [1 - (1-2hE) ' ] (7-3)

Although this expression could be expanded in a double binomial

series, the result is not very tractable. An analytic tradeoff

turns out to be highly non-linear with E and k. However, since

92
we are interested only in conditions of high traffic demand, we

can use the practical approach of inserting actual values typical

of high density footprints: E = 5.7 millierlangs, h ~0.13 (from

expression 6-9), N ~3000.

This yields:

P.k= [1-0.012]k

If k=8 (repetition rate of 55 sec), P^ = 0.91. If now we were

to double the repetition interval, E would reduce to 2.85

millierlangs, k to 4.

The new value of P,-i, would be: ik

Pik- [1-0.11]4 = 0.63

Thus, halving the repetition interval would yield a 30% benefit.

If we reduced the transmission rate further, say 4 times:

Pik= [1-0.33] = 0.45

The benefit would only be 28%. Figure 7-2 shows the computed

values. Thus, for very dense footprints, reducing the data rate

up to an optimum, i.e., increasing the transmission interval,

would yield a benefit. As can be seen from Figure 7-2, this

benefit is however not overly significant. The probability of

interference flattens out if the transmission interval is

increased beyond 220 sees. This is true, because the increase in

transmission interval reduces the number of attempts as well as

the total Erlangs. These two factors work against each other in

a highly nonlinear fashion.

93
Probability of

Interference

per Pass,

Percent

100

00 -

80-

70 H

60-

50 -

40-

30-

20

N Number of Platforms

per Footprint

5000

i i i i i r r r

60 80 100 200 400

Transmission Interval. Seconds

Figure 7-2. Effect of Varying Platform Transmission

Interval - Partial Immunity (Realistic)

Assumption

94
7.3.3 Exploit Phase Information

This options entails use of multiple antennas (at least 2 to

provide a fix in one dimension, at least 3 to provide twodimensional fixes).

In practice, 4 antennas are generally used, because this

simplifies the system's operation.

The resulting instrument is known as an interferometer. Its

major advantage is that a position fix can be effected upon

receipt of a single message instead of five. Thus under

conditions approaching saturation, the quality of service

(probability of interference) is greatly reduced with respect to

the probability of receiving five successful messages per

satellite pass. Specifically, the probability of interference

for position fixes is reduced to the level corresponding to the

probability of interference for data messages. In other words, a

"fix message" becomes equivalent to a "data message"; the

preceding treatment becomes applicable to both fix and data

transmissions.

The other major advantage is the fact that the system can

operate with the current ARGOS transmitter at no additional

burden to the users.

Other advantages are: i) capability to provide accurate

fixes for fast-moving platforms, e.g., balloons; ii) capability

to resolve ambiguities induced by the doppler fixes; iii)

possibility of adapting the system to also serve the Search and

Rescue (S&R) function.

7.4 Options in the Frequency Domain

Maintaining the current wide-coverage antenna pattern, the

principal options in the frequency domain are:

95
1) Increase the system's transmission-reception bandwidth.

2) Employ a platform polling policy.

7.4.1 Increase the System's Bandwidth

The net consequence of this improvement -- if effected

without changing any other system parameter -- would be

equivalent to increasing the number of "pseudochannels" . A

sufficient number of DRU's must of course be made available.

With reference to expression 6-8, repeated here for convenience:

" (7-4)

where

P^ = probability of one-shot interference

E = traffic demand per platform, erlangs

N = number of active platforms

h = ratio of acquisition bandwidth to system bandwidth

we see that the effect of increasing the system bandwidth would

be to reduce the factor h. For example, if the system bandwidth

were quadrupled to 96 kHz (nominally 100 kHz), expression 7-4

would read :

Pi = 1-(1-0.065 E)

 N'1 (7-5)

Applying 7-5, by way of example, to the densest cell in year 2000

(3240 platforms, 5.7 raE per platform), we obtain:

PL = 1-(1-0.065 x 0.0057)

 3239

= 0.7

We note by comparing with Table 6-3 that this level of oneshot interference would essentially meet the user requirements

for data from drifters (8 contacts per pass), and would increase

the data loss above 10% for fixed platforms (3 contacts per

pass), even for the densest cell predicted for year 2000.

