Technical Paper 321 

~ _ EVE i

~ 

AD

THE EFFECT OF WORKLOA D ON PERFORMANCE

OF OPERATORS MONITORING UNATTENDED

GROUND SENSORS

Lawrence R. Edwards, Sterling S. Pilette 1ç~ ~‘(‘

~ Billy E. Biggs , HRB-Singer, Inc. ‘

~

~~~~

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. ,

~~

and

Harold Martinek

Army Research Institute for the Behavioral and Social Sciences

BATTLEFIELD INFORMATION SYSTEMS TECHNICAL AREA

_______________________ L

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t. U. S. Army

Research Institute for the Behavioral and Social Sciences

S.pt.mb.r 1978

Approved for public release; distribution unlimited,

______ 

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U. S. ARMY RESEARCH INSTITUTE

FOR THE BEHAVIORAL AND SOCIAL SCIENCES

A Field Operating A gency under the Jurisdiction of the

Deputy Chief of Staff for Personnel

WILLIAM L. HAUSER

JOSEPH ZEI DNER Colonel, US Army

Technical Director Commander

Pesearch accozr~ 1ished undeL contract

to the Department of the Army

HRB-Singer Inc.

NOTICES

DISTRIBUTION: Primary distribution of this report hee been made by ARI. PI.s,e .ddr.ss correspondence cencerning distr ibut ion of reports to: U. S. Army Rs,e.rch Institute for the Behavioral and Social Sciences, ATTN. PERI.P, 5001 E,i.nhow.v Avenue, Alexandria, Virginia 22333.

FINAL DISPOSITION: Thit report my bs destroyed ~~en it is no longer needed. P~ ees do not return It to

ihe U. S. Army Reeearch Inst itute for tha Belt v,oral and Soci l Sciences.

li

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lit. findings in tits, report are not to be cOnetrusd as in official Dip.rtm.nt of the Army position, unless so designated by other authorized documents,

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Unclassified SECURITY CLASSIFICATION OF THIS PAGE (soi.n DMa EnS.,.d)

READ TNSTRUCTIONS REPORT DOCUM ___________________

ON PAGE BEFORE COMPLETING FORM

~~~p~~o’r .i,i~~prq

rechnical Paper 321 

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1

2. GOVT ACCESSION NO. 3. RECIPIENT ’S CATALOG NUMBER

~~~~ 4, TjT L~~ #~~~~ ~~~~~~~~ ~ 9~MLj’ 1•-•*VERED

~~4E EFFECT OF WDRKLOAD ON PERFORMANCE OF 7 / IFTN~~ ~EP~~ r 

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~~~~~~~~~ 74-C-#

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B. PERFORMING ORGANIZATION NAM E AND ADDRESS tO. PROGRAM ELEMENT. PROJECT , TASK AREA C WORK UNIT NUMBERS

HRB—Singer , Inc . ~~~~

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Science Park, State College , PA 16801 ~~ ~~~~7627l7A~~~~~~ P.O. Box 60

ii. CONTROLLING OFFICE NAME AND ADDRESS ~ 

V ~~~~~~~~~ ‘

~~~~~~

U.S. Army Research Institute for the Behavioral !? .LSep tember 1978

and Social Sciences L .

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5001 Eisenhower Avenue , Alexandria, VA 22333 68

14. MONITORING AGENCY NAME & AODRESS(lf dlil.rwt tro., CantrolUn4 Office) IS. SECURITY CLASS. (ci thi. rsport ,,

—— Unclassified

15.. DECLASSIFICATIONJDOWNGRADING SCHEDULE

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Approved for public release distribu unlimi ted _________

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~~~k ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 17. Dl T SJTIe4$ a~k , .......,. T~ST’th. ab.tr.cS o.t.r.d In Stock 20, II dUt.,.nl tro., Report)

IS. SUPPLEM ENTARY NOTES

IS. KEY W ORDS (Coufflnu. .,, r•vs,i• .id. If n c•a• 7 ed Id.ntIly Ply block ni ib.r)

Unattended ground sensors Target acquisition

Seismic sensors Belt

Grid Workload effects

Surveillance Multiple displays

25 A~~~7’RAC1’ ~~~~~~~~~ ~~~~~~~~~ ~~~~~~ ~~~~~~~~ ~~~ Na ffi’ by Mock m k.)

~~~~ji rc,.mc..ri~~~~ ~ ~ o dete rmine the effect of workload (target activity level and

numbe r of sensors used) on unattended ground sensor (LYGS) operatorsi targetdetection ability, false—alarm rate, and direction and speed estimation

accuracy. )

~~~oee~ ur~

&R— Experienced operators monitored activations of UGS used in grids ~‘

‘

under six workload conditions--two levels of target activity x three levels —‘ ‘

~~~~~

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~ 

~~~~~~ 1Q3 rornois or ~ wov SI IS o aoLtTE

Un classified

SICUMY? CI.*SSIFICATION OP Twit PASt (

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—~~~~ ,-

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

tJnc1assifi~d SECURITY CLAUIPICATION OF THIS PAOE(IISias bat. tnt.o.~~

\ 20.

4f number of sensors monitored. Target activity level was defined as either

5 or 14 vehicle groups per 27 sensors per hour. The operators monitored in

counterbalanced sequence 77 sensors (3 grids), 54 sensors (6 grids), and

- . 108 sensors j12..gids). • 1

A ~-gultg Percentage of detections decreased linearly from 85% (4 to 6 vehicle

groups per hour presented on 27 sensors) to 26% (abbut 40 vehicle groups per

hour presented on 108 sensors). Without special training, operators should

monitor no more than 60 sensors being activated by a maximum of 10 vehicular

groups per hour (detection completeness for this condition was 76%). The nuinber of false alarms and the accuracy of speed estimation did not significantly

change ov.2r workload . Operator accuracy in direction estimation decreased

significantly as a function of workload from true azimuth j30° to true azimuth

- 

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Unclassified

SECURItY CLASSIFICATION OF THIS PA GI(IRi.n Oat. titt.,. ~~

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Technical Paper 321

THE EFFECT OF WORKLOAD ON PERFORMANCE

OF OPERATORS MONITORING UNATTENDED

GROUND SENSORS

Lawrence A. Edwards, Sterling S. Pilette, Billy E. Blggs, HRB•Slnger, Inc.

and

Harold Martlnek

Army Research Institute for the Behavioral and Social Sciences

BATTLEFIELD INFORMATION SYSTEMSTECHNICAL AREA

SubmItted as complete and Approved by: technically accurate, by:

Edgar H. Johnson A.H. Blrnbaum, Acting DIrector

TechnIcal Area Chief ORGANIZATIONS AND SYSTEMS

RESEARCH LABORATORY

Joseph Ziedner

TECHNICAL DIRECTOR

U.S. ARMY RESEARCH INSTITUTE FOR THE BEHAVIORAL AND SOCIAL SCIENCES

5001 Eisenhower Avenue, Alexandria, Virginia 22333

Office , Deputy Chief of Staff for Personnel

Department of the Army

S.pt.m b.r 197~

Army Project Number intelligence Systems

20162717A721

Appros,d for public ref law; distribution unlinWtsd.

j
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.

