Technical Paper 300 1IE.

~~~ 

Et. 

~ [A D

THE EFFECTS OF WORK-REST, TARGET

ACTIVITY , BACKGRO UND NOISE, AND STRING

SIZE ON OPERATOR INTERPRETATION OF

UNATTENDED GROUND SENSOR RECORDS

Harold Martinek

Army Research Institute for the Behavioral and Social Sciences

and

Starling Pilette and Billy Biggs

* H RB-Singer, Inc. 10

BATTLEFIELD IN FORMATION SYSTEMS TECHNICAL AR

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U. S. Army

Research Institute for the Behavioral and Social Sciences

June 1978

Approved for public release ; distribution unlimited.

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iI 005 * ---~——-~~~~~ — — -— 

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-

U. S. ARMY RES EARCH INSTITUTE

FOR THE BEHAVIORAL AND SOCIAL SCIENCES

A Field Operating Agency under the Jurisdiction of the

Deputy Chief of Staff for Personnel

W. C. MAIlS

JOSEPH ZEIDNER COL . CS

Technical Director (Designate) Coinnsandcr

Research accomplished

under contract to the Department of the Army

HRB—Siriger , Inc .

NOTICES

DISTRIBUTION. Primary distribution of this report has been made by ARI. Please address correspondence

concerning distribution of reports to: U. S. Army Research Institute for the Behavioral and Social Sciences.

ATTN PEAl- P . 5001 Eisenho~~ r Avenue , Alexandria , Virginia 22333

FINAL DISPOSITION: This report may be destroyed when it is no longer needed. Please do not return it to

the U. S. Army Research Institute for the Behavioral and Social Sciences. 4 ~~~~~~~~~ The findings in this report crc not to be construed Cs an official Department of the Army position .

unless so designated by Oth r authori~Cd documents.

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It

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Unclassified

SECURITY CLASSIFICATION OF THIS PAGE (W ~ia~ Oat. Entered)

REPORT DOCUMENTATION PAGE READ INSTRUCTION S

BEFORE COMPLETING FORM

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C pmUpER - -

Technical ~~~~~~~~~~~~~

I. REPORT NUMBER 

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1 [2. GOVT ACC ESSI~~~~~~ 2 ~~~~~~~~~~~~~~

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IxPE aE.aEPORT .

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PE,

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I~ THE~~FFECTS OF~~ORK/REST, TARGET ACTIVITY,~~ ACK-j -- ~~RO ND NOISE , AND ~~~ING IZE ON PERATOR _INTER-I

PRETAT~~ N OF UNAT~~ NDED LUND S~~~SOR RECO~DS ~ / 6. PERFORMING ORG. REPORT NUMBER 

~~~ ~~ - ~~~

C l. AUTHOR(.) ~~~ ~~~ t s t n ~~~’ ifl ~ ER(.)

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~~~~~~T~~~~rtinek , ARt~ ~

md Sterii9~~~~ietteJ

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and 

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9. PERFORMING ORGANIZATION NAM E AND ADDRESS 10. PROGRAM ELEMENT , PROJECT . TASK AREA 9 ~ GR~ UNIT NUMBERS

HRB-Singer , Inc . 

~ ________

State College , Pennsylvania 16801 ooi~~~~

P.O. Box 60, Science Park 

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II. CONTROLLING OFFICE NAME AND ADDR ESS ,tf OPT DATE I 4

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5001 Eisenhower Avenue , Alexandria , VA 22333 54

Ti. MONITORING AGENCY NAME & ADDRESS (If d iff eren t from Co~ trollin~ Offi ce) 15. SECURITY CLASS. (of (hi. r.porf)

Department of the Army Unclassified Office of the Assistant Chief of Staff for _____________________________

IC.. OECLAS SIF ICA T IO N/DOWNGRADING Intelligence (DAMI) SCHEDULE

Washington , DC 20310 ____________________________

16. OISTR tBUTION STATEMENT (of thi. R.pozS) 

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Approved for public release; distribution unlimited.

Il. DISTRIBUTION STATEMENT (of the .b.tract .nt.r. d In Block 20. If dlff.,.nt from R.port)

IS . SUPPLEMENT ARY NOTES

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9. KE Y WORDS (Continue on rev.,.. .ld. If n.c.aeay aid Id.nttty by block nsaib.r)

Unattended ground sensors Seismic sensors

Work/rest cycles Surveillance

Target activity Target acquisition

P String size Remotely monitored sensors

20. AlIT PACT (CCfl(lnUSJtfl ~~2may aid I d entif y by block nomb.r)

• .

~1 ~~~ ü~ roseent: o investigate the relationships between unattended ground

sensor (UGS) operator performance and work/rest cycles , sensor string size ,

target activity levels, and noisy/quiet environments and to identify sources

of operator error that can be eliminated through the use of new interpretation

tech ue ~

__. ‘

—~~-,t-.. and training.

four different work/rest conditions : 2 hours works, 1 hour rest; 2 hours work,

e ators moniL.ored UGS records for 8 hours of worktime under

15 minutes rest; 4 hours work. 1. hour rest; and 4 hours work. 15 minutes rest -

DO 

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473 EDITION OF 1 NOV 65 11 01101. TE

9 Unclassified ~~~~ 

~~ sscu~~rry CLASSIFICATION OF ‘THIS PAGE (1kw Oat. tnfa .d)

G __ ~

8 _ ______
Unclassified

SECURITY CLASSIFICATION OF THIS PAOE(IThw Oaf. Bnfar.d)

20.

~,The UGS records included counterbalanced variations of three string sizes

(2, 3, and 4 sensors), 12 targets per hour or 6 targets per hour , and high

and low “battle” no ise . ~ I.

~ 8 hours of monitoring, 2-hour work shifts

interspersed with 1-hour or 15—minute rest periods are to be preferred over

4-hour work shifts interspersed with 1-hour or 15-minute rest periods. For

heavy short—term monitoring requirements, for example , enemy attack requiring

periods of concentrated monitoring, an operator can perform satisfactorily for

one 4—hour shift but performance will deteriorate during a second 4—hour shift.

Performance was equal using 2 , 3, or 4 sensor strings in the low-targetactivity condition. However, during the high-target—activity condition , use

of 3 or 4 sensor strings resulted in more target detections as compared to

use of 2 sensor strings.

Operator performance during the high “battlefield” noise was equal to

that during low noise . During the high-target—activity conditions the operators detected more targets than during the low-target-activity condition .

However, they detected a higher percentage of targets during the low

condition .

V

Unclassified

SECURITY CLASSIFICATION OF THIS PAGEfUkSn Oaf. Entered)

~
Technical Paper 300

THE EFFECTS OF WORK~

REST, TARGET

ACTIVITY , BACKGROUND NOISE, AND STRING

SIZE ON OPERATOR INTERPRETATION OF

UNATTENDED GROUND SENSOR RECORDS

Harold Martinek

U.S. Army Research Institute for the Behavioral and Social Sciences

and

Sterling Pliette and Billy Biggs HRB.Singer, Inc.

BATTLEFIELD IN FORMATION SYSTEMS TECHNICAL AREA

Submitted as complete and Approved By: technically accurate, by: A.H. Blrnbaum, Acting Director

ORGANIZATIONS ANb SYSTEMS

RESEARCH LABORATORY

Edgar M. Johnson

Technical Area Chief

Joseph Ziedner

TECHNICAL DIRECTOR (Designate)

U.S. ARMY RESEARCH INSTI~ UTE FOR THE BEHAVIORAL AND SOCIAL SCIENCES

5001 Eisenhower Avenue, Alexandria, Virginia 22333

Office , Deputy Chief of Staff for Personnel

Department of the Army

June 1978

Army Pro~sct N~ pø.r Surveillance Systems

1x1e37230101

2Qe 21O4A721 -

.

App roi*d for public release; dist ributio n unhimitad.

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ARI Research Reports and Technical Papers are intended for sponsors of

R&D tasks and other research and military agencies. Any findings ready for

implementation at the time of publication are presented in the latter part of

the Brief. Upon completion of a major phase of the task, formal recommendations for official action normally are conveyed to appropriate military

agencies by briefing or Disposition Form.

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FOREWORD

The Battlefield Information Systems Technical Area is concerned with

the demands of the future battlefield for increased man—machine complexity

to acquire , transmit, process , disseminate , and use information. The research focuses on the interface problems and interactions wi thin command

and control centers in areas such as topographic products and procedures ,

tactical symbology , information management , user—oriented systems, staff

operations and procedures , and sensor systems integration and utilization .

An area of special interes t is that of human fac tors problems in the

presentation and interprctation of surveillance and target acquisition information. One relatively new source of intelligence infcrmation is rem ote

monitoring of the battlefield using seismic , acou stic, and maqnetic unattended ground sensors. When these remote sensors are activated by enemy

personnel or vehicle movement, a monitor display located behind our lines

indicates the activity . The operator can derive from Ihis display not only

the presence of the enemy but such info rmation as the direction and speed

of convoys and personnel , the number of vehicles in a convoy , and the composi tion of the convoy , for example , armored or wheeled vehicles.

The present pub lication inve stigates the effect on operator performance of several variables of operational significance . Information on

work/rest cycles, background noise , and target activity levels have implications for operator assignment doctrine and the intelligence analyst ’s

reliability estimates of information derived from sensor reports. The

results on string size indicate that sensor systems can be made more cost

effective by using fewer sensors per string without loss of information .

ARI Technical Papers 299 and 281 describe earlier resea rch on una ttended

ground sensors .

Research in the area of sensor systems in tegra tion and utilization

is conducted both in—house and by contract. The project reported here

was conducted jointly by ARI and HRB—Singer , Inc. This research is responsive to requirements of Army Project 2Q6627O4A721 and to special requirements of the Assistant Chief of Staff for Intelligence . The

cooperation and assistance of the participa ting opera tors and staff of

the UGS USAIN school at For t Huachuca , Ariz., is greatly appreciated .

(

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Jb9~PH ZEIDNER - - Technical Director (Designate)

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ThE EFFECTS OF WORK/REST , TARGET ACTI VITY , BACKGROUND NOISE , AND FTRING

SIZE ON OPERATOR INTE RPRETATION OF UNATTEN DED G~ )UND SENSOR RECORDS

BRIEF ________________ _____

Requirement:

The experiment was designed to (1) investigate the relationships between unattended ground sensor (UGS) operator performance and various

system-dependent and target-dependent parameters including work/rest cycle ,

number of sensors in a string , target activity leve l, and background noise;

and (2) to iden tif y sources of operator error that can be reduced through

new interpretation techniques, procedures , and training .

Procedure :

Two 8—hour scenarios were compiled from a data bank of taped recordings of UGS act ivations during field tests by Modern Army Selected System s

Test, Evaluation, and Review (MASSTE R) at Fort Hood , Tex. The tests were

run under typical operational conditions using groups of personnel and

wheeled and tracked vehicles as tarqets. Roughly 80% of the sensors were

seismic , the remainder confirmatory . All sensors were deployed in typical

string configurations . The scenarios included counterbalanced variations

of strings of three different sizes (2 , 3, and 4 sensors), high and low

target activity, and high and low “battle” noise . The high-noise condition

contained the same targets as the low but also included typical aircraf t,

artillery, and high background noise taped durinq the above field tests.