96
In fact, the maximum number of data-transmission platforms

(exclusive of the position fix function) per footprint per pass

computes out for drifters to be N = 2,850 at 5% data loss, 3370

at 10% data loss. For fixed platform at 10% data loss, N =

1,540.

In summary, increasing the bandwidth to ~ 100 kHz would not

preclude the ARGOS system from saturating in year 2000.

We note that use of the nominal 100 kHz bandwidth would

impose the requirement on the transmitter manufacturers of having

their center frequencies randomly "dispersed" over a band of 76

kHz (total band of 96 kHz less doppler excursion of 20 kHz).

This should not affect the cost to the users: it would probably

call for some management of the crystal oscillator frequencies on

the part of the community of manufacturers -- with some guidance

on the part of the user community and the operator of the system

-- so as not to result in biases caused by "bunched" frequencies.

7.4.2 Use of Platform Polling Policy

Platform Polling implies that the platforms would transmit

only upon being queried by the spacecraft. This would in effect

reduce the Erlang demand at the cost of increased complexity in

the platform's communications package, that now would require a

receiver in addition to a transmitter.

If the polling were random, the effect of this policy would

be tantamount to reducing the repetition rate—or, equivalently,

to increasing the transmission interval. In the limit, the

repetition rate can be reduced to once per satellite pass.

Perusal of Figure 7-2 shows that only a moderate improvement can.

be gained from this method to the effect of reducing

saturation. A truly random polling policy would require polling

all the platforms during the nominal spacecraft overpass time of

approximately 10 minutes. Assuming a query-response time of the

97
order of 1 second, only 600 platforms could be polled during an

overpass. To poll say 3,000 platforms would require at least 5

times the bandwidth (considering necessary overlaps). The

additional costs, especially the added costs to the users, do not

appear to warrant further consideration of this policy.

If the polling were systematic, and highly organized, then

in the limit the number of platforms that the satellite could

query in one pass would equal:

N =

 TP * n (?_6)

where:

T = time duration of overpass, ~ 600 sec.

t = time duration of one message, say 1 sec.

n = number of equivalent channels, say 4

N = number of platforms

With the above assumptions, N is approximately 2,400 for a

"perfect" systematic polling.

In practice, "perfect" systematic polling would not occur

unless the polling signals were separated in frequency

sufficiently to avoid doppler interference among signals. This

would require that the multiple channels be spaced beyond the

potential doppler interference from adjacent channels, thus

needing a substantial bandwidth (for 3,000 platforms, within a

footprint, approximately 125 kHz).

The implementation of such a scheme would require a

sophisticated form of on-board processing in the satellite. More

importantly, it would require that each platform be equipped with

a receiver capable of i) accepting the polling call; ii)

evaluating whether the call addresses the specific platform; and

iii) triggering the transmitter.

98
While such a receiver could be developed, its cost would add

a burden to the user. At an estimated sales price of $200

(projected to the 1995-2000 era), the forecasted 18,000 users in

year 2000 would collectively have to disburse $3.6 Million.

7.5 Synthesis of the ADCLS Requirements

7.5.1 Screening of Options

The preceding examines major options to overcome the ARGOS

system saturation that is expected to occur in the 1995-2000 era.

We will now summarize the advantages and disadvantages of

these options, discard those that are obviously of low value, and

compare those that promise the greatest cost/effectiveness.

Space Domain Options

1) Restrict the FOV by providing higher antenna gains.

Advantages: i) reduces footprint area, hence the number of

platforms per footprint, hence the saturation level, ii) allows

lowering the transmitter power level, hence increases platform

battery life.

Drawbacks: increases the data collection interval, see

Figure 7-1.

Tradeoff: Shelve—most users wish rapid data collection.

2) Provide space diversity reception via a high-gain antenna

equipped with multiple squint feeds.

Advantages: i) provides effective large footprint (5,000 km

diameter), hence rapid acquisition of data; ii) allows less

platforms in a single FOV, hence increases the saturation

99
threshold, iii) maintains the current ~24kHz bandwidth, hence

imposes no additional burden on users.

Drawbacks: i) greatly increases complexity and cost of

satellite antenna configuration, ii) requires multiple satellite

receivers and corresponding data processing circuitry; iii) might

still require a wider-band system, because of constraints on

frequency reuse.

Tradeoff: Retain for further analysis

Information Extraction Options

1 ) Narrow the acquisition and tracking bandwidth

Advantages: improves traffic handling capability (possibly

up to a factor of 2).