L.

4.-

______________________________________________ _________________________ 

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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 within command and control centers and is concerned with topographic products and procedures , tactical symbology , information

managemen t, user—oriented systems , staff opera tions and procedures ,

and sensor systems integration and use.

One area of special interest is human factors problems of presentation and interpretation of surveillance and target acquisition information . One relatively new source of intelligence informa tion is remote

monitoring of the battlefield using seismic, acoustic , and magnetic

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 determine from this

display not only the presence of the enemy bu t also informa tion such as

the direction and speed of convoys and person nel , the number of vehicles

in a convoy, and the composition of the convoy (e.g., armored versus

wheeled vehicles).

This publication investigates the effects of workload on operator

performance as defined by target activity level and number of sensors

monitored. These results have implications for the design of monitor

displays and operator—assignment doctrine .

Research by the Army Research Insti tute for the Behavioral and

Social Sciences (ARI) in the area of 3ensor systems integration and use

is conducted as an in—house effort augmented by contracts with selected

organizations--in this case, HRB-Singer under contract DAHC19-7A—C—0030.

The effort is in response to requirements of Army Project 2Q762717A721

and to special requirements of the U.S . Army Intelligence renter and

School , Fort Huachuca , Ariz., Headquarters , MASSTER , Fort Hood , Tex.,

and the Remotely Monitored Battlefield Sensor System Project (REMBASS) .

Special requirements are contained in Human Resource Needs 74-21 and

74—73.

The cooperation of participating personnel of the unattended ground

sensor platoon of the 5O2d Military Intelligence Battalion , 2d Armored

Division , Fort Hood , Tex., is appreciated. Special thanks are given to

LTC Dunlap , 2d Armored Division G2 Officer , CPT Jones , UGS platoon commanding officer , and SGT Stollings, 

\

UGS Platoon NCO.

- .4L \

~ ~ ~ JOS~PH ZEIDN~ R

Technical Di~ ector 

_ ._ I

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-__-- - - -_.-—-- --_ _ . _

ThE EFFECT OF WORKLOAD ON PERFORM~~ CE OF OPERATORS MON ITORING

UNATTENDED GROUND SENSORS

BRIEF

Requirement:

To investigate the effect of workload on operator performance as

defined by target activity level and number of unattended ground sensors (UGS) used.

To determine operators ’ target-detection ability , false-alarm

rate, and direction and speed estimation accuracy to help establish

system capability.

Procedure :

Following an orientation and training session , experienced UGS

ope rators monitored , in sequence , each of three event recorder displays

showing activations of UGS used in grids. The operators monitored 27

sensors ( 3 grids) on one display , 54 sensors (6 grids) on the second ,

and 108 sensors (12 grids) on the third. Each grid was composed of

nine minisids , spaced 500 m apart to form a 1,000 m2 field . Operators

encountered periods of high and low target activity that were of equal

time duration . Operators reported each target they detected and estimated speed and direction of movement.

Findings :

The number of sensors monitored and the target activity level

significantly affects UGS operator performance . The operators’ ability

to detect targets decreased as either activity level or number of sensors increased. Operators’ ability to estimate target direction also

decreased as activity leve l increased. Although target speed was underestimated , no significant differences were found between any of the experimental conditions for this variable . The false—alarm rate was low

(one per 3 hours).
Utilization of Findings :

Careful judgment should be exercised in assigning workloads to

UGS operators. Operators without special training or experience should

not monitor more than 60 sensors , and then only if targe t activ ity is

low. If operators are required to monitor more than 60 sensors or if

target activity is h igh , in tel ligence estimates of target activity based

on UGS operator reports should be adjusted upward.

The grid deployment of UGS is a valid method for surveillance of

large areas to detect vehicular movement. Operators’ target-detection

performance was good even though they had received no training or experience in monitoring UGS employed in grids . The false-alarm rate

(one per 3 hours) and the 85% detection rate for the 27-sensor , low—

target—activity condition demonstrates the initial capability of the

use of UGS employed in a grid . Although the true speed of vehicles

passing through the grid was unde restimated for all conditions, the

“ cross—country ” speed estimate (used for predicting time of arrival )

is as accurate as that made for sensors deployed in the more typical

string configuration along roads or trails.

Special training should be instituted for target detection under

high—workload conditions and for the estimation of the target ’s d irection of travel . Direction estimation was poor (±400 on the average);