Four work/rest cycles were used , each of which involved a total of 8 hours

of work with work and rest periods of different durations : 2 hours work,

1 hour rest; 2 hours work , 15 minutes rest ; 4 hours work, 1 hour rest;

and 4 hours work , 15 minutes rest. Sixteen students at the U.S. Army

Intelligence Center and School (Ground Sensor Department) at Fort Huachuca,

Ariz. , were given test procedure training and a 1—hour review consisting

of instruction and practice in interpretation of seismic sensor records .

They were also given a background questionnaire and a 30—minute pretest.

Pretest results were used as the basis for assigning operators to the experimental groups . Each group w as as signed one of four work/rest cycles

the first test day and a different one the second test day. Subject

performance was scored against the known target activity for correct detections , wrong detections, correct identifications , elapsed time , and

confidence.

T :

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Fi.~dings :

For 8-hour monitoring shifts , 2—hour work shifts interspersed with

1—hour or 15-minute rest periods were better than 4-hour work shifts interspersed with 1—hour or 15—minute rest periods . For important short-term

monitoring requirements , operator performance was satisfactory for the

first 4—hour shift, but deteriorated during the second 4-hour shift.

Operator performance was equal using 2- , 3- , or 4-sensor strinqs in

the low—taraet-activity condition . However , in the high—target-activity

condition , use of 3— or 4—sensor strings resulted in more correct target

detections than use of 2—sensor strings .

Operator performance during the high “battlefield” noise was equal

to that during low noise.

During high—target-activi ty conditions , operators detected more

targets than during low—target-activi ty conditions . They detected a

higher percentage of targets during the low condition, however.

Sources of operator errors included the use of 2-sensor strings for

the detection of targets in a high—target-activity condition , endpoint

determination , measurement , arithmetic calculations , and use of confirming sensors .

Utilization of Findings :

The major findings regarding work/rest cycles can he used by all

operational UGS commands and school uni ts for assignmen t to duty cycles .

Considering only operator performance and assuming high-sensor reliability ,

2—sensor strings, rather than 3— or 4—sensor strings , can be used to reduce costs if only low— target activity is expected. If high activity is

expected , 3—sensor strings can be used rather than 4 with no operator

performance de’~rement. Operator problem areas identified should be used

as the basis for a new training program . A UGS ruler should be developed

for measuring sensor activation times directly on the display; a job aid

(such as a nomograph) should be developed to simplify ari thmetic computations and decimal point placement. A programed text for other operator

errors should be developed and validated.

_ __ _ 

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THE EFFECTS OF WORK/REST , TARGET ACTIVITY , BACKGROUND NOISE , AND STRING

SIZE ON OPERATOR INTERPRE TATION OF UNATTENDE D GROUN D SEN SOR RECORDS

CONTENTS

Page

BACKGROUND 1

OBJECTIVE S 2

METHOD 2

Research Considerations 2

System—Dependent Variables 2

Target-Dependent Variables 4

Population and Sample 5

Research Design 5

Dependent Variables 6

Development of the School Solutions 9

Administration Procedure 10

RESULT S AND DISCU SSION 12

Correct Detections 12

False Alarms 23

Correct Identifications 23

Error Analysis 32

CONCLUSION S AND RECOMMENDATIONS 33

Summary of Results 3 3

Recommendations for Operational. Application 34

Training Recommendations 35

REFERENCES 37

APPENDIX A : DEVELOPMENT OF THE SCENARIOS 39

B : OPERATOR INSTRUCTIONS 4 1

DISTRIBUTION LIST 53

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LIST OF TABLES

Table 1. Work/rest cycles investigated (time in hours) 3

2. Schedule of administration 7

3. Number of personnel and vehicle targets in Scenarios A

and B 9

4. Time schedule ~~~ work/rest cycles 11

5. Analysis of variance table for target detection 13

6. Detection rights for Work/Rest Cycle I (2—1) 14

7. Detection Rights for Work/Rest Cycle II (2—1/4 ) 14

8. Detection Rights for Work/Rest Cycle III (4—1) 15

9. Detection Rights for Work/Rest Cycle IV (4-1/4) 15

10. Trend analysis for correct detections by work/res t

cycle 18

11. Mean number of correct detections and completeness

by target activity and scenario 20

12. Mean number of correct detections by target activity

and days 21

13. Mean number of correct detections and completeness

by target activity and string size 21

14. Mean number of correct detections by scenario and

string size 22

15. Mean number of correct detecLions by string size ,

target activity , and scenario 22

16. Analysis of variance table for target identification . 24

17. Correct identifications for Work/Rest Cycle I (2—1) . . 25

18. Correct Identification s for Work/Rest Cycle II (2—1/4) . 25

19. Correct Identifications for Work/Rest Cycle III (4-1) . 26

20. Correct Identifications for Work/Rest Cycle IV (4—1/4). 26

21. Trend analysis for each work/rest cycle identification

score 29
Table 22. Average confidence and elapsed time results 31

B—i . Target log 43

B-2 . Sensor program record 47

LIST OF FIGURES

Figure 1. Correct detections for Work/Rest Cycle I 16

2. Correct detections for Work/Rest Cycle II 16

3. Correct detections for Work/Rest Cycle III 16

4. Correct detections for Work/Rest Cycle IV 16

5. Total correct detections for each work/rest cycle . 17

6. Total correct detections for work/rest cycle pairs . 17

7. Correct identifications for Work/Rest Cycle I . . . 27

8. Correct identifications for Work/Rest Cycle II . . . 27

9. Correct identifications for Work/Rest Cycle III . . 27

10. Correct identifications for Work/Rest Cycle IV . . . 27

11. Total correct identification for each work/rest cycle 28

12. Total correct identification for each work/rest cycle 28

B-l. Example of implant sketch , part II 46

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THE EFFECTS OF WORK/REST , TARGET ACTIVI TY , BACKGROUN D

NOISE , AND STRING SIZE ON OPERATOR INTERPRETAT ION

OF UNATTENDE D GROUND SENSOR RECORDS

BACKGWDUND

Although significant technical achievements have been accomplished

in the deve lopment of unattended ground sensor (UGS) systems , insufficien t

effort has been directed toward the study of the person who must operate

and monitor the system and the interface of this operator and the equip—

merit. Of major concern are interpretation errors on the part of the

operator——errors of omission and errors of commission (false alarms)

Depending upon field conditions , human error can be fairly substantial

in attempting to isolate valid target activations .

Human factors studies have been conducted to investigate techniques

of improving operator interpretation performance . One study (Cravens ,

1972) investigated a limited automatic processing technique designed to

suppress spurious ac tivations and enhance meaningful activations . The

intention was to provide a simplified display to the monitor by having

the equipment identif y con tinuous targetlike sequences using specified

detection criteria. The technique caused no improvement in operation

target detection performance and , in fact, increased the number of false

detections .

The second study (Martinek , Hilligoss, & Lavicka , 1978) investigated

the relative utility of a 1:25,000 situation map display and tape playback at eight times the normal speed of review (compressed time). The

map covered small lights that showed the ground location of the sensors

and blinked when the sensors were activated . Although the operators

were able to determine the location of targets quickly because of the

map presentation, they had difficulty separating target activations from

nontarget activations . Because of the lack of a permanent record , it

also was difficult to determine target speed and length of the column .

The use of a compressed—time review was insufficient to compensate for

lack of a permanent record .

The Remotely Monitored Battlefield Surveillance System (RE MBASS)

proj ect focuses on providing support in conflict situations of middle

and high intensity . In such situations, the DOS operators must be constantly alert to distinguish valid target activations from the many

“false” activations produced by helicopters , low—flying fixed-wing aircraft , and artillery shell bursts, etc., in addition to nonmilitary and

random false activations caused by wind, rain, small animals, and malfunctioning sensors. Operator errors from these and other sources cause

the total system to have less than optimal reliability . An in—depth

study of these sources of errors could be the basis for specialized

training to enhance system reliability.

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OBJECTIVES

Th~ general objective of this effort was to develop information

concerning the level of performance exhibited by trained DOS operators

in interpreting display patterns (activations) obtained from sensors

deployed in the field. More specifically, the objective was to investigate the relationship between operator performance and the following

system-dependent and target-dependent parameters : work/rest (W/R) cycles,

sensor string size, target activity level, and “noisy” versus quiet environments. An additional objective was to identify, by an analysis of

the monitor errors, interpretation training techniques or procedures

that could improve operational performance.

METHOD

Research Considerations

Variables considered for inclusion in the present study can be divided in to two categories that present different requirements for the

research design and procedure. In a monitoring situation, one group,

the system—dependent variables, represents variables whose value is

known or even sometimes controlled ; for example , training and work/rest

cycle. The second group, Target—Dependent variables, are variables whose

vaLes are always uncertain to the operator ; for example , target type,

target direction, and activity level. These variables are constantly

changing during the course of an operationa l mission and their occurrence during an experiment must also change with no warning to the operator participating.

Sys tern- Dependent Variables

The primary System-Dependent variable investigated in the present

study was the work/rest cycle. There is disagreement among operational

personnel as to the optimal work/rest cycle. Most agree, however, with

the conclusion of the Cavalry Troop Test Report (U.S. Army, January 1972)

that work—shift length affects operator performance. During this field

experiment , 12 operators worked in two shifts and manned six stations.

The work shifts were 2 hours for the first week of the test and 4 hours

for the second week. At the end of the experiment, the operators felt

that the 2—hour shifts were fine but that the 4-hour shifts were too

long. The conclusion regarding the shifts must be regarded as tentative

because the work period was confounded with several other variables such

as experience, target activity, and possible weather changes. Moreover,

work/rest cycle as a function of other variables was not investigated.

On the basis of these results and discussion with operational per—

gonnel, a 1-hour work/rest cycle was eliminated from the present experiment. At the other extreme, it was felt that effects of a long work

shift should be assessed, but probably one no longer than 8 hours. It

2

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was unreasonable to assume that a monitor would sit at a display for

8 hours and never leave the post. Therefore , it was decided to use a

4—hour shift with a 15-minute break . A 15—minute break might not have

been sufficient, so a 1—hour break was also used . Because 2 hours is a

typical length of worktime for a perceptual visual task (e.g., certain

kinds of sentry duty) -and was found acceptable in the above study, two

work shifts were planned that contained 2-hour work periods. Rest periods

were planned for 1 hour and for 15 minutes. Table 1 shows four work/rest

cycles that were selected for study . For every work/rest cycle investigated, the total amount of worktime was 8 hours.

Table 1

Work/Rest Cycles Investigated

W/R I W/R II W/R III W/R IV

Periods (in hours) (in hours) (in hours) (in hours)

Work 2 2 4 4

Rest 1 .25 1 .25

Work 2 2 4 4

Rest 1 .25

Work 2 2

Rest 1 .25

Work 2 2

Total

work 8 8 8 8

Total

rest 3 .75 1 .25

Total

time 11 8.75 9 8.25

The second System-Dependent variable of concern was training. Although training was not varied as an experimental condition, the m dividual reports were analyzed with the intent of improving training.