Drawbacks: i) increases complexity of satellite receiver,

ii) adds burden to users by requiring modification of current

transmitter design.

Tradeoff: Shelve as major tradeoff option. Retain as a

potential engineering improvement to finally selected option.

2) Modify the transmission rate (repetition interval)

Advantages: in situations approaching saturation (numerous

platforms per footprint), optimized transmission rates alleviate

erlang demand somewhat, hence reduce traffic congestion by a

factor of up to 100%.

Drawbacks: the optimum transmission rate is a function of

the platform density within each footprint, Figure 7-2.

Optimization of this parameter would require that the

transmission rate be made variable as a function of the

100
platform's geographic location, and with aforeknowledge of the

density of platforms sited in the same geographic area

(footprint). The relatively small advantage that can be derived

from this policy is not sufficient to compensate the increased

onus on the users of having to "tailor" their transmission rates,

and on the system managers of having to keep track of regional

platform densitites on a continual basis.

Tradeoff: Shelve, because the advantages are relatively

small, further they do not appear to compensate the disadvantages .

3) Exploit phase information (by using an interferometer)

Advantages: i) in situations approaching saturation,

interferometry, that utilizes one message instead of five for

position fixing, alleviates the congestion caused by traffic

demand for position fixing; ii) does not require modifications to

the platform transmitter, thus places no additional burden

accrues on the users; iii) can handle platforms that move more

rapidly than sea-going platforms, e.g., balloons; iv) can assist

in resolving ambiguities originating with the doppler fixes.

Drawbacks: i) requires more complex and costly satellite

on-board systems.

Tradeoff: Retain for further consideration.

Frequency Domain Options

1) Increase the System's Bandwidth

Advantages: i) alleviates the saturation problem—a,

bandwidth of ~ 100 kHz, plus additional options, for example,

interferometer, reduced transmission rate (increased interval

between transmissions) would meet the requirements of the year

101
2000 traffic; ii) does not require significant changes to the

platform transmitter, except for selection of center frequencies.

Disadvantages: requires that manufacturers of transmitters

and possibly system's operators coordinate the placement of the

transmitter's center frequencies to insure their uniform spread

across the frequency band.

Tradeoff: Retain.

2) Use of Platform Polling Policy

Advantages: i) Random polling would have little or no

advantage towards reducing saturation; ii) systematic polling

could circumvent saturation at least up to year 2000.

Disadvantages: i) Polling in general would require the

addition of a receiver and data analyzer to each platform, with

added expense to the user; ii) systematic polling would require a

prior knowledge of each platform's location—possible with fixed

platforms, costly for drifters; iii) a sophisticated form of onboard processing would be needed on the satellite.

Tradeoff: Retain for further comparative analysis.

7.5.2 Comparison of "Best" Options

From the preceding, the surviving options are:

a) Provision of space diversity via a high-gain, multiple

feed antenna

b) Reduction of erlang traffic demand for data by

systematic polling

102
c) Reduction of traffic demand for position fixing by use

of interferometer

d) Provision of more equivalent channels by increasing the

system's bandwidth (and providing the necessary number

of DRU's).

Let us now proceed to trade these remaining four options

among themselves.

The tradeoff criteria that we used, in descending order of

importance, are:

1) Principal criterion: minimum impact on platform-related

costs to the users.

2) Second-echelon criterion: minimum impact on the ground

segment, specifically as regards: a) cost of processing (because

it indirectly reflects on user tariffs); b) timeliness of

delivery (because it affects the "quality of service" expected by

the users).

3) Third-echelon criterion: minimum impact on the cost of

the space segment (because it may affect the decision to proceed

on the part of NASA/NOAA management).

The major elements entering the tradeoff are recapitulated

following.

Option a. Space Diversity

We have seen in Section 7.2.2 that there are two possible

suboptions: 1) with frequency reuse factor approaching 1; 2)

with a "normal" or "conventional" frequency reuse factor.