but in view of the atypical target paths used in this research , the

above value should not be generalized to the usual operational

situation. 

~~~~~~~~~~~~ 
THE EFFECT OF WORKLOAD ON PERFORMANCE OF OPERA TORS MONITORIN G

UNATTEN DED GROUND SEN SORS

CONTENTS

Page

INTRODUCTION 1

OBJECTIVES 4

METHOD 4

Population and Sample 4

Independent Variables 5

Dependent Variables 5

Research Design 6

Apparatus 6

Scenario Construction 6

Test Procedure 8

RESULTS AND DISCUSSION 10

Percent Detections 10

False Alarms 15

Speed 16

Direction 16

CONCLUSION S AND RECOMMENDATIONS 19

APPENDIX A. THE GRID DEPLOYMENT OF SEISMIC SENSORS USED

FOR PATCHING 23

H. TARGET QUALITY DISTRIBUTION--NORFOLK SCENARIOS . . 37

C. ILLUSTRATION OF SENSOR GRID REVERSAL 39

D. TARGET QUALITY DISTRIBUTION FOR TARGETS PRESENTED

IN THI S STUDY 41

E. ORIENTATION BRIEFING 43

F. INTRODUCTION TO THE GRID DEPLOYMENT PATTERN

(LECTURE/DISCUSSION ) 45

G. TEST PROCEDURE TRAINING 49

F I
Page

APPENDIX H. MULTI-DISPLAY PROCEDURE TRAINING 59

I. TARGET LOGS 63

DISTRI BUTION 67

LIST OF TABLES

Table 1. Research design (30-minute periods) 7

2. Schedule of administration onsite at Fort Hood 9

3. An alysis of variance for percent detections 11

4. Duncan Multiple Range Test on percent detections

by display 12

5. Mean percent detections for display by activity . . . . 12

6. Average number of detections for display by activity

(30—minute periods) 13

7. Number of targets presented for display/activity

condition 15

8. Average number of false alarms for each display/

activity condition 15

9. Mean speed deviation for display by activity in

meters per minute 16

10. Analysis of variance for speed deviations 17

• 11. Analysis of variance for direction deviations 18

LIST OF FIGURES

Figure 1. Example of a 9-sensor grid used at a natural

chokepoint 3

2. Effect of workload on percent detections 14

3. Effect of workload on direction estimation accuracy . . 20

—

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
THE EFFECT OF WORKLOAD ON PERFORMANCE OF OPERATO RS

MONITORIN G UNATTENDED GROUND SENSORS

INTRODUCTION

Unattended ground sensors (UGS) represent part of the Army ’s capability for detection , locat ion , and target acquisition of enemy activity

at a remote location . UGS can be used alone or in combination with

ground surveillance radar , night vision devices , aeria l surveillance

(radar , infrared, photographic , and visual) , signal intel ligence , patrols , and observation and listening posts to produce timely and reliable in telligence information . Several types of UGS that the Army uses

can be categorized according to the method of remote sensing: seismic ,

acoustic , magnetic, electromagnetic , and infrared. UGS are tactically

used in offensive and defensive operations by units from small independent patrols to full division operations. Uses of UGS in offensive operations include the following :

• Target acquisition——sensors ’ real—time detection capability

leads to immediate reaction .

• Landing (drop) zone——sensors monitor enemy activity for future

airmobile assault.

• Combat sweep——sensors monitor enemy withdrawal or attack

activity.

• Ainbu~h--sensors establish enemy habits and are employed with a

remote firing device and command—detonated mines .

Uses in defensive operations include the following:

• Base camp defense——sensors provide warning of enemy presence

and extend listening post/observation post detection range .

• Convoy security——sensors provide ambush detection and warning.

• Border surveillance—-sensors provide warning of enemy presence

and fire control information for real-time rea Lion .

• Beach defense-—senso rs prov ide warning of coun terattack in

beachhead situations.

CJGS can be employed in three ways : string, grid , and alerting.

• In string employment , UGS are used along a potential transportation

route (land or water). Whether hand-emplaced or air-delivered , the

objective is to implant sensors accurately so that their location with

respect to the route and their separation distances are known . This1
- • —

information enhances the manual readout function by permitting relatively accurate direction , speed , and length of column information to

be derived from the sensor activation patterns. If hand—emplaced , the

sensor locations can be pinpointed on a map and “ seated” properly in

the ground. Various combinations and mixes of sensor types have been

field—tested by the Army .

In grid employment (sometimes called field , belt, gate , or gate

array) , (JGS are deployed in a regularly spaced , two—dimensional pattern

to “cover ” a given geographical area or field (Figure 1). The grid

would normally be used in defensive operations for surveillaiice and

target acquisition of the forward edge of the battlefield and behind

enemy lines and for guarding areas of importance in the rear. Whether

hand—emplaced or air—delivered , the objective is to implant the sensors

accurately so that their locations are known and ground distances between the sensors are about equal. Aga in , hand emplacement is best for

knowing sensor location and for proper “seating.” The grid is designed

to maximize the probability of detecting and acquiring enemy forces intruding in any portion or from any direction within a large area (1 to

severa l km2). Because the path of the target is estimated , the operator

can make only gross estimates of speed. Until special operator training procedures and job aids are developed , the accuracy of estimates of

speed , direction , and number of targets will be below that usually obtained with string employment of UGS .

In alerting employment , UGS are used to “cover ” a given route or

ground area , but for various reasons their exact locations and the

ground distances between them are not accurately known . This situation

can occur when sensors are delivered by mortar or artillery in areas

that are inaccessible to friendly units or when sensors have been airdelivered under poor visibility conditions. Whatever the cause , the

operator knows only the approximate location of the sensors . Reliable

detection of activity can be made , bu t additional information such as

speed , numbe r of targe ts , and direction cannot be computed accurately .

The U.S. Army Intelligence Center and School ( USAICS ) teaches the

string employment concept and the alerting employment concept. Other

than a br ief ove rview , howeve r , the school does not train students in

monitoring and interpretation procedures for grid employment. Thus ,

in the past , UGS operators were not likely to encounter grid-monitoring

situations. Because of the shift in emphasis from the Southeast Asia

type of conflict , however , the possibilities of grid applications in

area-intrusion situation s have increased. The grid employment can be

used in almost all the offensive and defensive situations discussed

previously.

2

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In a recent study of how to patch sensors to the RO 376 event

recorder ,1- a number of promising techniques were reviewed . Four of

these eventually were selected for experimental comparison . Trained

UGS monitors CMOS l7M20) performed their tasks using all four of these

patching techniques. The result of this experiment was the selection

of the “row” patching technique (see Appendix A) for optimal performance .

The study was run with grids consisting of either 9 or 24 sensors

in a 1,000 m2 field . It was shown that monitors could detect targets

in a field where sensors we re placed 500 m apart (9-sensor grid) as

well as when sensors were placed only 250 m apart (24-sensor grid) .

Results showed that hi gh battlefield activity caused a lower target

detection rate than did low battlefield activity. This result occurred

for all patching techniques evaluated.

One problem with extensive use of grid deployment is that the number of operators required is not known . More information is needed concerning the level of performance that can be expected from a single

operator as the number of sensors or sensor fields is increased. It

was assumed that as the n umbe r of sensors to be monitored increases,

the operator ’s ability to respond adequate ly to all targets diminishes.

The leve l of performance re lative to the n umber of monitored sensors

is , howeve r , unknown . Research is needed to determine the rate of impairment of performance as a fu nction of an increased numbe r of sensors .

OBJECTIVES

The present study was , therefore , designed (a) to investigate the

• effect of workload on operator performance as defined by target activity

level and number of unattended grou nd sen sors used and (b) to determine

operators ’ target-detection ability , false-alarm rate , and accuracy of

direction and speed estimation to help establish system capability.

METHOD

Population and Sample

The population of concern consisted of Army enlisted UGS operators

(MOS l7M20) who had been trained at the USAIC&S and who had received

some field experience with an operational unit. The sample consisted