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During discussion with training personnel at Fort Huachuca , several

points became evident:

1. Lecture—discussion and team training techniques are heavily

used .

2. Practical exercises are typically based on ideal clearcut

target ac tivation patterns occurring in a relatively sanitized

environment.

3. In the formulas used for computing speed , length of column ,

and number of units in a column , only the most essential fac tors

are taught. Factors such as environmental effects are not considered part of the formulas.

Although the trainees were adequately prepared to detect , interpret ,

and compute target activations that appeared in orderly stairstep patterns, on— the— job experience may be required to cope with the more complex target environment of the real world , which includes unreliable

sensors, radio masking, and other noise sources. In the last analysis ,

the value of DOS will be gaged by the quality of information it can provide under operational restraints . Thus, the scenarios used in the research contained activations that occurred during actual field conditions .

The reports of these inexperienced operators could then be analyzed to

find problem areas to revise training and develop improved interpreta tion

techniques.

Target-Dependent Variables

After review of current Fort Huachuca training materials (U.S. Army ,

February 1971; U.S. Army , November 1972; U.S. Army , 1973; U.S. Army ,

December 1970; U.S. Army , September 1971), relevant research previously

conducted (U.S. Army , December 1970; U.S. Army , May 1972; U.S. Army,

June 1969), and consultation with knowledgeable personnel , nine Target—

Dependent variables were identified. From these, three were selected

for the present experiment: target activity level , sensor size , and

background noise .

Target Activity . Target activity was defined as the number of

sensor strings partially or completely activated during a given time

segment. Two levels of activity were systematically assigned based on

anticipated battle conditions. (These are consistent with target conditions as discussed in the DCPG Phase III Field Experiment Report,

1970.) Low target activity was designated as three target activations

occurring within 30 minutes. High target activity was designated as

six target activations occurring within 30 minutes (West, 1973). Because the targets were randomly assigned to the low- and high-activity

conditions, equivalent target difficulty was assumed .

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Sensor Size. The number of sensors in a string yielded different

activation patterns and also had a potentially important effect on

monitoring performance . Assuming the necessity of two working sensors

for calculating speed and length of column , the question was asked , “How

important are additional sensors to the complete reporting process from

detection to dissemination?” Because there was a reasonable variation

in the number of sensors per string, three string sizes (2, 3, and 4 sensors) were selected as levels of study .

Background Noise. DOS alone cannot distinguish between friend and

foe, nor between natural and manmade disturbances. A false activation

will produce the same result on the RO 376 event recorder as an activation made by a valid target. Generally , valid target activations differ

from false activations in that valid target activations appear in distinguishable patterns. Even so, false activations can have a major effect on operator performance , and any analysis of performance should

consider this. The level of false activations could be manipulated

readily to either high— or low-noise conditions by carefully dubbing in

or erasinq battlefield noise . The presence of various noise tyoes in

the BASS and Project 1030 field data offered the necessary varic~

’

~ility

in readily manipulated form . The amount of noise inserted into high— and

low—noise scenario segments was subjectively estimated.

The problem of estimating what noise to include was partially alleviated by using characteristic noise from five major noise sources :

fixed—wing aircraft, helicopter, artillery shell bursts, weather activity,

and radio interference . Noise could not be superimposed over target activity because of the characteristics of taçe recorders . However, target activation patterns were not free of noise because noise did occur

in the field during the original recording of the activations .

Population and Sample

The population of concern is the Army enlisted operator (MOS 17M2O) ,

school—trained at the U.S. Army Intelligence Center School, Fort Huachuca ,

Ariz. DOS classes were selected on the basis of class size as required

by the experimental design and scheduling compatibility.

Research Design

The following independent variables and levels were included in the

design: work/rest (4), sensor string size (3), target activity (2), and

noise (2). The latter three variables and their levels were systematically presented in two matched scenarios. Each scenario was composed of

16 30—minute segments . Each 30—minute segment included one level of

target activity and noise and all three levels of sensor string size.

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Table 2 presents the schedule of administration showing the work!

rest cycle and scenario assigned to each operator each day . The 16 operators were divided into groups of two on the basis of pretest scores.

They were administered the two scenarios in a counterbalanced arrangement across the 2 days. On Day 1, half the operators took Scenario A

and the other half took Scenario B. On Day 2, the groups switched scenarios, switching the work/rest cycles because Work/Rest Cycles I and IV

were never paired with II and III. In the derivation of the analysis

of variance, an intermediate sum of squares was included to correct for

the partial confounding. The analysis of variance used a balanced

incomplete—block design (Winer, 1962) with an embedded 3 x 2 x 2 factorial composed of the three Scenario variables. As shown in Table 2,

the two highest operators became Group A and the two lowest became

Group H. The operators were thus assigned to maximize homogeneity within

the groups. Across the 2 test days, the matching technique provided a

systematic balance of operator skill level across all of the work/rest

cycles investigated.

Dependent Variables

Separate analyses of variance were planned for the following Dependent variables:

Correct Detections If an ope rator reported an activation

pattern resulting from a valid target,

the response was classified as a correct detection . This variable is

perfectly correlated with detection

completeness except that completeness

is a ratio of correct detections to

total number of targets presented .

Percentage completeness figures are

given where they have special meaning .

False Alarms If an operator reported an activation

pattern resulting from other than a

valid target, the response was classified as a false alarm .

Correct Identifications If, in addition to detecting a valid

target, the operator classified the

target correctly by type (personnel

or vehicle), the response was also

classified as correct identification.

Two dependent measures were considered but were not statistically

:

~ 

analyzed:

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____ - -- -
Elapsed Time Time between tarqet detection and

completion of the report as written

by the subject.

Confidence The operator’s confidence on a

4-point scale as to how confident

he is that the activation pattern

he has reported is a valid target.

A total of 72 target patterns were selec ted for the scenario tapes

to satisfy the requirements of the research design . These patterns were

divided into eight groups of nine targets each . Each group was included

in 2 separate 30-minute segments . The operators were presented nine

targets during each hour of monitoring. One 30-minute segment contained

three targets. The other 30-minute segment contained six targets. Equal

numbers of 2- , 3-, and 4—sensor string sizes were included within each

30-minute segment. Each scenario was composed of 16 of these 30—minute

segments presented to the operator in four sections (I, II , III , and IV) ,

lasting 2 hours each . The number of vehicles and personnel targets

within each 2-hour section is shown in Table 3.

Upon completion of the sce nario format, magnetic tapes were produced

by splicing the appropriate segments of BASS III and DOS 1030 tapes together. These spliced tapes were used to produce four 2-hour scenarios

on RO 376 plot paper. One copy of the scenarios remained as recorded ,

that is, under relatively low—noise conditions. The other copy was

changed to be used for the high—noise conditions . Representative samples

of noise were selected from the original BASS III and TJGS 1030 data to

complete the high noise conditions. Several kinds of field noise (artillery, fixed-wing aircraft, helicopters, radio activity, and random

noise) were “burned in” on the high-noise portions of the scenarios .

Thus, the actual targets in the low- and high-noise sections were identical. The scenarios were duplicated by using the training simulator at

Fort Huachuca, Ariz. Additional information on scenario development is

presented in Appendix A.

Development of the Implant Sketches. To simulate real world conditions, operators were given implant sketches . Implant sketches are

made from topographical maps and are used as a quick reference to reveal

the ground location of sensor strings and individual sensors being monitored . These sketches enable the monitor to visualize better the activity being reported by the sensors because the sketches do not include

the often distracting information found on topographical maps .

The fact that the sensor activations used in this study were obtam ed from two separate field tests involving different terrain and

scenarios eliminated use of the original field sketches . Consequently ,

it was necessary to construct implant sketches that presented appropri—

ate portions of the original sensor fields integrated to simulate a

realistic field situation . Because of several constraints under which

8

— ..

~~~~~~~~ - — .

. 

- — -- - 

~

j __ i —- -
- ~ —

the scenarios were deve loped, 8 different implant ske tches w ere necess ary,

one for each low- and hiqh-noise pair of 30-minute segments . (An example

is given in Figure B-l.)

Table 3

Number of Personnel and Vehicle Tar getsa in Scenarios A and

Total targets Personnel targets Vehicle targets

Scenario A

Section I 18 6 12

Section II 18 4 14

Section III 18 6 12

Section IV 18 4 14

Scenario B

Section I 18 4 14

Section II 18 4 14

Section III 18 4 14

Section IV 18 4 14

Total 144 36 108

a

A target consists of from one to nine personnel or vehicles activating a

sensor string .

b

scenarios A and B are each 8 hours long with four 2-hour sections shown

above . Sections I and II were low noise and Sections III and IV were

high noise and contained exactly the same targets.

Development of the School Solutions

The school solution to all records was based on standard computational procedures . A majori ty of the school solutions, however, did not

correlate well with ground truth . In some cases, gross discrepancies

existed-- in speed or number of targets, for example . The poor correlation between the school solution and ground truth was probably due to

lack of information concerning the actual detection range of the sensors

and irregular activations.

9
Actual Detection Range. Because the actual detection ranges of

the sensors were not known , manufacturers ’ specifications were used (U.S.

Army, September 1971). Compounding this problem is the fact that the

computational methods used by the Army do not integrate the effects of

several additional important variables that influence detection range .

For example, for calculating length of column, the detection range is

required, but gain setting (whether high, medium , or low), soil type,

and environmental effects usually cannot be considered even though it

has been proved that they affect detection range .

Irregular Activation. Irregular and inexplicable activations occurred in the target activations . These activations probably have simple

explanations, but the information was not available and it was necessary

to work around them. Where gross discrepancies existed between school

solution and ground truth, it was necessary to make reasonable adjustments to some or all of the following parameters for a particular target: reported distance between sensors, de tection range specifications

as reported by manufacturers , and change of target type to use a different assumed distance between units . Troublesome school solutions were

discussed with Fort Huachuca training personnel to safeguard against unreliable or invalid data from inaccurate school solutions .

Adininistr~ tion Procedure

Data were collected over a 2-1/2-day period . During the first half

day, all operators were given test procedure training (Appendix B) that

included a familiarization briefing in which a background (school and

experience) questionnaire was completed . The operators were then given

a 1-1/2-hour review of instruction and practice in interpreting seismic

sensor records. During this time, questions were answered and operators

were given the correct interpretations of the records . Finally , a

30—minute pretest was administered, scored, and used as the basis for

matching the operators into homogeneous groups.

The scenarios were displayed by specially built training simulators

identical in appearance to the operational I~

D 376 event recorder normally

used in the field. The simulation of the display equipment was judged

to be perfect with respect to operator display interface. The XT plots

and the speed of presentation were identical to that found in the field.

The only difference was that no sensor with associated electronic equipment was operating because the XT plots had been prepared earlier.

Operators were assigned work/rest cycles and a particular order

for work/rest (W/R) cycles and scenario presentation . The testing

schedule was conducted with the time schedules presented in Table 4.

During the testing, the two experimenters continually insured that each

ope rator was using the proper implant sketch (Fig . B-l) and sensor program record (Table B—2) for each 30—minute segment . The program record

contained the following inEo rmation: pen number , string/field number,

sensor type, and detection radius.

10

—- ___ 4__ - -- . — —______
Table 4

Time Schedule of Work /Rest Cycles

W/R Cycle I (2— 1) W/R Cycle II (2—1/4)

Briefing 7:20 — 7:30 a.rn . 7:20 — 7:30 a. m.

Work 7:30 — 9:30 7:30 — 9:30

Finisha 9:30 — 9:35 9:30 — 9:35

Rest 9:35 — 10:35 9:35 — 9:50

Work a 10:35 — 12:35 p.m. 9:50 — 11:50

Finish 12 :35 — 12 :40 11:50 — 11:55

Lunch 12:40 — 1:40 11:55 — 12:10 p.m.

Work 1:40 — 3:40 12:10 — 2:10

F~ fl~ Sh a 3:40 — 3:45 2:10 — 2:15

Rest 3:45 — 4:45 2:15 — 2:30

Work 

a 

4:45 — 6:45 2:30 — 4:30

Finish 6:45 — 6:50 4:30 — 4:35

Secure 6:50 — 7:00 4:35 — 4:45

W/R Cycle III (4—1) W/R Cycle IV (4—1/4)

Briefing 7:20 — 7:30 a.m. 7:20 — 7:30 a.m.

Work 7:30 — 11:30 7:30 — 11:30

Finish 11:30 — 11:35 11:30 — 11:35

Lunch 11:35 — 12:35 p.m. 11:35 — 11:50

Work 12:35 — 4:35 11:50 — 3:50 p.m.

Finish 4:35 — 4:40 3:50 — 3:55

Secure 4:40 — 4:50 3:55 — 4:05

aFive minutes were allowed to finish calculations on targets already

annotated because some targets appeared very near the end of the work

period.

3

- 

11

- ______-

~

--

- . 