103
Suboption 1 would require antenna patterns with very steep

skirts, e.g., 4 oversized antenna apertures of order 2.5 meters

diameter (to achieve say an equivalent 100 kHz bandwidth). If we

used suboption 2, in order to achieve a factor of 4 in equivalent

bandwidth, with a frequency re-use factor of ~6, the 5000 km

diameter footprint ought to be subdivided into ~25 beams, each

beam subtending a footprint diameter of ~1,000 km. Thus the

antenna diameter, at 400 MHz, from an orbital altitude of ~800

Km, would be approximately 1 meter when looking towards nadir,

approximately 3.2 meters when looking towards the outermost edges

of the 5000 km footprint. The key drawback would be that, since

most of the frequency excursion is induced by the doppler

frequency shift, the system would require a wider radiofrequency

bandwidth, because of beam-shape constraints on frequency

reuse. Practical frequency-reuse schemes, such as are used in

the planning of land-mobile relay satellites, allow a maximum

frequency reuse factor of 4. Thus they work well when the

doppler excursion is small, e.g., from geosynchronous orbit:

from LEO, the doppler excursions occuring in adjacent FOV's will

overlap, thus needing a distinct separation of carrier

frequencies.

This option thus merges with Option d), wider bandwidth.

Option b. Systematic Polling

The key requirement would be the addition of a receiver and

data handling circuitry to each platform. Assuming an added cost

per platform of $200 for each of the forecasted 18,000 platforms

in year 2000, this would amount in the aggregate to a $3.6

Million burden to the users.

Moreover, choice of Option b would necessitate a

sophisticated on-board processing system on the spacecraft:

and/or a sophisticated ground-based system with an up-link to the

spacecraft. This is needed to maintain track of the stationary

104
platforms (from knowledge of their position and of the

satellite's epheraerides, to compute the corresponding doppler

shift). For drifting platforms, such a system would have to

essentially dead-reckon the platform's motion since the latest

fix--conceptually not a difficult chore, yet quite demanding of

computational resources in view of the large number of platforms

to be tracked. Furthermore, the uncertainty of any drifter's

position would induce uncertainties in the doppler frequency to

be addressed, thus broadening the system's bandwidth and negating

a portion of its advantages.

In view of these negative factors, the option of systematic

polling does not appear advantageous because: i) it is costly to

the users; ii) it is expensive for the ground segment; iii) it is

cumbersome and costly for the space segment.

Option c. Exploit phase information

The principal advantage of this option is to reduce the

number of messages needed to achieve fixes from 5 per satellite

pass to 1 , thus alleviating the saturation for position-fixing

platforms (oceanic buoy and atmospheric balloon drifters).

Theoretically, the number of fix messages would be reduced to

those applicable to data messages.

The disadvantage is the requirement for a phase-sensitive

device (interferometer). If, however, the interferometer's

design is kept simple, i.e. broad-coverage, avoiding complex

antenna structures, the cost will be moderate.

No impact would result to the users if the interferometer is

made to operate in conjunction with existing platform

tranmitters.

105
Option d. Increase the system's bandwidth

This option, coupled with Option c, appears to be the

"cleanest" and least expensive. The impact on the user's costs

would be minimal, because existing transmitters would work just

as well with a ~ 100 KHz bandwidth (0.025% of carrier

frequency) as with the current ~ 25 KHz bandwidth. The only

impact would be the requirement for manufacturers (on their own

and/or guided by the system's managers) to spread the crystal

frequencies over an ~ 75 kHz band rather than over the current

~ 5 kHz band. The impact on the ground processing system would

only be proportional to the increased number of users—this would

have to be upgraded, anyway, no matter which option were chosen.

The impact on the satellite receiving, processing and retransmitting system would be confined to added circuitry, that is

light-weight; and to an increase in the satellite downlink

bandwidth. Sophisticated on-board antennas would not be

required.

Table 7-1 recapitulates these tradeoffs. In the Table,

"baseline" connotes the simplest and least costly system

(increased bandwidth), upgraded only to the extent of being able

to handle the increased traffic demand. The legend "not

intrinsically affected" pertaining to the column headed

"timeliness of data delivery" connotes the fact that there are no

basic reasons impeding the rate of data turnaround — except cost,

that is reflected in the second column.

We see that, based on the tradeoff criteria stated in

Section 7.5.2, Option b, Systematic Polling, infringes the

primary criterion of low cost to the users. Option a, Space

Diversity, infringes the criterion of low cost of the space

segment. We are thus led to favor Options c, Interferometer, and

d, increase the system's bandwidth. We note that an advantage of

selecting these two options is that they are complementary.