of 28 enlisted personnel of the l63d Military Intelligence Battalion

stationed at Fort Hood , Tex. , who served as operators. Each operator

had participated in one or two of the following exercises: Fort Huachuca

• ‘Pilette , S., Biggs , B., Edwards , L., & Mar tinek , H. Optimum Patching

Technique for Seismic Sensors Employed in a Grid. ARI Technical Paper

320, August 1978.

4

• •
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~

• --• - ---•-•—-- -

exercises , August 1972; Gallant Hand , Fort Hood , April 1973; Brave

Shield , Fort Bliss , November 1973; Operational Readiness Training Test, • Fort Hood , February 1974; Advanced Individual Training (AlT) , Fort

Huachuca , February 1974.

Independent Variables

• Displays. Each operator monitored in succession three displays ,

each presenting activations from a different number of sensors—-27,

54 , and 108. Order of presentation of the displays (or numbe r of sensors) to the subjects was counterbalanced to prevent practice or learn- • ing from confounding this variable .

Scenario--Order of Presentation. Each operator was presented 14

30-minute scenarios CR0 376 event recorder plots portraying sensor ac-

• tivations) in one of 14 counterbalanced orders. Scenarios and order

are confounded but not with displays.

Target Activity . A target was defined as one or more vehicles in

a group . The low-target-activity level was set at two to three targets

per 27 pens per 30 minutes. The high-activity level was set at six

to eight targets per 27 pens per 30 minutes. The targets (sensor activations) in the low— and high-target—activity levels were different.

Thus, this variable is confounded with scenario (target difficulty) .

Dependent Variables

The dependent variables in the study-—correct detections, false

alarms , direction , and speed——were scored as follows :

False Alarms. If an operator reported a target in the scenario

when no target was causing activations of the designated pens , or if

an operator reported two or more targets on the same pens when there

was only one target, the response was classified as a false alarm .

Detection and Percent Detection. If an operator reported a target in the scenario at the time a target was causing activations on

the designated pens , the response was classified a correct detection .

Percent detection is the number of detections divided by the numbe r of

targets available for detection .

Direction. The direction of a target path was scored from the

point where a target left the grid. An 18-point sector scale was

used , with each sector being 100. The response was scored as a cor—

rect direction if the target path that the subject drew was anywhere

in the correct sector. If the target path was drawn in a sector other

than the true sector, a deviation score was given corresponding to the

number of sectors removed from the correct sector

.S
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Results on target direction should be generalized with caution .

Because of space restraints in the area assigned for the collection of

sensor activation data at Fort Bragg , after passing throuqh the grid

most targets were required to turn and travel parallel to the last row

and approximately 100 m from it. Thus , most of the targets activated

the last row of sensors, making the direction estimates more d i f f i c u lt

than if the target had kept going straight as expected .

Speed. Deviation scores were used in scoring speed . If an operator reported the correct speed of a target , he was given a score of

zero . If the re sponse was incorrect , the deviat ion in meters per minute

f rom the correct value was determined .

I~~search Design

• The research design is presented in Table 1. The evaluation was

a comparison of monitor performance on three displays (27, 54 , and 108

sensors). The independent variables analyzed were target activity (2),

scenario—order (14), and displays (3). The design counterbalanced the

sequence of scenario presentations , sequence of d isplays , and sequence

of high and low target activity . All operators were presented with all

14 scenarios and each of the three displays. The effects of the three

primary independent variables and their interactions were analyzed using

the analysis of variance and Duncan ’s Multiple Range test.2

Apparatus

~ qelve RO 376 tactical recorder simulators were used. The simulator consists of a v iewi ng win dow and a drive mechanism tha t presen ts

sensor activations at the same rate of speed and in the same format

as the actual 30-channel RO 376. To display 54 sensors , the same simulator was used bu t wi th a larger wi ndow , similar to the Bass III recorder. Two of these were used for displaying 108 sensors. Previously

prepared RO 376 plots were displayed on the simulators.

Scenario Construction

Realistic scenarios were con structed from activa tions recorded

during Army field exercises conducted at Fort Bragg . These exercises

consisted of a vehicle or groups of vehicles moving through a 1,000 m2

field at known rates of speed along specified routes. Because the

activations were recorded on audio tape , selected par ts could be “played

back” to an RO 376 event recorder in any orde r required to construct a

2

Burning, J. L., & Kimtz , B. L. Computational Handbook of Sta~

.istics.

Glenview , Ill.: Scott , Foresman and Company , 1968, pp. 115-117.

6 

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__________• ~ • .

.- - - —-— 

- - 
___ __ 

scenario on RO 376 plot paper. Scenarios had been constructed from

the field data on two previous studies (Pilette et al., 1975) , and

these scenarios served as the primary source of data for this study .

An analysis of monitor performance (see Appendix B) on 113 of

the targets presented during the previous study 3 was accomplished to

determine the level of difficulty (p values) for each of the targets .

A broad range of target difficulty was used in the scenarios to provide

realistic target situations for the monitor. No changes were made to

the original target activation patterns; however , some of the target

activations were displayed a second time in a manner that represented

a perfectly synunetrical reversal of the actual sensor grid. This reversal did not affect the temporal sequence of activations or the

quantity of activations. The purpose of the reversal was to provide

a greater variety of target paths for the monitor to observe . This

manipulation doubled the number of target paths available . Appendix C

shows the results of such a reversal on a target pattern.

This study required a total of 14 30-minute scenarios . A scenario

was presented on RO 376 plot paper , which was subdivided into three

9—pen groupings , with each grouping representing a 9-sensor grid.

Pens 1 to 9 represented Grid 1, pens 11 to 19 represented Grid 2,

pens 21 to 29 represented Grid 3, and pens 10, 20, and 30 were idle.

Seven of the scenarios contained two to three targets and constituted the low activity condition . The other seven scenarios contained

six to eight targets and constituted high activity. The entire 7 hours

of scenarios contained a total of 64 targets , with 15 targets in low

activity and 49 targets in high activity . A target—quality distribution chart for the targets presented in this study is included in Ap-~ pendix D. This chart shows that the predicted detection completeness

of the low—target—activity targets is 68% whereas that for the high—

target—activity targets is 57%. Thus, the target difficulty of the

two groups of targets is different , and the results should be interpreted accordingly.

Test Procedure

The training and test schedule is presented in Table 2. During

the first day , officers associated with the UGS platoon were briefed ,

classrooms were prepared, and drive mechanisms were readied and placed

into position . Each operator then participated in the following three

sessions in the order given :

3

Edwards , L.., Rockford , D., & Shvern , U. Comparison of Four Displays

for Use in an Unattended Ground Sensor Grid Deployment Situation. API

Technical Paper 281, April 1977.

8

L - - -- - - —- .-----• • 

• - - -
— -.- - - 

~

1

Table 2

Schedule of Aónl ni s tratlon Onsl te at Fort Hood

Room A Room B

Day 1 AM Unit briefings Classroom set-up

PM Equipment set-up, Subject

Scheduling

Day 2 AM Group I (14 subjects ) 8:00-11:00

Orientation Briefing

• Grid Briefing

Test Procedure Training

PM Group I (14 subjects ) 1:30-4:00 Group II (14 subjects )

Patch Technique (Row ) Ori entation Briefing

Training Gri d Briefing

Test Procedure Training

Day 3 AM Group II (14 subjects) 8:00-11:00

Patch Technique (Row)

Training

PM Group A (9 subjects ) 2:30-5:00

Multi-display Training

Data Collect ion

Day 4 AM Group B (8 subjects ) 8:00-12:30

Multi-display Training

Data Collection

PM Group C (8 subjects ) 12:30-5:00

Multi-display Training

Data Collection

Day S AM Group D (3 subjects ) 8:00-12:30

PM All operators 1:30-3:00

Critique and Review ________

I

.•. - 

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

- 

• :