~~~~
-- r

Durinq data collection , the operator annotated the scenario plot

by drawing a circle around each potential target pattern and numbering

these circles consecutively as they were drawn . The operator recorded

each potential target on the sensor target log report (Table B—l) - After

recording the pattern number , the operator recorded the pen number associated with each pattern , the approximate time, and the operator ’s

confidence usin-~ a 4—point scale (4 Ic’w , 3 = 50-50, 2 = high , and

1 = positive) -

The operator then determined and recorded target direction, speed .

and target type, and number of units in the tarqet (quantity) -

RESrJLTS AND DISCUSSION

Correct Detections

Table 5 presents the analysis of variance (ANOVA ) results for correct detections . Of primary interest is the nonsiqnificant result for

the work/res t (W/R) cyc le variable . The ANOVA indicates tha t there

were no differences in number of correct detections as a fun ction of

work/rest cycles.

It is equally important, however , to de term ine if there is a trend

over the 8-hour work shifts, whether due to learnina or fatique or a

combination of the two. Because each 8—hour test scenario consisted of

four 2—hour sections counterbalanced in order of presentation , it was

possible to analyze performance over the four sections without scenario

effects confounding the results . Because of the significant difference

between the two scenarios (Table 5) , each scenario had to be considered

individually at the beginni ng of a trend anal ysis for each work/rest

cycle. Tables 6 through 9 present correct detection data by work/rest

cycle , scenario, and time period.

A graph presenting the same data is shown in Figures 1 through 4.

The first two figures indicate a possible slight positive trend in

Work/Rest Cycles I and II; the second two figures indicate a moderate

negative trend in Work/Rest Cycles III and IV, perhaps due to fatigue .

Wi thin each cycle , the general tr~ nd pa ttern appears to he similar for

the two scenarios . ‘n other words , although the number of correct detections in any time period may depend on which scenario was used , the

trend pa ttern is generally the same.

Figure 5 ind ica tes the overall trend in each of the four work/

rest cycles for both scenarios combined . Components of linear , quadra tic ,

and cubic trends were analyzed . A discussion of the computational details of the analysis is given in Winer (1962) . As shown in Table 10,

none of the trend components was statistically significant for any

individual W/R cycle.

12

—- . - - - - —~~~- -

~~~~~~~~~~ J__ __

~~
Tabl e 5

Analysis of Variance Table for Targe t Detection

Significance

Source of variation df SS MSS F level

Work/r est cycles 3 7.344 2.488 1.94 NS

Days 1 .010 .010 .01 NS

String size 2 206 .646 103.323 80.53 .01

Noise 1 1.260 1.260 .98

Target activity 1 283.594 283.594 221.04 .01

Groups 6 148.562 24.760 19.30 .01

Scenarios 1 6.510 6.510 5.09 .05

Days x string size 2 .584 .294 .23 NS

Days x noise 1 .095 .095 .07 NS

Days x target activity 1 6.511 6.511 5.07 .05

String size x noise 2 2.522 1.261 .98 NS

String size x target

activity 2 216.063 108.032 84.21 .01

String size x scenarios 2 24.144 12.072 9.41 .01

Noise x target activity 1 .511 .511 .40 NS

Noise x scenarios 1 2.910 2.910 2.27 NS

Target activity

x scenarios 1 23.006 23.006 17.93 .01

Days x string size

x noise 2 5.803 2.902 2.26 NS

Days x string size

x target activity 2 .642 .321 .25 NS

Days x noise x target

activity 1 .259 .259 .20 NS

String size x target

activity 2 1.582 .791 .62 NS

String size x noise

x scenarios 2 7.568 3.784 2.95 NS

String size x target

activity x scenarios 2 61.577 30. 789 24.00 .01

Noise x target activity

x scenarios 1 4.600 4.600 3.58 NS

Residual 151 276.249 1.829 1.43

Error 192 246.500 1.283

Total 383 1386.490

13

- - 

.—-

-—--- —--- — — 

~~~~~~~ ~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~ -

~~~~~~~~ -- - 

-- __i__

~~~~~~~~_d~I
Table 6

Detection Rights for Work/Rest Cycle ~ (2..1)a

2-hour

periods 1 2 3 4 Total

Scenario A 30 39 35 38 142

Scenario B 40 41 33 43 157

Total 70 80 68 81 299

a

Four_hour work periods separated by 1-hour rest periods for a

total of 8 hours’ work .

Table 7

Detection Rights for Work/Rest Cycle II

2-hour

periods 1 2 3 4 Total

Scenario A 34 34 32 42 142

Scenario B 41 44 42 43 170

Total 75 78 74 85 312

a

~\~~ .hour work periods separated by 15-minute rest periods for

a total of 8 hours’ work .

p

14

~~- -
Table 8

De tection Ri ghts for Work/Rest Cycle III

2-hour

periods 1 2 3 4 Total

Scenario A 46 48 46 38 178

Scenario B 43 43 39 33 158

Total 89 91 85 71 336

~~~~~~~~~ work periods separated by 1—hour rest periods for a

total of 8 hours ’ work .

Table 9

Detection Rights for Work/Rest Cycle IV (4_1/4)a

2-hour

periods 1 2 3 4 Total

Scenario A 42 37 39 26 144

Scenario B 46 41 45 39 171

Total 88 78 84 65 315

a

pour_hour work periods separated by 15-minute rest periods for

a total of 8 hours ’ work .

15 t

4

._

-*- _

_. ~—.. ~~~~- ‘

-

~-
50 50

Scenario B

Scenar i o B .

.

.

.

.

.

.

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. 

.

.

.

.

.

.

. 

I ::

. 

~~~~~~~~~~~~~~~~ 

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~~~~~~~~~/ 

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~~~~~~,m.J

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Scenario A

20 I I 20 i

1 2 3 4 1 2 3 4

Time period Time period

Figure 1. Correct detections for Figure 2. Correct detections for

Work/Rest Cycle I. Work/Rest Cycle H.

50 50

• Scenario A

Scenario B

.2 40 - *. 40 

_

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•_ •

•

•

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~~~~~~~~~~~~~~~~

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.

~~

~ 

30 . 30 

ScenarIo A 

~~

20 20 I

1 2 3 4 1 2 3 4

Time period Time period

Figure 3. Correct detections for Figure 4. Correct detections for

Work!Rest Cycle Ill. Work/Rest Cycle IV.

p

16

- - -

~~~~~~.--—~~~~-~~~~~~~~~~~~ — ~~

—~~~ -~~— —~~~~~~ — ~

— - ---~~~~ —~~-. — ——- a-— — 

~~~~~‘iTiii. ~~~~~~~~~~~~
90-

• Work/Rest Cycle II

/

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.

.

.

.

.

.

.

“ \ .

.

~~/

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Work/Rest Cycle Ill

70- ‘

V

Work/Rest Cycle IV

60 _________________________________________________________________

1 2 3 4

Time period

Figure 5. Total correct detections for each Work/Rest Cycle.

180

\ \ ,

. Work/Rest Cycles I & II

2 , \ .• \ / uuu - .

.

.

-

-

~ 

/

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N 

~~~~~~ 

Work/Rest Cyclesl&Ill

‘

\/ Work/Rest Cycles II & IV

~i 140 -

Work/Rest Cycles III & IV

120 I I I I

1 2 3 - 4

Time period

Figure 8. Total correct detections for Work/Rest Cycle pairs.

17

~

—. - 

_

~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 
Table 10

Trend Analysis for Correct Detections by Work/Rest Cycle

W/R Cycle Source df MSS F-ratio

Linear 1 2.8 0.2

Quadratic 1 0.3 0.0

Cubic 1 13.8 0.9

Within—cells 24 14.6

II Linear 1 4.2 0.5

Quadratic 1 2.0 0.2

Cubic 1 3.0 0.3

Within—cells 24 9.2

III Linear 1 22.5 1.8

Quadratic 1 8.0 0.7

Cubic 1 0.0 0.0

Within—cells 24 12.3

IV Linear 1 24. 8 4.0

Quadratic 1 2.5 0.4

Cubic 1 10.5 1.7

Within—cells 24 6.2

I + II Linear 1 6.9 0.6

Quadratic 1 1.9 0.2

Cubic 1 14.9 1.3

Within—cells 48 11.9

III + IV Linear 1 47.3 5.1*

Quadratic 1 9.8 1.1

Cubic 1 5.2 0.6

Within— cells 48 9.3

I + III Linear 1 4.8 0.4

Quadratic 1 2.6 0.2

Cubic 1 6.9 0.6

Within—cells 48 13.5

II + IV Linear 1 4.3 0.6

Quadratic 1 .02 0.0

Cubic 1 2.1 0.1

Within—cells 48 7.7

< .05 .

18

• . 

~

-• ~~~~
In addition to the trend analyses of the individual cycles, trend

analyses were conducted by combining the data of the cycles into the

following logical pairs : I and II. III and IV, I and III , and II and

IV. This procedure provides a more powerful test for trend by increasing the number of observations on which it is based. Figure 6 presents

the graph of overall performance for each cycle ~~~~~~~~~~ The corresponding

analysis and testing of trend components is given in Table 10.

From the F-tests indicated in Table 10, it can be seen that only

Work/Rest Cycles III and IV combined have a significant linear trend .

From Figure 6 , it is evident that this trend is negative, implying that

a degradation in performance occurs over the time periods .

As indicated in Figure 6, the downward trend of Cycles III and IV

is accentuated by the fact that they started noticeably higher than

Cycles I and II. It is possible that this initial high performance is

an artifact of the experimental procedure . This beginning spurt may

have been the result of a positive motivational reaction by the operators due to the realization that they would be finishing sooner than

operators on Cycles I and II. Perhaps even more likely , the operators

may have felt they were selected for the hardest job and were willing

to work harder because the operators knew they would be monitoring

4 straight hours without a break .

The data and trends of the Work/Rest Cycle results suggest that for

a contemplated 8 hours of monitoring, 2-hour work shifts interspersed

with 1—hour or 15—minute rest periods are preferred over 4—hour work

shifts interspersed with 1-hour or 15-minute rest periods.

As indicated in Table 5 , the Days variable is nonsignificant.

This outcome indicates that any fatigue , learning, or boredom effec ts

from the first day ’s testing were not carried over to the second day ’s

testing.

The String—Size variable is significant at the .01 level. Out of

24 possible detections the average operator could have made in 1 day

for each string size, the 2—sensor strings resulted in 9.1 detections,

a significantly lower figure than the 15 .4 detections for the 3-sensor

strings and the 15.1 detections for the 4-sensor strings . At least two

factors could account for this result: The orientation of the USAI~S

places less emphasis on 2—sensor interpretation during training , and

the targets in the 2-sensor string condition could be more difficult

than those in the 3- and 4-sensor string condition because they included

more personnel targets.

The Noise variable was nonsignificant, indicating that the highnoise level had no effect on detection performance . The low-noise

-— scenario sections resulted in 40 correct detections , as compared to 39

in the high-noise scenario sections .

19

—

--—— .

~

- ••