106
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8.0 ADCLS Specifications and General Configuration

8.1 ADCLS Specifications

From the foregoing, we see that a data collection and position location system capable of meeting the anticipated year 2000

traffic demand ought to incorporate the following functions:

Primary Functions -- required to obviate saturation

1) Capability of performing position fix based on a single

platform message (instead of the currently required five

messages).

2) Capability of relaying random access data messages in a

manner similar to ARGOS--but over a bandwidth of up to 150 kHz

(instead of the current ~ 25 kHz).

3) Should 150 kHz not be possible incorporation of one or

more additional improvements, e.g. narrower acquisition and

tracking bandwidth, optimized transmission rate

Secondary Functions -- desirable to enhance "quality of

service" characteristics

4) Capability to exploit the doppler frequency shift to

obtain platform velocity (instead of the current differencing of

two position fixes).

5) Enhance capability to perform position fixing based on

doppler messages—as a complementary feature to Primary Function

1) above -- primarily aimed at resolving positional

discrepancies of interferometer fixes.

These functional requirements give rise to the following

technical specifications:

108
• Carrier frequency: 401.6 raHz (same as ARGOS)

• Doppler Bandwidth:

 c

 ~ 20 kHz

• Allowable Carrier Frequency Excursion up to ~ _+_ 65 kHz

• Total RF Bandwidth: ~ up to 150 kHz

• 4-Antenna Interferometer for position fixing

• Data Format and Modulation: Same as ARGOS

• Message Duration/Repetition rate: Similar to ARGOS

• Number of Equivalent channels: ~ 100 to 150

• Number of Data Recovery Units: ~ 15 to 30

8.2 General Configuration of ADCLS

Based on the specifications set forth in previous Section

8.1, Figure 8-1 depicts the overall ADCLS system configuration.

The system consists of the following three major functional

elements:

• space segment

• communications relay subsystem (see Figure 8-1)

• ground data processing and dissemination subsystem

The configuration synthesized in this section pertains to

the space segment, i.e., that portion of the ADCLS system that is

located on the polar platform. The configuration's major

elements are depicted in Figure 8-2.

In accordance with the specifications set forth in Section

8.1, the operational concept of ADCLS employs a combination of

Doppler frequency measurements and radio frequency interferometer

phase difference measurements for position location. The ADCLS

instrument includes two RF interferometers with extended lateral

antennas, consisting of four, approximately ten meter booms at

right angles to each other, each bearing an antenna at its end,

and one doppler antenna.

109
Space Segment

Communications

Relay

Sub-Systems

Ground

Processing &

Dissemination

Subsystem

r ••

| In-Situ |

I Platforms I

t a

I

I

f

TDRSS

1

TDRSS

Ground

Station

1 ADCLS 1

'

'

Ground

Station

\ •

Dissemination

Network

J

Dissemination

Network

1 I

Users Users

^ Polar Platform

^ Utilities

i f

LUT

1

Use

'

jrs

Figure 8-1. The Overall ADCLS System

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Signals transmitted by the in-situ platforms are

simultaneously received by the ADCLS antennas, are demodulated,

amplified, and then conveyed to the on-board data handling

system. This latter system measures the received signal's

frequency, detects phase differences between the two input signal

representations, and extracts the data transmitted by the surface

platform(s). The collected and processed data is then in turn

supplied to the on-board transmission subsystem for downloading

to the ground processing facility and/or to local user

terminal(s) (LUT's). The downloading can be conceptually

effected in three ways: via TDRSS; direct to local user termals

(LUT); dumped to ground-based antennas when in view of the polar

platforms. The definitive choice among these transmission

options—whether all three, or only TDRSS--is under analysis by

the EOS system designers. Since however, we assume that EOS will

provide either option as a "service" to ADCLS, the ultimate

choice will not significantly influence our physical estimates.

In the EOS mission baseline concept the ADCLS instrument

will be placed on the Polar Orbiter, as one among several other

sensory and housekeeping payloads. We assume here that these

other payloads will have common power supplies, and common

housekeeping, transmission, telemetry and command and control

subsystems. The ADCLS system-peculiar requirement is to provide

interfaces to and from these common subsystems.