~~~~~~:~~ 

-
—V~~~~~ ~~~~~~~ • --- -~~~-~~~~~~~~~~~ 

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

• —-— -

~~~

Session I Orientation Briefing (see Appendix E)

Introduction to the Grid (see Appendix F)

Test Procedure Training (see Appendix G)

Session II The Grid Deployment Using Row Patching (see

Appendix A)

Session III Multidisplay Training (see Appendix H)

All familiarization and training activities were intended to prepare operators for the data collection after Session III. The orientation briefing of Session I gave operators an idea of the purpose of

the study and what was going to happen. Operators were then introduced

to UGS grid deployment and were shown examples of target intrusion .

The test procedure training was intended to teach operators the ne cessary procedures , including the use of the three target logs (Appendix I).

In Session II , operators were trained in target detection and direction and speed estimation using the row-patching technique for UGS

displayed in a 9-sensor grid. As with the test procedure training, a

self-administered workbook ( Appendix A) was used with instructor guidance. This training was an introduction to the row-patching technique

with a 9-sensor grid , not a comprehen sive grid training program.

The multidisplay training in Session III used a round—robin approach . Each operator monitored each display condition for approximately

10 minutes, during which time he would report any targets and provide the

required responses. The same approach was also used during data collection . Each operator monitored each display condition for 1 hour and

then switched to a different condition as required by the experimental

design .

RESULTS AND DISCUSSION

Percent Detections

The analysis of variance results for percent detections are given

in Table 3, A statistically significant effect at the .001 level was

found for percent detections for the Display (number of sensors) variable. A Duncan Multiple Range Test (Burning & Kimtz, 1968) was subsequently performed comparing detection performance for the three displays.

Table 4 shows that all three displays were significantly different from

each other at the .05 level. Thus , as workload increased (from 27 pens

to 108 pens), operator performance decreased.

Table 3 shows that the difference between the high and low activity

levels is significant at the .001 level. This significant result m di—

cates that a large number of targets entering a sensor grid over a short

V 

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individually. Again , as workload increased (low to high activity), V

performance decreased

Table 4

Duncan Multiple Range Test on Percent Detections by Display

Shortest

significant

108 pen 54 pen 2 7 pen range

Means 43 57 71

43 14.64* 27.86* 9 334

57 13.33 * 9.804

*Significant at the .05 level.

Table 5 shows the mean percent detection rates for all displays

and activity levels. The percentage of targets detected is greatest

for the 27—pen display , low-target-activity condition , and smallest for

the 108—pen display , high-target-activity condition .

Table 5

Mean Percent Detections for Display by Activity

Target Display condition

activity 27 pen 54 pen 108 pen Average

Low 85 76 60 74

High 56 39 26 40

Average 71 58 43 57

The percent detection rate during high target activity on the 27-

pen condition was approximately the same as that during low target activity on the 108-pen condition . This finding is noteworthy because

L these two conditions are the only ones that present approximately the

12

I

V - V . - - -

L .. - ~~~~~~~~~~~~~ - --- ~~

-
same number of targets within the same time period-—approximately one

every 4 minutes. These results are shown in Figure 2, which indicates

the percent detections as a function of the number of targets presented.

The slight displacement of the line could be attributed to chance variations , individual target difficulty differences between the high— and

low—target-activity condition , or the increase in difficulty associated

with target overlap and crowding on the display . The latter problem

was observed in scoring the operator reports and is hypothesized as one

error source that may be reduced through special training. As noted

earlier, there was a diffe rence in target difficulty between high and

low target activity based on figures from previous research (Appendix D) - These diffe rences (predicte d percent detection for low = 68%, for

high = 57%), if appl icable , would accoun t for the displacement of the

curves and resul t in the dotted line in Figure 2.

Table 6 shows the total detections for all displays and activity

levels. These figures indicate that the number of detections increases

as the number of sensors or target activity increases , even though the

percentage of targets detected decreases (Table 5). These results we re

expected because of the greater number of actual targets presented as

the n umbe r of sensors or targe t activity increased. The average number

of targets presented to an operator for each display/target activity

condition is given in Table 7.

Table 6

Average Number of Detections for Display by Ac tivity

(30-minute periods)

Targe t Display condition

activity 27 pen 54 pen 108 pen

Low 1.8 3.3 5.1

High 3.9 5.4 7.2

Table 3 also shows statistically significant effects for scenario—

order combinations . Because the Scenario-Order variable was confounded • with subjects, individual differences are believed to be responsible

for much of the variation . To what extent the order of presentation

of the 14 scenar ios affec ted mon itor performance cannot be precisely

determined. The three-variable (activity-display-order) interaction

effect is significant; howeve r , this statistical result cannot be clearly

interpreted in view of the confounded nature of the Scenario-Order

variable . 

13
~~~~~~~~~~~~~~~~

---

~ 

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~~ 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ V~~~~

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27. 54, 108 = Number of pens - 

L = Low target activity ML H = High target activity

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10-

0— I I I I -

i I I

5 10 15 20 25 30 35 40 45 50

NUMBER OF TARGETS PRESENTED (WORKLOAD )

Figure 2. Effect of workload on percent detections.

14

~

~~~V -• -~~~~ :~~ :VT

~~~:~V:I~~E ~~~~~• H
-

Table 7

Numbe r of Targets Presented for Display/Activity Condition

Target Displ~y condition

activity 27 pen 54 pen 108 pen

Low 2.1 4.3 8.6

High 7 14 28.2

False Al arms

A frequency polygon of the false-alarm data shows a marked positive ly skewed distribution and was judged to not approximate the norma l

curve. Because of the skewed distribution and paucity of false alarms ,

a statistical evaluation was not conducted.

The average number of f alse alarms for each display and target

activity condition is shown in Table 8. Mean false-alarm rates are

similar for all three displays and for both target activity levels.

False—alarm rates this low were considered to be relatively useless

for research purposes but highly important for operational implications .

On the average , only one false alarm was reported by each operator for

3 hours of monitoring.

Table 8

Ave rage Numbe r of False Alarms for Each Display/Ac tivi ty Condi tion

Target ________ Display condition

activity 27 pen 54 pen 108 pen Average

Low .14 .18 .29 .20

High .25 l8 .00 .14

Average .20 .18 .15 .18

15

L. - - - -

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

Speed

Mean speed deviation scores are shown in Table 9. Scores for each

activity level and display are negative and the overall mean is negative. A two—tailed t test for a single mean indicates that a 54 in per

minute deviation is significantly different from zero at the .01 level;

therefore , when sensors are used in a grid , operators ur lerestimate the

true speed of targets.

Table 9

Mean Speed Deviation for Display by Activity in Meters per Minute

Target Display condition

activity 27 pen 54 pen 108 pen Average

High —47 — 67 —54 —56

Low -47 —60 —48 —51

Average -47 —63 —51 -54

The probable explanation for this underestimation of speed is the

operator ’s assumption that targets were traveling in a straight line .