~~~~~~~ - ~~~~~~~~~~~~~~~~~~~~~~~~~ -
The Target Activity variable is significant at the .01 level. The

low-target-activity condition resulted in an average 29.2 correct detections (out of a possible 48 for both scenarios) ; the high-target—activity condition had an average 49.7 correct detections (out of a possible

96 for both scenarios) . The high-target-activity condition , however,

contained twice as many targets as the low-target—activity condition .

A statistical tes t of completeness (correct detections divided by total

targets presented) resulted in a significant difference (t = 6.31,

df = 15, p < .01). This outcome shows that the low—activity condition

resulted in significantly higher completeness (61% versus 52%).

The Groups variable is significant at the .01 level. The operators

in the eight groups were selected to minimize within—subjects variability for the purpose of increasing the power of the statistical test.

The inclusion of a main effec t for groups permitted this source of

variability to be subtracted out of the error term , thus increasing

the power of the statistical tests for other main effects .

The Scenario variable is significant at the .05 level . On the

average , operators detected 37.9 targets on Scenario A and 41 targets

on Scenario B (out of a possible 72 for each scenario) . As with the

Groups variable, control of this variable was necessary to increase the

sensitivity of the statistical analysis and eliminate confounding .

• The differences in the low- and high-target-activity conditions

by scenario are shown in Table 11. The significant interaction between

scenario and target activity indicates noticeably lower performance

(22.6) in the high— target—activity condition of Scenario A than in the

high-target—activity condition of Scenario B (27). The data in Table 11

also suggest that the difference in completeness between the high and

low activity conditions occurred mainly in Scenario A.

Table 11

Mean Number of Correct Detections and Completeness

by Targe t Activity and Scenario

Scenario A Scenario B Sum

Low—Target Activity 15.3 (64%) 13.9 (58%) 29.2

High—Targe t Activity 22.6 (47%) 27.0 (57%) 49.7

Average 19.0 20.5

20

___ ___ ______ -- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 

~~~~~i.
The target activity by days interaction (Table 12) is significant

at the .05 level. The cause of this interaction is difficult to identify because there is a decrement in perfo rmance for the low-targetactivity condition .

Table 12

Mean Number of Correct Detections

by Target Activity and Days

Day Low Targe t High Target Sum

Day 1 15.3 24.1 39.4

Day 2 13.8 25.7 39.5

Average 14.6 24.9

The string size by target activity interaction presented in

Table 13 is significant at the .01 level. This interaction is due to

the substantially fewer correct detections in the high activity, 2-sensor

string condition than in the 3- and 4-sensor string conditions. Equally

informative is the completeness score of 26% , which is far below all

other string-size and target activity level combinations shown in the

table . This result suggests that 2—sensor strings could be used in

areas where target activity is expected to be low with no loss in per—

forinance and with a reduction in system costs .

Table 13

Mean Number of Correct Detections and Completeness

by Target Activity and String Size

2-sensor 3—sensor 4-sensor Sum

Low—Target Activity 9.8 (61%) 10.4 (65%) 8.9 (56%) 29.1

nigh—Target Activity 8.3 (26%) 20.3 (63%) 21.2 (66%) 49.8

Average 9.1 15.4 15.1

21

-—--=-— .

~ ~~~~~~~~~~~~~ 

- 

~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~ i

~~~~~—t “-

-. 

-—~~~~~~~~~~ *“-- .~~ . -
The string size by scenario interaction (Table 14) was significant

at the .01 level, indicating tha t the number of correct detections using

2-sensor, 3—serAsor , and 4—sensor string sizes differed , depending upon

whether the scenario was A or B.

Table 14

Mean Number of Correct Detections by Scenario and String Size

2—sensor 3—sensor 4—sensor Sum

Scenario A 7.7 16.3 14.1 38.1

Scenario B 10.4 14.5 16.1 41.0

Average 9.1 15.3 15.1

The three—way interaction of string size by target activity by

scenario was significant at the .01 level. The raw scores and completeness values are shown in Table 15. Notice the exceptionally poor perforinance for both scenarios in the 2—sensor , high—target—activity

condition .

Table 15

Mean Number of Correct Detections by String Size,

Target Activity , and Scenario

Low-Target Activity nigh-Target Activity

String size Scenario A Scenario B Scenario A Scenario B

2—sensor 3.9 (48%) 5.9 (73%) 3.7 (23%) 4.6 (28%)

3—sensor 5.8 (73%) 4.6 (58%) 10.4 (65%) 9.9 (62%)

4—sensor 5.7 (70%) 3.4 (42%) 8.5 (53%) 12.7 (79%)

22

—-— 

-

-

~~~~ .—- —— - —.- — --.—- — -- - —- 

. ~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~ -
The remaining interactions in Table 15 were all nonsignificant and

are not discussed. Higher order interactions (i.e., beyond three-way

interactions) were not analyzed because they would serve no useful purpose in this study .

False Alarms

Of particular interest to the present problem is the small number

of false alarms reported by the operators. Only 11 false alarms were

reported across both days of testing, a number insufficient for statistical analysis and relatively unimportant operationally . Also , the

false alarms were distributed in a random fashion across 10 operators ,

who achieved a very high target reporting accuracy (better than 95%).

Correct Identifications

Table 16 presents the analysis of variance results for correct

identifications. The Work/Rest Cycle variable was nonsignificant, as

with coriect detections . The same analyses were used to assess trends

in correct identifications as in assessment of trends in correct

detections.

Tables 17 to 20 present the correct identification data by work!

rest scenario and time period. Figures 7 to 12 indicate that large

fluctuations are apparent, both between the two scenarios and also in

a comparison of one W/R cycle with another. Figure 11 indicates the

overall trends in each of the four work/rest cycles for both scenarios

combined. Cycles I and II showed no overall improvement or loss in performance across the four time periods . A trend analysis (Table 21) of

these data detected no significant trends.

In contrast to the curves for Cycles I and II in Figure 11, the

curves for Cycles III and IV present a downward trend . The trend analyses

conducted across the four time periods for these data show a significant

cubic trend only for Cycle IV . The practical portion of this cubic trend

is the rapid decline in operator performance from period 3 to period 4

from a performance plateau across periods 1, 2, and 3.

Thend analyses conducted on pairs of the work/rest data are reported in Table 21. From the F—tests shown, it can be seen that Cycles

III and IV combined resulted in a significant linear trend. This result

parallels the decrease over tine periods found for correct detections.

The Days variable was nonsignificant (Table 16). As with detection

performance, Day 2 identification performance was not affected by Day 1

test activity .

23

-
Table 16

Analysis of Variance Table for Target Identification

Source of variation df SS MSS F

Work/rest cycles 3 .864 .288 .257

Days 1 .666 .666 .595

String size 2 163.734 81.867 73.160*

Noise 1 2.041 2.041 1.823

Target activity 1 219.010 210.010 195 . 719*

Groups 6 107.875 17.979 16 .067*

Scenarios 1 7.593 7.593 6.786*

Days x string size 2 1.286 .643 .574

Days x noise 1 .843 .843 .753

Days x target activity 1 4.166 4.166 3.723

String size x noise 2 .223 .111 .99

String size x target activity 2 186.098 93.049 83.153*

String size x scenarios 2 14.828 7.414 6.625*

Noise x target activity 1 3.375 3.375 3.016

Noise x scenarios 1 1.041 1.041 .930

Target activity x scenarios 1 31.510 31.510 28.159*

Days x string size x noise 2 5.171 2.585 2.310

Days x string size x target

activity 2 6.317 3.158 2.822

Days x noise x target activity 1 .843 .843 .753

String size x noise x target

activity 2 1.421 .710 .634

String size x noise x scenarios 2 .255 .127 .113

String size x target activity

x scenarios - 2 20.067 10.033 8.966*

Noise x target activity x scenarios 1 .374 .374 .334

Residual 151 3352.555 22.202 19.841*

Error 192 215.000 1.119

Total 383 4347.156

< .01.

24

.—

~~ -

--~~~~~

— 

- ~~~~ ~~ ., • - - ~~~~~~Th-

~~~~~~~~~~~~~~~~~~~ T~~
Table 17

Correct Identifications for Work/Rest Cycle I (2~ 1) a

2-hour

periods 1 2 3 4 Total

Scenario A 28 35 24 31 118

Scenario B 31 37 27 37 132

Total 59 72 51 68 250

a

~~ o_hour work periods separated by 1—hour rest periods for a

total of 8 hours of work .

Table 18

Correct Identifications for Work/Rest Cycle II (2-1/4)

2-hour

periods 1 2 3 4 Total

Scenario A 29 27 27 34 117

Scenario B 32 32 31 28 123

Total 61 59 58 62 240

25 I

— —~~~

-
Table 19

Correct Identifications for Work/Rest Cycle III (4—1)

2-hour

periods 1 2 3 4 Total

Scenario A 37 34 33 31 135

Scenario B 30 30 32 21 113

Total 67 64 65 52 248

Table 20

Correct Identifications for Work/Rest Cycle IV (4-1/4 )

2-hour

periods 1 2 3 4 Total

Scenario A 26 25 23 18 92

Scenario B 42 37 40 29 148

Total 68 62 63 47 240

____ — - - 

26
50 50

~

0 U, C

C 0

.9 Cs

o 4 0 - .2

,.

~

Scenario B /

‘

:: ________________ _________________

Time period Time period

Figure 7. Correct identifications Figure 8. Correct identifications

for Work/Rest Cycle I. for Work/Rest Cycle II.

5C 42 -.

•

Scenario B \ U)

C C

o .2

~~40 ~~3 2 - .

.

.

.

Scenario A

g 30 ~~~~~~~~~~~~~~~~~~~~ g22 -

Scenario A

20 i 12 ______________________________________

1 2 3 4 1 2 3 4

Time period Time period

Figure 9. Correct identifications Figure 10. Correct identifications

for Work/Rest Cycle Ill, for Work/Rest Cycle IV.

27

4

~~~~~~ 

— --.--

- - - 

___

~~~~ _

,—L: .,— 

- -
80

70- ,

. \

I Work/Rest Cycle

60 - 

Work/Rest Cycle

\

\ / Work/Rest Cycle

~ 50- V ~

~ Work/Rest Cycle

IV

40 I I

1 2 3 4

Time period

FIgure 11 . Total correct identificatio n for each Work/Rest Cycle.

140

—

.-• .— •\ ‘

. 1Work!Rest Cyc l es

l &li

,~~~ 120 - 

~~~~~.