8.2.1 Physical Characteristics

The estimated volume, mass and power requirements are based

on an instrument comprised of two interferometers, one doppler

antenna and the electronic package. The estimates are as

follows:

Power requirement = 61 watts

Mass (including antennas) = 37.35 kg (82.17 Ibs)

Volume (including antennas) = 61.95 liters

112
The features assumed for these estimates are twenty to

thirty channels (DRU's); operational frequency is 402 MHz. The

itemized details of the conceptual ADCLS system are shown in

Table 8-1. The estimates shown in Table 8-1 were abstracted from

the following two sources:

1 . NASA Space System Technology Model Volume IIB Space

Technology Trends and Forecasts. NASA Headquarters,

1984.

2. NOSS/ALDCS Analysis and System Requirements Definition

Final Report. ORI-Feb., 1981.

The weight and volume of each components were further

reduced to reflect the development of advanced technologies in

circuitry design, fabrication and installation, estimated to be

possible in the later portion of the 1980 decade. For example,

significant savings in weight and size accrue to use of digital

signal processing schemes in place of analog schemes (currently

used in ARGOS).

8.2.2 Cost Estimates

The costs of the ADCLS elements were estimated utilizing the

Unmanned Spacecraft Cost Model (USCM) developed by the Space

Division of the Air Force Systems Command. The model employs an

empirical parametric estimating technique: it reconstructs the

costs of a number of "functionally equivalent" subsystems and

components -- e.g., antennas, telemetry packages -- that have

been used in various civil and military missions, regresses them,

and derives a "best fit" expression relating costs to key

parameters of the subsystems and/or components being evaluated.

The USCM segregates the costs into non-recurring and

recurring. Non-recurring costs are those associated with all the

113
TABLE 8-1

PHYSICAL CHARACTERISTICS ESTIMATES OF VARIOUS

ADCLS COMPONENTS

ADCLS COMPONENT

ONE-5 CHANNEL RF AMPLIFIER

DOWN CONVERTER, DISTRIBUTOR

ONE-SIGNAL DETECTOR

ONE-CONTROLLER

FOUR-INTERFEROMETER ANTENNAS

AND ONE DOPPLER ANTENNA

FOUR PHASE -COMPARATOR ASSEMBLIES

AND ONE LOOP ASSEMBLY

TWENTY PHASE COMPARATOR UNITS

TWO- POWER DIVIDERS

TWENTY-LOOPS

TWENTY- DATA DETECTORS

TWENTY-FREQUENCY COUNTERS

ONE-FREQUENCY SYNTHESIZER

ONE-POWER CONDITIONER

TOTAL

PHYSICAL CHACTERISTICS

MASS VOLUME

(KG) (LITERS)

1.25 1.35

0.3 0.5

1 .0 1.5

20.0 37.5

3 5

1.5 2.0

0.2 0.1

2.5 3.0

2.0 3

2.5 4

1.6 2.0

1.5 2.0

37.35 61.95

POWER

(WATTS)

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114
activities of design, development, manufacturing and testing of a

single space qualified prototype. The recurring costs are those

associated with all the activities of fabricating, manufacturing,

integrating, assembling and testing of the flight hardware. The

USCM subdivides the cost items by hardware elements and by

subdivision of work for each element as depicted in Figure 8-3.

For the purposes of costing the ADCLS falls within the

communication area of activity. We have computed the recurring

and non-recurring costs for the elements . that are ADCLSpeculiar. Costs associated with the power supply, transmission

and command and control system components are excluded from the

cost estimates. Costs related to housekeeping functions, i.e.

thermal control, attitude control, and propulsion are also

excluded because they are common to other payloads on the

platform.

The USCM is constructed based on the historical cost data of

various spacecraft programs. The USCM Cost Estimating

Relationships (CER) were developed by using multiple regression

analysis, engineering logic and programmatic information. The

relationship represents the best fit through the data. The cost

estimating relationship for complete communication system

analogies to ADCLS are of the following form:

y = a x "

where:

y = cost in thousand of 1979 constant dollars

a,b = CER constants

x = weight of the complete system in Ibs

The CER constants applicable to the above relationship for

ADCLS cost estimates are:

115
ELEMENTS OF COST

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LAUNCH & FLIGHT OPNS

FLIGHT HDWR LEVEL

INTERSTAGE/DISPENSER

SPACECRAFT

SPACECRAFT LEVEL

STRUCTURE

THERMAL CONTROL

TT&C

EPSJ

ACS,

COMMUNICATIONS

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116
CER Constant

a b

For Recurring Cost: 49.96 0.87

For Non-Recurring Cost: 564.68 0.56

The corresponding ADCLS costs derived from the USCM are:

Recurring Cost: $2,314,318 (1979 $) =

$4.65 million (1985 $)

Non-Recurring Cost: $6,668,710 (1979 $) =

$13.5 million (1985 $)

The sura of the recurring and non-recurring costs of the

ADCLS instrument expressed in 1985 dollars is $18.15 million.