Thus , if a target activates a sensor 5 minutes after activating a previous one located 1,000 m away, the mon itors would estimate the target’s

speed to be 200 m per minute. If , however , the target had traveled on

an indirect route (as would be the case in cross-country travel) between

the two sensors and covered a distance of 1,100 m , its actual speed

would have been 240 in per minute . If actual target speed is necessary

for some purpose , such as target classification , operator underestimates of the speed can be a problem in grid deployment of sensors. If

the primary purpose of determining target speeds, however , is to aid

in predicting target arrival time at a certain point or line , then

these underestimates are the correct values for this application providing the terrain characteristics remain relatively constant.

Table 10 shows no significant effects of the primary variables on

speed deviation. Underestimation of speed was consistent across displays , activity levels , and scenario-order combinations .

Direct ion

The analysis of variance results for direction deviat:rn scores

are given in Table 11. The only statistically significant effect found

was for the target activity variable. The average direction deviation

for the low—target-activity condition was 3.44 (or *34.4°), whereas

that for the high-target-activity condition was 4.4 (or ~46.4°).

16
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~~sults in Figure 3 indicate that it is more difficult for operators to determine a target’s direction of travel when other targets

are in or around the same area. It may be that operators have diff i—

culty distinguishing sensor activations caused by one target from activations caused by other targets , or that time pressures affect operator accuracy . Figure 3 shows the effect of workload on direction

deviation score . The re appears to be a consistent relationship for

the high-target-activity condition between direction deviation and

number of targets, although no significant effects were found in the

analysis of variance for the display variable or its interaction with

target activity . No consistent effect appears for the low—target—

activity condition .

The mean direction deviation score for all activity levels was

±40 40 from ground truth. Al though scores were somewhat better when

target activity was low, this amount of deviation might be considered

high for a field commander’s purposes. Operators are more familiar

with sensor—string data in which the target’s direction is generally

a known road or path. The grid employment situation causes more difficulty in determining direction . A need for more training and experience with grid use seems to be indicated. These results , however,

should be generalized with caution to the operational situation in

view of the atypical target paths required after the targets had passed

through the grid.

CONCLUSIONS ANt) RECOMMENDATIONS

The result of increasing operator workload (number of targets an

operator must detect and report) is a decrease in the percentage of

detections. This effect occurred if workload was increased by increasing the number of pens (or sensors) to be monitored from 27 to 54 or

from 54 to 108 with the density of targets per pen held constant. The

effe ct also occurred if workload was increased by increasing the target

density per pen (target activity) with the number of pens held constant.

We can conclude that increasing either the number of sensors an

operator must monitor or the level of target activity will cause a decrease in the percentage of detected targets; furthermore , a combined

increase in both numbe r of sensors and activity level will cause a

greater impairment. The extreme comparison of operators monitoring

27 pens under low target activity versus operators monitoring 108 pens

under high target activity revealed a decrease in percent detection

from 85% to 25%.

It is critical that field officers be aware of these effects.

They must decide which levels of target detection are acceptable and

which are not , and then make provisions for adequate UGS operator support. Intelligence analysts should note the effects of increased

19 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -~~- --—-- - — --- ~ —-~~ 
27, 54, 108 - Numbe r of pens

L — Low target activity

L H — High target activity

- 108H

550

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a 0

350_

271 108L 0 0

300 — I I

5 10 15 20 25 30

NUMBER OF TARGETS PRESENTED (WORKLOAD)

Figure 3. Effe ct of workload on direction

estimation accuracy .