.

.

“

. 

7——Work /Rest Cycles

~~~~~~~~~~~~~~~ ,

.

-

~~

Work/R est Cycies

100 Work/Rest Cycles

lil &Iv

0

80— 1 1 I I

1 2 3 4

Time period

Figure 12. Total correct identification for each Work/Rest Cycle.

28

_____ _____ ___________ ______

- - -. ~~~~~~~~~~~~~~~ ~~~~~ 

-
Table 21

Trend Ana1y~ 1s f or Each Work/Rest Cycle Identification S~ nr.-

Work/Rest

Cycle Source df MSS F-ratio

I Linear 1 0.2 0.2

Quadratic 1 0.5 0. 1)

Cubic 1 32.4 2.’~ Within—cells 24 12 .4

II Linear 1 0.0 0.0

Quadratic 1 1.1 0.1

Cubic 1 4.6 0.5

Within—cells 4 9.5

III Linear 1 12.1 1.4

Quadratic 1 3.1 0.4

Cubic 1 2.0 0.2

Within—cells 24 8.4

IV Linear 1 24.0 3.3

Quadratic 1 3.1 0.4

Cubic 1 36.1 49*

Within—cells 24 7.3

I + II Linear 1 39.2 3.7

Quadratic 1 4.5 0.4

Cubic 1 2.3 0.2

Within—cells 24 11.0

III + IV Linear 1 35.1 45*

Quadratic 1 6.3 0.8

Cubic 1 5.5 0.7

Within—cells 24 7 .8

I + III Linear 1 4.5 0.4

Quadratic 1 0.6 0.1

Cubic 1 9.1 0.8

Within—cells 48 10.4

II + IV Linear 1 11.3 1.3

Quadratic 1 0.3 .0

-j Cubic 1 1.3 0.1

Within—cells 48 8.4

.4 *p < .05.

.

/ 29

p.;
The String-size variable was significant at the .01 level. Of

the 24 targets for each of the three string sizes, an average of 7 were

correctly identified for the 2-sensor strings , 12 for the 3—sensor

strings, and 12 for the 4—sensor strings. This result, however, was due

to the fewer targets detected with 2—sensor strings. Of the total number

of targets detected with the 2-sensor strings , 72% were identified ; of

the total detected by 4—s~~sor strings , 81% were identified. These

latter results may inci~~.Lt. t~ at. ttring size was not a factor in determining whether the target wa~ vehic’.ilar or personnel.

The remaining identification results in Table 16 are similar to

th~ detection results in Table 5. Of the main effects, the Scenario,

Group , and Target Activity variables were signi ficant at the .01 level,

whereas Days and Noise were not. For the Target Activity variables,

the identification completeness values (taking intc consideration the

unequal number of targets in each of the activity conditions) were also

significant (t = 2.73, df = 15, p < .02), the low—activity condition

having the hi gher mean.

Nost of the significant interactions in the detecti n analysis

were also significant in this analysis : string size x target activity ,

string size x scenario target activity . The significant residual means

that one or more of the higher level interactions (i.e., beyond the

three—way interactions) were significant but were not considered important to the objectives of the study . All of the remaining interactions

are nonsignificant . Table 22 presents the confidence and elapsed tine

results broken down by W/R cycle, operator , and day . Tests of statistical significance for confidence were not conducted for several reasons .

Posttest interviews revealed that some operators were not giving confidence with respect to the target detection as instructed, but with

respect to the entire target report , including speed and length of the

column . Of more importance, the absence of false alarms prevented an

analysis of the variable, average confidence in correct detection minus

average confidence in false alarms.

During the testing, irregularities were noticed with regard to the

operators’ handling of the variable, Elapsed Time. On many occasions it

was observed that some operators were not reporting the clock time when

they first detected a target as instructed but at some time during the

target analysis. Even though frequent reminders were given, some operators would begin filling out the target information sheet without recording the time at which they had detected the target, or they would

record the time only after they were positive that they had detected a

valid target, usually long past the time of detection. The elapsed

time data, therefore, contains considerable error variation, and for

this reason a statistical analysis of this variable was not conducted .

30

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~ w “~ -— I-I H H

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31 - . -

S 

-:—-

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-

- - ~~~~~~~~~~~~~~~~~~~ - -
Error Analysis

During the test procedure it became apparent that almost half of

the operators were having difficulty in using the column—length formula

(Appendix B) and interpretinq its results . This formula is used to determine target speed , length of column , and n umbe r of targets, three important types of information for target acquisition and intelligence

estimates .

During posttest interviews, it was discovered that the opera tors

were rejecting target detections if calculations of the column—length

formula yielded negative answers or zero. Theoretically , these answers

are impossible if a valid target is involved . However, they are completely reasonable in the real world considering the inaccuracies that

could exist in the formula substitution values and the errors that can

be made by an operator .

In the case of inaccuracies existing in the real world , an opera tor

may be confron ted with inaccurate sensor detection range s, incorrect

distances between sensors , wrong sensor types , and other inconsistencies.

Some of these errors we re present in the data given to the operators.

The operators , however , were accustomed to working with more clear—cut ,

easily solved problems and tended to reject targets and target calculations that did not compute and yield expected answers .

In the case of errors tha t can be made by an operator , data analysis of the target log information revealed the following errors directly

connected with the column—length formula:

1. Incorrect placement of the endpoints of sensor activation

patterns for measuring TT1 and TN (time estimates) .

2. Inaccurate estimations of ‘i”r1 and TM measurements even if

the activations endpoints are not ambiguous .

3. Arithmetic errors in multiplication, division, and decimal

point placement.

4. Con fusion in computing the detection range (DR) value and in

deciding what arithmetic function to use with it.

It was also discovered during data analysis that the nonseismic

sensors (Electromagnetic Intrusion Detector (EMID) , Magnetic Intrusion

Detector (MAGI D), and Directional Infrared Intrusion Detector (DIRID ))

were not optimally used , especially when the column—lenqth formula

failed to work . For example , when sensor strings resulted in zero or

negative number after computation of the column-length formula , the

activation pattern was discarded as a true target instead of the nonseismic or confirmatory sensor being analyzed for the target information .

32

~~-
CONCLUSIONS AND RECOMMENDATIONS

Summary of Resul ts

Correct Detections. Independently considered , none of the four

work/rest cycles investigated showed any statistically significant advantage in operator detection performance.

When analyzed together, the two 4—hour work shifts (W/R III and IV ,

with rest periods of 1 hour and 15 minutes , respectively) resulted in a

significant linear trend toward detection performance deterioration .

When analyzed together , the two 2-hour work shifts (W/R I and II

with three rest periods of 1 hour or 15 minutes respectively) did not

result in any significant changes in performance .

Time effects resulting from Day 1 testing had no appreciable effect on Day 2 performance .

The “battle noise ” activations in the high-noise condition did not

affect monitor performance when compared with the low—noise condition .

This is interpreted to mean tha t the Army operators are receiving at

least sufficient training in differentiating “noise” activations from

“target” activations .

Detection completeness was significantly lower in the high—targetactivity condition than in the low—target—activity condition when 2-sensor

strings were used. This is a definite source of operator error.

False Alarms. The number of false alarms was negligible. The

subjects showed hi gh target reporting accuracy (in excess of 95%) but

at the expense of relatively low completeness of target reporting (55%) .

Correct Identification. Independently considered , only Cycle IV

(4 hours work , 15 minutes rest, 4 hours work) showed any statistically

significant trend. Cycle IV resulted in an increasing decline in operator performance over time .

When analyzed together, the two 4—hour work shifts (Cycles III

and IV) showed a significant linear decline in performance.

Approximately four out of every five targets detected were identified correctly . The remaining targets were not identified correctly

because of various operator errors, including inaccurate measurement of

the target activation patterns and errors in arithmetic in the use of

the column-length formula.

Time effects resulting from Day 1 testing had no appreciable effect on Day 2 performance .

The high-noise condition did not affect operator performance.

33

- - -

~~ -~~~~~~~~ — S - - - - - . __________________
Operator identification completeness under the high—activity level

was signi ficantly lowe r when a 2—sensor string was used than when the

3— and 4-sensor strings were used . This is a definite source of operator error but is largely attributable to the poorer detection rate

found when 2—sensor strings were used .

Co1umn—Len~ th Formula. The column-length formula provides an estimated target speed and length—of-column measurement and is typically

computed for each detection that the operator feels is a valid target.

In the process of determining why some targets were not detected , were

detected but later scratched out , or were detected but incorrectly

identified, the following operator procedural and arithmetic errors

were noted :

1. Incorrect placement of the endpoints of sensor activation

patterns for measuring TT1 and T

M .

2. Inaccurate estimations of ~~ l and TM measurements even if the

activation endpoints are not ambiguous.

3. Arithmetic error in multiplication , division, and decimal

point placement.

4. Confusion in computing the combined detection range (COR)

value and in deciding what arithmetic function to use with it.

5. Seismic and confirmatory sensors--EMID , MAGID , and DIRI D we re

not used to full advantage .

Recommendations for Operational Application

1. For monitoring schedules ove r extended periods of time , 2-hour

work shifts interspersed with 1—hour or 15-minute rest periods are to

be preferred over 4—hour work shifts interspersed with 1-hour or 15—minute

rest periods. The size of the rest periods did not seem to have an

appreciable impact on operator performance.

2. The use of 2—sensor strings is advantageous from the convenience and cost factor point of view and results in no decrement in performance if target activity is low (3 targets per 30 minutes) and sensors

are reliable . Use of 2—sensor strings in an operational situation should

be considered, dependent on local conditions .

3. For operations similar to those in this study, use of 3—sensor

strings results in the same operator performance as use of 4-sensor

• strings.

4. Scenario differences must be controlled for testing and research

in this area .

34

i

— -

~~~— -- 

.