117
REFERENCES

1. Ashcraft, C.P. and J. Marini. A Combined Data Collection and

Search and Rescue Satellite Package. NASA Publication No. X945-81-17. June 1981.

2. Coates, J.L. The Nimbus F Random Access Measurement System

(RAMS). IEEE Transactions on Geoscience Electronics. Vol.

GE-13, No. 1, January 1975.

3. ECOsystems. Sea Surface Temperature (SST) Measurement Using

Integrated Infrared and Passive Microwave Sensing.. October

1980.

4. Wang, J.R., J.L. King, T.T. Wilheit, G. Szejwach, L.H.

Gessel, R.A. Nieman, D.S. Niver, B.M. Krupp, and J.A.

Gagliano. Profiling Atmospheric Water Vapor by Microwave

Radiometry. Journal of Climate and Applied Meteorology, Vol.

22, No. 5, May 1983

5. Wilheit, T.T., A.T.C. Chang, J.L. King, E.G. Rodgers, R.A.

Nieman, B.M. Krupp, A.S. Milman, J.S. Stratigos, and H.

Siddalingaiah. Microwave Radiometric Observations Near

19.35, 92 and 183 GHz of Precipitation in Tropical Storm

Cora. Journal of Applied Meteorology, Vol. 21, No. 8, August

1982.

6. Wilheit, T.T., A.T.C. Chang, M.S.V. Rao, E.B. Rodgers, and

J.S. Theon. A Satellite Technique for Quantitatively Mapping

Rainfall Rates over the Oceans. Journal of Applied

Meteorology, Vol. 16, No. 5, May 1977.

7. Wilheit, T.T., J.R. Greaves, J.A. Gatlin, D. Han, B.M. Krupp,

A.S. Milman, and E.S. Chang. Retrieval of Ocean Surface

Parameters From the Scanning Multifrequency Microwave

Radiometer (SMMR) on the Nimbus-7 Satellite. IEEE

Transactions on Geoscience and Remote Sensing, Vol. GE-22,

No. 2, March 1984.

8. A Sourthern Hemisphere Drifting Buoy System. Service Argos

Newsletter, CNES, Toulouse, France. No. 21, February 1985.

9. Earth Observing System, Science and Mission Requirements,

Working Group Report-Volume 1, NASA

10. Earth Observing System, Science and Mission Requirements,

Working Group Report-Volume 1 (Appendix), NASA

118
PERSONAL CONTACTS

1. Dr. Thomas Wllheit

Goddard Space Flight Center

10-24-85, 11-6-85

2. Dr. Donald Cavalieri

Goddard Space Flight Center

10-24-85

3. Dr. Robert Binschadler

Goddard Space Flight Center

10-24-85

4. Dr. Robert Chase

Woods Hole Oceanographic Institute

10-17-85, 11-13-85, 11-27-85, 12-04-85

5. Dr. William Large

National Center for Atmospheric Research

11-9-85

6. Dr. Ross Davis

Scripps Institute

11-13-85

7. Dr. Thomas Rossby

University of Rhode Island (Bay Campus)

11-15-85

8. Mr. Charles Cote

Goddard Space Flight Center

9. Mr. Michael Taillade

Service ARGOS, Toulouse, France

10. Mr. Ray Allison

USDA Forest Service

119
QUESTIONNAIRE RESPONDENTS

1 . Ms. Carol Pease

NOAA/PMEL

2. Richard Byles

Virginia Institute for Marine Science

3. Bill Large

National Center for Atmospheric Research

4. Don Murphy

U.S. Coast Guard International Ice Patrol

5. Martial Car

U.S.N. Oceangraphic Office

6. Dr. Hansen

NOAA/Atlantic Ocean Marine Laboratory

7. Ivan Rissaver

U.S. Coast Guard R&D Center

8. Roger Colony

University of Washington, Polar Science Center

120