L

20

- ~~~~~~~~~~~~~~~~~ L E ~~~~~~~~~~~~ T~

1L~~- - - i

~ -- — -
~ —--

numbers of sensors and activity leve l when interpreting operator reports and should make corresponding adjustments to their intelligence

estimates.

If workload was increased by increasing target activity level, a

decrease was found in the accuracy of target-direction estimates made

by the operator. Moreover, results on operators’ target-direction

estimates indicate that these estimates are of little use operationally because of the large average deviation from the true target direction . It is not concluded , however , that they should be eliminated

from the operator reports at this time . Two temporary causes for these

poor estimates can be hypothesized-—ope rator ability and unusual activation data . If operator ability is the problem , an error analysis and

training program should be researched. If the results are due to the

atypical target paths used afte r passing through the grid , these results

should not be generalized to operational situations. Additional activation data should be collected in a field exercise more suitable to

obtaining generalized estimates of the operator’s capability to provide

valid target-direction estimates.

In the present experiment, errors of omission (missed detections)

were far more frequent than errors of commission (false alarms). Only

29 false alarms were generated by the 28 operators , each working for

a 3—hou r period. Efforts to improve systems capability should concentrate on errors of omission , while insuring that the false-alarm rate

does not increase.

Target speeds were significantly underestimated for all displays

and both activity levels. There were no significant differences in

the degree of underestimation between any of the display conditions or

target activity levels. The underestimates of target speed can be more

useful information than actual speed. The underestimates occur because

the ope rator must assume a relatively straight target path between two

points on the grid used for making a speed estimate. In fact , a target

will make slight (50 to 300) changes in direction to avoid obstacles

and , thus, will travel a greater distance than the operator estimates.

Therefore , the operator will underestimate the actual speed. Given

that indirect routes were available for the targets, the underestimates

are not surprising. Whenever a grid deployment of sensors is used , an

underestimate of target speed can be expected unless the terrain is

relatively free of obstacles. However , because the field officers

will typically be interested in determin ing when a target will reach

a certain area , the target’s actual speed is immaterial. The estimated

cross—country speed , which is an un derestimate of the actual target

speed , will be the appropriate measure for this purpose . Some adjustment in the estimated speed value s may be required if there is a signif—

L ican t difference in terrain between the area the target has traversed

and the area it is approaching. Similarly , if actual target speed is

needed for target identification purpose s, the operators’ estimates

must be increased appropriately.

21
As a result of this research , it is recommended that

1. Operator performance , as represented by percentage of target

detections , false—alarm rate, and speed estimations , is sufficient for operational use given a low workload (30 to 60

sensors and low target activity) .

2. Special training on the interpretation of unattended ground

sensors used in a grid should be developed , especially for

the higher workload situations and for estimating target

direction .

3. Doctrine should be developed defining the use of operators

in the field con sistent with Army requirements for target detection , availability of operators, and workload/performance

tradeoffs.

- - 

22
AP PEND~X A

ThE GRID DEP LOYM ENT OF SEISMIC SENSORS USED FOR PATCHI!’IG

0b,iecti ye

To familiari ze you with hOw the row patching technique is used with

a grid deployment pattern and to train you on how to use it to detect and

report on tatgets using the seven-step procedure . Part I of this workbook

deals wi th training and Part II deal s with practice in target reporting .

PART I - TRAINING

What is the Row ~~~~~~~~~~~~~~~~

The row patchi ng technique is defined as patching the sensors which

have been deployed in a symmetri cal grid pattern into horizontal rows on

the X-T plot. Look at the next page of this workbook. The top half of

Figure A presents a syn~netri cal 9—sensor gri d which shows the sensors

grouped into three hori zontal rows : Row I , Row II , and Row III. All the

sensors are seismi c and are set at the same medium gain setting. The

bottom half of Fi gure A contains the seven-step reporting procedure that

you are already familiar with . Notice that the sensor numbers are shown.

At this time pul l Fi gure A out of this booklet , wri te your name in the

upper rig ht-hand corner and place it on your desk where it is clearl y

visible.

Exami ne the 9-sensor gri d of Figure A more closely. Study again

wh i ch sensors have been assi gned to the various rows . Fill in the fol l owing bl anks as you come to them.

Row I is composed of sensors 1 , 2, and 3.

Row II is com posed of sensors 4, —, and 6.

Row III is composed of sensors , , and

How do you Detect Targets?

Any target that enters this gri d will have to pass throu~~ and around

one or more of these rows . What this means to you is that you will be able

to detect and report on targets by observing what activation activi ty is

taking place in each row . In other words , any target entering or leaving

the grid area will have to activate one or more sensors in one or n~re rows .

Now loo k at the X-T plot in Fi gure 8. The sensors that you have just

studied in the grid are each patched to a pen of the same number on this

X-.T plot (one-for-one). Pen 1 on the X-T plot , therefore , refers to sensor

1 on the grid, etc . Th roughout this lesson the terms “sensor” and “pen”

will be used interchan geabiy .

&

23

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24

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Figure B. X-T plot for row patching usinç~ 9—sensor grid

(learning targets).

25
_____ 

- - - - -

Fiid your job aid (UGS Ruler). One side of the ruler has a 24-pen

(sensor grid) scale and a 9-pen (semor grid) scale as shown below .

74 - sn

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

1

For this exercise you will be concerned only with the 9-pen scale. You

will notice that your p-pen scale is broken down into three (3) colors . Each of these colors represents a row of sensors within a 9-sensor gri d.

BY PLACING THIS SCALE ON T~E X-T PLOT YOU

WILL BE ABLE TO QUICKLY DETERMINE WH ICH

SENSO RS IN EAC H ROW HAV E ACTIVATE D.

Now lay this scale on the X-T plot and line it up properly. Notice

how quickly you can tel l which sensor in each row is activating. In many

situations , this job aid may help you to: (1) detect a ~~~~~ (2) deter -

mi ne if more than one ta~~et is within the grid area at the same time.

Go back to Figure A. Fi gure A shows the paths of three targets which

we will analyze . As you can see , these targets passed through or around

various rows and activated sensors in these rows . Place your job aid on

the X-T plot for each of these targets and briefl y note which pens of

each ro~ have activated.

a. Example 1 - Target 1

For targe t 1, the pattern of activations provides good examples of

inte rpretation principles. All three sensors in Row I have activated in

a noticeable stairs tep pattern . This indicates that the target traveled

somewhere al ong Row I itself as though the sensors were deployed along a

road as in a trail/road monitoring situation. In this case the target

was traveling perpendicular to what we consider the primary watch direction

of the grid. Because sensor 5 (the internal sensor) did not activate , you

should be able to conclude that the target probabl y did not penetrate the

grid , but merely traveled along the top as shown in the target 1 path of

Figure A. The last two sensors to activate (sensors 6 and 9) are the last

sensors on the right -hand side of Rows II and III respectively. Again , since only outer sensors activated, you would probabl y be ri ght in conclud-

~~~~~ t~~~~~~~et did not penetra te the inside _of the grid. Also , because of the regular stairs tep pattern formed by sensors 1 , 2, and 3, it can be concluded that the targ~~ passed these sensors one r.jght after

the other at a relativ~~~~pnstant~~p~ed.