- 

- -:

~~~~iTi~.
Training Recommendations

1. Training programs should be oriented toward improving operator

performance in areas found to be deficient in this investigation . The

major sources of operator error were (1) detection and identification

performance of those targets associated with 2-sensor strings in hightarget-activity conditions, (2) column—length formula calculations,

and (3) utilization of nonseisinic and confirmatory sensors.

2. To perform accurate time measurements directly from the ~~ 376

tactical data, it would be advantageous to develop a small , easily used

ruler accurate to 0.1 minute. To perform arithmetic calculations and

decimal point placement, it would be advantageous to develop a job aid

in the form of a nomograph .

3. The present-day training for target detection during “battle

noise ” conditions should be continued .

Si
REFERENCES

Cravens , M. N. Human Factors Evaluation of the Terminal Message Processor

(TMP). Sandia Laboratories , July 1972. (Specified distribution only.)

Martinek , H., Hilligoss , R. E., & Lav icka , F. Comparison of Three Display Devices for Unattended Ground Sensors. ARI Technical paper

299, August 1978.

U.S. Army Armored Cavalry Troop Test Report , HQ, Mode rn Army Selected

Systems Test and Evaluation (MASSTER) at Fort Hood , Tex., Vol. II,

January 1972.

U.S. Army . Operational and Tactical Concepts for Employment of Unattended Ground Sensors , February 1971. U.S. Army Combat Surveillance and Electronic Warfare School , Fort Huachuca , Ariz.,

ST-30—20—2 , February 1971.

U.S. Army . Program of Instruction for l7M20 Unattended Ground Sensor

Specialist Course and Unattended Ground Sensor Mair .tenance. Draft ,

November 1972.

U.S. Army . Interpretation and Analysis Text for Unattended Ground Sensors. U.S. Army Combat Surveillance and Electronic Warfare School ,

Fort Huachuca , Ariz ., 1973.

Project MASSTER ’s “Guide for Extnployment of Unattended Ground Sensors, ”

Fort Hood , Tex., December 1970.

U.S. Army . Unattended Ground Sensor Devices. U.S . Army Combat Surveillance and Electronic Warfare School , Fort Huachuca , Ariz., revised , September 1971. 3T-30—20—l .

U.S. Army . DCPG Phase III Field Experiment Report of the Battle Area

Surveillance System (BASS III) , December 1970, Project MASSTER .

U.S. Army . UGS Experimentation Test Plan (Project 1030) Report. Deputy

Commanding General (DCG) , Project MASSTER , May 1972.

U.S. Army. Operator and Organization Maintenance Manual for Recorder,

Signal Data RO 376/UGQ Resdel Model No. 91662-1, DAABO7-60—0l95,

June 1969.

West, H. W . Effects of Environment on Microseismic Wave Propagation

Characteristics in Support of SID Testing at Fort Bragg, N.C.

Technical Report N-73-2, June 1973.

Winer, B. J. Statistical Principles in Experimental Design . 2nd Ed.

New York: McGraw—Hill , 1962.
APPENDI X A

DEVELOPMENT OF TifE SCENARIOS

The development of two realistic and equivalent pe rformance measures

(Scenarios A and B) was accomplished in a series of phases. Each phase

was followed by reevaluation and revision .

The initial phase of development consisted of review of pertinent

literature, and detailed studies of all BASS III and UGS 1030 field data.

Target activations from this field data were used in the scenarios. Emphasis was placed on the requirements of the Target—Dependent Independent

vari~’b1es .

Additional detailed suzmnary tables containing all relevant information found in the field data were constructed. These tables included

information on sensor type , sensor configuration, radio frequency, sensor

ID number, target type, number of targets, field study number, troop

scenario number, field run number, dates, times , amounts of noise, and

jud ged dif ficulty levels (subjectively determined) of the target

activations.

Recordings of activations and records of target activity of two

MASSTER field tests were available . Field test UGS 1030 involved wheeled

and tracked vehicles as targets in groups of from 1 to 9 traveling at

different predetermined speeds. BASS III involved personnel as targets

in groups of 1 to 20. All target groups traveled on predetermined paths

according to a time schedule .

Both the BASS III and UGS 1030 field data had been collected on

eight radio frequencies (RF). It was necessary to select 2 RE’s from

each of the studies because of electronic recording constraints . Those

which were selected ( 790 and 1,690 from BASS III and 190 and 1, 150 from

UGS 1030) contained the greatest amount of usable data. The data from

these four frequencies we re further analyzed in an attempt to determine

which specific sensor ID and sensor strings provided the largest amount

of quality data. A total of 60 sensor ID’s were chosen to be used in

the scenarios.

With the usable data then reduced to 4 frequencies and 60 ID’s,

the specific targets were selected . The criteria applied to target

selection were the following :

1. Activations involving strings composed of 2, 3, or 4 sensors

2. Activations within a 30—minute segment covering a range of

difficulty

-

- ~~~~~~~~~~~~ 5—
3. Balance between number of vehicular and personnel targets

4. -The presence of at least a minima l amoun t of staircase natterning in each target.

I

I .

-

40

- - -

~~~~~~~~~~~~~ 

—— 7 — . -—

~~~~~~~~~~~~ - ~~

-— - - - —--

~~~~

- 

~~~~~~~~~~~~~~~~~~~~ 

- 

— —

~~

-

~~~~

-

~~ 

-
APPENDIX B

OPERATOR INSTRUCTIONS

A. Test Procedure Training

Before the operators entered the testing room the following preparations were made :

1. Placed two tables and four chairs in each corner of the test

room with two X-T event recorders on each table .

2. Checked to see that the event recorders were in proper running

condition . Checked recorde r operation when driven by a master

recorde r or independently.

3. Loaded pretest tape into each event processor and checked

operation when carriage was lif ted out.

MONITOR : Read the following instructions (15 minutes):

As you already know , you have been selected to participate in a research effort to study tJGS performance under various conditions as they

might exist in the field . We have been contracted by the Department of

the Army and this school to administer this exercise to you , to collect

performance data , to analyze the results, and to submi t a report. I

want to maice it clear at the outset that our objective is not to isolate

each of you and attach a proficiency score to each of you . Our objective

is to determine the total capability of the UGS information potential as

it combines both the man (you) and the machine output (the UGS record) .

Howeve r, part of your performance will be scored and given to the school

for its use .

To summarize the entire exercise , you will be given tJGS sensor

records (XT plots) to interpret. These plots, for the most part , are

target activations that have been collected under various field exercises

primarily in the Fort Hood area. Involved in these exercises were varying numbers of tanks, APCs , and personnel. These tests also contain

noise activations which are typical of wartime operation, such as fixedwing and helicopter activity, malfunctioning and unreliable sensors ,

radio interference, weather/wind activity, and artillery—shell bursts.

All we ask is that you interpret the X-T plots to the best of your

ability and try to make sense out of what sometimes might appear to

you to be rather difficult. Let me stress that we have tried to make

these records as realistic as we could.

You will interpret these X—T plots under periods of work and rest

similar to those under battlefield conditions. You will probably become

41 - 

—

__ - 

~~~~~~~~~~~~~~~~~~~~~~~~~~~
tired and fatigued because of the workload. However , in wartime it

mi ght be a lot worse . You wouldn ’t slow down then because your life

might depend on how well you do your job . There is a great need for

the Army to find out how typical UGS specialists will be able to function under battlefield conditions. The results of this test should

give them an idea.

You are important because you , as a group , represent the hundreds

of specialists who have graduated and will graduate from the UGS School

for a lon g time to come . Army deployment plans for UGS equipment and

personnel will be partly influenced by what ~~~~ can do under various

workload conditions.

Since we will be repeating this exercise with other UGS operators,

I will read the instructions to you so that all groups will get the

same information. However, you may ask questions at any time .

At this time we will pass out the test packets which contain all

the materials you will need today. Take out all the materials carefully. The first sheet should be a questionnaire . Complete this

questionnaire at this time. Feel free to ask questions .

t4JNITOR: Pass out packets and administer and collect questionnaires

(10 minutes). Discuss Target Log Sheet (30 minutes).

The next sheet should be a TARGET LOG (see Table B-i). On this

sheet you will record most of the target information you would regularly record on a SENSOR ACTIVATION SPOT REPORT plus additional information. Note the first column of the target log. This is the pattern

log number. For activation patterns on the chart paper that you think

are targets we want you to circle the target on the chart paper and number it. Record the number in the first column . Each target that you

detect always number and re cord on your target log. If you de tect a

target but later feel it is not a target do not erase what you have

written but simply write “No Target” and start recording the next target on the space below . Number all your targets consecutively in

sequence .

In column 2 record the clock time that you made a target detection

and round it off to the nearest minute . You can use your wristwatch

but be sure it is synchronized with the wall clock.

In column 3 record the pen numbers of the sensor string.

In column 4 record how confident you are that what you think is

a target really is a target. Use the terms of confidence that are shown

at the bottom of the target log sheet: positive, high, 50/50, and low .

Tell us how confident you are that the activation pattern you are looking at really is a target. Assuming that you will be sending this in- 4

formation to your company commander during a battle situation . He knows

you are doing your best but he wants to know how confident ~~~ are in

42

4 — -- -- —‘—

~~~~~~~~~ 

— -

~~~~~~~

--
V

o ~~~~~~~ ,-4 Q ...4 O s _4 ..4-.4

4.i

5 

‘-4 a)

-4

—

II ‘-4

o 0

4-

,

a)

N ~~

‘-4 

~

,

I4

~~~~~~

a)a

-4

0)5 

0 In ~~o In

0 4) 

0 ______ ____ ____ ____ ____ ____ ____ ____ ____ ____ In . 4 5

“.4

.5

U)

I•I -.4 0) 4) m -

~~ U)

4’S 

5 4.)

(‘4 ~~~~C) 4’ U S

0 4’

S

55 -4

43

- -

-~~~~~~~~~~~~~ - 

— 

-~~~
the information you are sending to him. If are not confident in your

information then he will place a higher weight on the information being

supplied to him by other intelligence sources such as real-time IR r’connaissance , radar, or electronic intelligence . The confidence estimate

should relate only to your detection of a target and not necessarily to

any of the following information .

In column 5 record the direction of movement of the target. Use

the terms NW , NE, SW, and SE.

In column 6 compute the speed of the target using the formula ,

Speed (S) D/TM

where D = distance between sensors

mean time of activations from center of the first sensor

activation to the center of the second sensor pattern .

Show your calculations for speed in the space provided. Round off your

speed to the nearest meters/minutes.

In column 7 record the target type whether personnel or vehicular.

If the speed is less than 150 meters/minutes , call the target “personnel”

and write P. If the target is greater thar, 150 r,eters/minutes call the

target “vehicles” and write V.

In column 8 compute the length of the target column using the

formula ,

L

C = S (TT 1) -

where S = speed calculated and recorded in column 6

= total time the first sensor was activated

DR = detection range which is the detection radius of the

first sensor the detection radius of the second

sensor added. In this test the detection radius of all

sensors in a string is the same .

Substitute the values in the formula in the spaces provided and show your

work . Do your actual multiplication on scratch paper. Round off your

numbers where appropriate .

MONITOR: Find out what they have been taugh t in UGS schoo l for rounding

numbers .

• In column 9 record the quantity or number of units in the target.

-— If the target is personnel , divide the length of the column by 5 meters

to determine the number of personnel. If the target is vehicles , divide

the length of the column by 50 meters to determine the number of vehicles.

44

— 

--________ -

~~~~ 

.- — 

- 

. 

~~~~~~~~~ ~~~~~~~~~~
In column 10 record the clock time in which you are finished with

the target and are ready to send the information to your company

commander.

The sequence of the information requ ired on the tarqet leg was

planned and we want you to try to use this sequence . Does anyone have

arv reservations about this sequence? If another sequence works better

for y.i U let us know so everyone can try it .

MONITOR: Discuss the Implant Sketch (Field I). (10 minutes)

Remove your target log and place it aside . The next sheet should

be an implant sketch (see Figure B-l) wh ich is marked on the upper

right-hand side Pretest , Part I. As you know , implant sketches show

the location of the sensor strings.

During the next couple of days, you will be using implant sketches

very similar to this one . The implant sketches will show the location

of the sensors along the roads and trails , give the pen number for each

sensor , the string number, and the distance between the sensors .

As you can see , the spatial relationships between the sensors are

not drawn to scale. This is the case with all the implant sketches you

will be given during this entire exercise . The purpose of this implant

sketch is merely to present you with the information that you will need.

There will also be times in which you may disagree as to the placement

of the sensor strings in the various deployment patterns. Although

certain string deployments may differ from what you feel or have been

taught, accept the deployments presented, keeping in mind that in operational situations there are many factors involved in deploying sensors .

The sensor string deployments are the ones used in the Fort Hood tests

and are adequate for purposes of this exercise.

The imp .ant sketches will also provide you with information as to

whether the string contains a MAGID, ACOUSID , EMI D , or DIRID sensor.

In this implant sketch (Pretest , Field I) there are three MAGIDs.

MONITOR : Discuss the Sensor Program Record.

Put the implant sketch aside . The next sheet should be a SENSOR

PROGRAM RECORD (see Table B-2). This sheet provides the string number

and field designation, sensor type and detection ranges of the various

sensors . It contains four sections to provide this information for four

different sensor fields . On this sheet three sensor fields are shown :

I, II , and III. Ri ght now we will be concerned with only the first sensor field labeled roman numeral I. The sensor record or readout sheets

you are probably using to work with contain a great deal more information including geographical coordinates , sensor ID, sensor frequency ,

45 

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mode, and inhibit times . The ones we will work with are simplified for

purposes of this exercise .

Notice that for detection radius, a value is given for vehicles and

for personnel. Detection radius varies creatly for vehicles and personnel depending upon the sensor type , soil type , and gain setting. The

detection radius of the first two sensors of every string will always

be given since you will always determine the time between the midpoints

of the first two activations in a string used to determine target speed.

MONITOR: Administer Pretest, Part I.

Place your target log, implant sketch , and sensor record in a conven ient place near your event processor which is already loaded wi th

our X-T chart paper. Put your packet aside . We will work through a

30—minute practical exercise , in which we will use the materials we have

just discussed . Fill out your target log and use your implant sketch and

sensor record. Please do not write on the implant sketches or the sensor

record. As you detect patterns that you think are targets , circle the

pattern on the chart with your pencil and place the number of the target

next to the circle. Then fill out your target log by first recording

this numbe r in column 1. Are you ready? Start monitoring.

MONITOR: Turn on Event Processors.

Check each man to be sure he is working with proper materials. When

the first group of noise activations has completely appeared , find ou t

if anyone called them targets . When the first, second , and third targets have each appeared (in different time frames) find out who did not

detect them as targets and assist these people . For the first target,

work out the calculations on the blackboard if necessary . Find out how

this class is performing and give assistance individually or for the

entire class as required. Emphasize aspects of the procedure that are

not being performed. Check each man to be sure he is properly filling

in all the information blanks on the target log.

At the end of the 30—minute period turn off the event processors

no more than one—half inch above the line separating the 30-minute

periods and review procedures where appropriate.

MONITOR : Read the Following:

During the next several days , you will be monitoring various

30—minute chart preparations . After each 30-minute period you will use

a new implant sketch. We will begin the next 30—minute period shortly .

Get your packets and take out the implant sketch marked Pretest, Part II ,

in the upper right-hand corner. Do you have any questions concerning

/

48

S

—-—.4—-- - — -: ——---— - --—— —- 

— - r

~~~~~~~~

-- 

~~~~~~~~~~~~~~~~~~~ - —~~--~~ —-- .
— r

this one? Remember, you are numbering your targets consecutively in

sequence so if you need additional target loas let us know and we will

supply them. Again , do not write on the implant sketches or the sensor

record sheets. Se sure you are working with the appropriate sensor

record. For the next 30-minute segment you will be working with the

sensor record, labeled Pretest II. Are there any questions before we

begin the next 30-minute segment? All right , we will now start.

MONITOR: Turn the Equipment on and Administer Pretest, Part II.

Conduct Pretest, Part II , in a manner similar to Part I , with somewhat less involvement of the monitors during the test. Check what procedural problems are still occurring. At the end of the 30 minutes , turn

off the equipment not more than one-half inch below the line indicating

the next 30—minute segment. Address the entire class on procedural

problems and reiterate where necessary .

MONITOR : Read the Following:

The next 30—minute segment, Pretest, Part III , will be the last

one this afternoon. Get your packet and take out the implant sketch

ma rk ed Pretest, Part III , and place your old one at the rear of the

• event processor . Do you have any questions concerning this new implant

sketch? Take your sensor record and if you desire , place a piece of

paper over sensor field II so you will not confuse it with the next sensor field which is roman numeral III. You may write on the target log,

but do not write on the implant sketch and sensor record sheets. During

this next 30-minute period we will let you work quietly and discuss any

problems afterwards . If you are going to use your wristwatch , synchronize it with the wall clock . Are there any questions before we

begin? All right , we will start now.

MONITOR: Turn the Equipment on and Administer Pretest, Part III.

Since the results of this 30—minute segment will be used as the

basis for subject placement into homogeneous groups, there should be

little or no interplay between personnel. At the end of this segment

ask the subjects to roll up their chart paper, tape it, and place it

on top of the event processor. Revi ew any final procedural problems.

MONITOR: Read the Following:

Thank you for your cooperation today . Today’s activities were

geared to teaching you the procedures that will be used during the next

2 days. You will be monitoring 30-minute segments tomorrow but we will

not stop you after each one as we did today. You will continue to work

49

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~

- - - 

~~~

-

_____
through the 30-minute segments for different periods of time and you

will receive a different implant sketch for each 30—minute segment .

The implant sketches you will be working with during the next 2 days

are similar to the ones you worked with today.

Tomorrow , you will be interpreting UGS tapes during different

periods of work and rest. Some of you will be working longer tomorrow

and some of you will be receiving longer rest periods and lunch breaks

than others. However, these differences will equalize the second day

so that everyone will have worked and rested approximately an equal

amount of time. Tomorrow, take the same seats at 7:30 to start.

B. Test Administration

MONITOR: Do the Following Before Operators Arrive:

Based upon the pretest scores , rank—order the operators and place

them in matched groups . On a class roster place the appropriate operator number next to each name. On each operator—numbered test packet

write the appropriate name and place the packets arid target logs on the

tables as per the administration plan .

As each operator enters the test room, have him find his own packet

or assist him. Each event processor must be fully loaded with the appropriate work/rest cycle X—T scenario . Check to see that operators

have a pencil and X-T plot. Begin the testing promptly at 7:30 and

try to maintain the testing schedule.

MONITOR: Read the Following:

Take the material out of your test packets. The first two sheets

will be a sensor record sheet and the implant sketch for your first

30—minute period . All the implant sketches and sensor record sheets

that you will use today and tomorrow are the same as those you studied

yesterday . Remembe r that you will not stop working after each 30-minute

segment but will continue to work until you have conpleted your work

shift. All of you will be given a lunch break and some of you will

get several rest periods . You will be told as a group when your rest

period will occur . Depending upon which group you are a membe r of ,

you will receive different periods of work and rest. However , as I

said yesterday , total work and rest across the 2 days will be equal

for all of you.

I would like to remind you that the wall clock is right there

(point to it) to get the times required on the target log. If you are

going to use your wristwatch , set it with the wall clock now. We will

not be assisting you in any way with respect to your target analysis.

We will, however , be assisting you to make sure you are looking at the

50

- ,.—— — -——--- —— - - —- - ---——- _ -I-—-~

.-.JT--

II_ - ~~ - -- - — 

—
right sensor record and implant sketch throughout the exercise. If

you have any questions with regard to whether or not you are using the

proper sensor record or implant sketch please do not hesitate to ask.

Be sure to circle the activation patterns that you think are targets.

Number these patterns consecutively and record in the first column of

the target log . Are you ready? Begin.

MONITOR: Turn the Equipment On.

Check to see that all the equipment is running satisfactorily.

Every 30 minutes each monitor will supervise the changing of the implant sketches for two groups of four subjects . The monitor will be

sure that each operator is using the proper implant sketch and sensor

record.

S

51.

-i,

- 

-

-

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-- -.. --_ - -

~~~~~~

--— — - -

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.-.- — -—-

~~

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___________________
DISTRI BUTION

ARI Distribuljon List

4 OASD (M&RAI 2 HOUSACDEC. Ft Ord. ATTN: Library

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1 Mi) A~

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_ 

~~~~~~~~~~~~~~~~~~: 

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--~~~~~~~~~~~~~~ - —~~~~~~~~~~ -- 4~~~~~~~~ _ - — - - - ~~~~~ —

- -~~~~ - - - 

- 

.

~~~~~~~~~~~~ ~~~~~~~~~~~~~ -
1 US Marinr Corps Li.ision Ofc , AMC, Alexandria. AIIN: AMCGS—F 1 Oaf & Civil Inst of Enviro Medicine. Canada

1 USATRADOC, Ft Monroe, ATTN ATRO—ED I AIR CRESS. Kaneington. ATIM: Info Sys Br

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~

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2 Navy Med Neuro psychiatric Rich Unit , San Diego

1 Nay Electronic Lab , San Diego, AIIM: Rex Lab

1 Nay Trngden, Sen Diego, AIIM: Code 9000— Lib

1 NavPostGraSch , Monterey, AIIM: Code 55Aa

1 NavPostGraSch, Monterey, AIIM: Code 2124

1 NavlrngEquipCtr, Orlando. AIIN: Tech Lib

1 US Dept ol Labor, DC, AIIM: Manpower Admin

I US Dept of Justice, DC, ATIN: Drug Enforce Admin

1 Nat But of Standards, DC, AIIM: Computer Info Section

1 Nat Clearing Housv for MH—Info , Rockvul!e

I Denver Federal Ctr, Lakowood, AIIM: SCM

12 Defense Documentation Center

4 Dir Psych, Army Hq, Ruaaell Ofcs. Canberra

I Scientific Advsr. Mu Bd, Army Hg, Russell Ofcs , Canberra

1 Mil and Air Attache , Auttri an Embascy

1 Ceistre dii Recherche Des Facteurs . Humaine de Ia Defense

Nationale . Bruss els

2 Canadian loins Stall Washington

I C/Air Staff , Royal Canadian AF . AIIM: Pars SW Anal Br

3 Chief , Canadian Oaf Rich Staff , AIIM: C/CRDS(W)

4 Briti sh Del Staff . British Embassy , Washi ngton

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