26 

- - ——- —-~~~ -~~~ - ---- ---•- ----~~~—
r -

~~~ 

_________

It is important also to note that each sensor activated for about the

same period of time (2 minutes). Th is indicates that the target had

entered the detection range of each - .ensor for about the same period of

time . Of more importance , this condition implies that the target travel ed

the same d i stance a~ay from each senspr. If the activation lengths had

diffe re d , this woul d imply that the target traveled cl osest to the sensor

wi th the longest activation pattern . We can say this because gain setting,

which i s i mpor tant in de terminin g detection ramp , is in the medium range

for all the sensors . Keep in mind , however , that other factors can also

influence detection range such as the seismic response characteristics

of the ground , the environmental/weather factors , and the condition of

the equi pment.

Review Period - Take a few minutes now and study target 1 and the row

patching technique. Start with the X -T plot and retrace the path of

target 1 on the gri d and try to visualize the relationships that we

have jus t discussed.

b. Example 2 - Target 2

Turn your attention now to target 2. Fi rs t loo k at the X-T plct , then the grid. The activations are in which row(s)? _____ Sensor 1 of

Row I shows the fi rst activations. The sensor which shows the fi rst

activations wi]j us u al yte you_ the closest point in the grid where

a targe t fi rs t made con tact wi th the grid by entering or going around

the grid. The wo rd usually is used here because in the fiel d another

sensor rnay activate firs t even though i t is further away from the target

because of detection range di fferences . Next , sensor 5 of Row II

acti vated and was followed by sensor 9 of Row III. This indi cates that

the target moved out of Row II and into Row III.

YOU 1-lUST USE JUDG~

1ENT IN TRACING A TARGETS ’

PATH AND BE ABLE TO USE CLUES FROM THE LENGTH

OF ACTIVATIONS.

It is important to unders tand the concept of single targets versus

multiple targets trav~jj~~j~rough the grid. Try the following exercise

while still lookin g at the XLI plot. Imagine that target 1 and target 2

are starti ng at the same time and progressing through the gri d at the

same time . In your mind , su per i mpose target 2 on to target 1 so that the

PEN 1 ACTIVATIONS OVERLAP. Now , actual l y fill in the remaining activations of target 2 wi th your pencil or pen. Be careful as you fill in

the activations to reproduce the same time relationships of target 2.

Now l ook at the combined activations of both targets carefully. If

you had just now seen these activations for the firs t time woul d you be

able to tel l that two targets were involved? Woul d you have been able

27

I - -
--- ~ --- - ----- --- ----- -- --- -

to separa te the one long activation attern on pen 9 into two targets?

Remember , several targe ts can travel through the grid at the same time

or close to the same time especially during a battl e situation. If an

intruder tried this tacti c do you think that you would be able to distinguish and report on the separate targets?

Review Period - Take a few minutes and study the combined acti vation

patterns in relation to the path s of these separate targets on the grid.

c. Example 3 - Target 3

Look at targe t 3 on the X-T plot. Line up your UGS ruler on the X-T

p lot direc tl y under targe t 3. Using your UGS ruler to hel p you with your

answer , which pens have activated? It is easy to see that sensors

in all th ree rows have activa ted. Again it would be safe to assume that

the target prob ab ly passe d through the ent i re~grid.

Noti ce the di fferences in the lengths of the various activation

patterns on the X-T plot. Generally, you can use this as a guide in

giving you an idea as to how close the target came to the various sensors . Compare the lengths of the activations on pens 3 and 8. The activation

length on pen 8 is about one minute longer than the one on pen 3. Since

the gain setting of all the sensors i s the same ,

YOU CAN SAFELY CONCLUDE THAT THE TARGET PASSED

CLOSER TO THE SENSOR WITH THE LONGEST ACTIVATION

PATTERN .

In the exam ple d iscus sed , the target probably passed closer to

sensor _____ than it did to sensor 3. Look at the target path in Figure

A and check where the target did pass.

Sensors 5 and 6 activated and it would be a reasonable assumption

that they are va lid acti vations associated with target 3. Do you think

you can concl ude the same about the four activations on pen 1? Probably

not. Chances are the activations on pen 1 are unrel ated to target 3 and

probably do not even involve a target. Sensor 1 may be starting to malfunction and if it becomes a “talker ” it w ill run down its power supply.

Look at the X-T plot and answer the following question for the pairs

of sensors listed below . The target passed closer to which sensor?

Tar get 3: Sensor 5 or Sensor 6? _____

Target 3: Sensor 3 or Sensor 5? _____

Now superimpose target 2 wh i ch you studied previously onto target 3

so that they start i r-i the same time frame . Wi th your pencil or pen , fill

28

-

— — -1____ ~~~~~~~~~ —---- — — -
in the target 2 activations in the sm e manner that you did previously with

target 1. This will take you several minutes to do as before . Now took

at the combined activations carefully. If you had just now seen these

acti vations for the firs t time , woul d you be able to tell that two targets

were involved? Lay your job aid on the X-T plot. Does the job aid help

in distingu ishing these targets?

Review Period - Take a few minutes and study the combined activation patterns

in relation to the paths of these separate targets as shown on the grid.

d . Example 5 - Artillery and Helicopter Activity

Look in the upper portion of the X-T plot and you will see a typical

activation pattern for artillery and hel i copter acti vi ty. Could you have

recognized them if they had not been annotated? An artillery shellbur s t

usually shows as a thin band of one or two activations per sensor wi th

the activations occur ing at the same time . Helicopter activity is different in that there are groupings of two or more activations per sensor

occuring at the same time . There are more activations because the helicopter is in the area longer and therefore the disturbance created by the

helicopter has an effect on the sensors for a longer period of time .

For th is exercise circl e and anno tate on your X-T plot but do not

report artillery or helicopter activity as targets . It is i mportant for

you to know what it looks like on an X— T plot so you do not report this

activity as targets . Study the examp les shown .

How Do You Est imate Distance?

Once you have detected a target on the X-T plot , number it , and

draw what you think is the path of the target on the grid, you must

estimate the distance of tha t path . This , of course , is step _____ of

the seven-step procedure that you learned previously.

For this task you will find it helpful to use the other side of the

UGS ruler . Take your UGS ruler and look for the scale which is l abeled “Distance i n Meters ” as shown below .

- I - I -

100 200 300 400 500 600 100 800 900 1000 1100 1290 1300 1400 1500

DISTANCE IN METERS

UGS RULER ~31fl~ 50(1

SIIANIN ~nin~ s9n NI 3WII

7 2 3 4 5 6 1 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 

~~ ~

., L

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

29

L
To use this scale , place it along a ‘ ar get path that you have drawn on a

gri d and measure the length of the p,’th to the nearest 50 meters . Remem ber

that the path of an actual target tr€ veling across country will never be

a straight line because of turns in the hori zontal direction to avoid

obstacles and inclines (hillsTfn the vertical direct~on.

BECAUSE OF HILLS AND OBSTACLE AVOIDANCE , ALWAY S

OVER-ESTIMAT E THE DISTANCE IN METERS THAT YOU

GET FROM THE UGS RULER .

Usin g your UGS ruler , measure the target paths drawn in Fi gure A and

check your est i ma te wi th the answe rs already provided. If 

~~~~ 

answers

differ from the given answers by over 100 meters , consul t the Training

Moni tor. ___________

How Do You Detennine the M id-Point Time Di fference?

As you learned previously, an estimate of target speed F

~

’ H

L~ tmade only by knowing the: (1) distance that the H ~ rget trave led thro ugh or around the grid and (2) the

amount of ti me that the targe t spent in the grid. Step 3 L asks for your ____ 

as to whether you feel ‘ .iu in fact

have detected a real target. Step 4 require s you to record H : the numbers of the firs t and _____ 

sensors which activated I—~~ c

for the target. ~~ - -

Step 5 requires you to find and mark (on the X-T plot) L_ the mid —points of the activation patterns of the first and —

last senso rs which activated ari d record the time difference. ~~ All cons i dere d , the time diffe rence between these two mid- ~~~~~ ~~

points probably gives you the best estimate of how long the ~ target was in the grid than any other method. Any easy ~~~ ~~ way to estima te th is mid point t i me d i fference is to use a U’

scale . -

Check the scale on your UGS ruler which is l abeled ~~~~~ ~~ 

“

“Time in UGS Ruler Minutes ” . An example is shown on the

ri ght . The scale extends from 0 to 30 minutes and should

be adequate for measuring most activation patterns that ~~~~~

you will be wo rking with . To use this scale simply measure — 

-

the distance between the two midpoints as though it were a ruler and you were measuring inches. Read the time to ~~~~~ —

the nearest 1/2 minute . This answer wou ld be recorded

in the Step blank.

Take a few minutes now and check the midpoints of the

firs t and last sensors of targets 1 , 2 , and 3 on the X-T —

plot. 1~

leasure the m i dpoint time differences with your ~~~~~

UGS ruler and see how close you come to the school solutions ~~~~~

30
provided in Figure A. You may feel that using the UGS ruler for this measurement is not needed because the answe rs can be si ght-read , but remember that

these learning targets were intentionally simplified for training purposes

and fiel d-collected targets will be more difficult. Also , you will make

fewer mistakes if you use the ruler. In the event that your answers differ

by over 1/2 minute from the given answers , consult the Training Monitor.

If your answers differ by over _____ minutes from the given answers consult

the Training Monitor.

How Do You Calculate Speed?

Step 6 requires an esti mated average speed concerning the type of

target whether vehicle or personnel . In order to save time arid avoid

ari thmetic errors , you shoul d use the Speed Table whi ch you have already

been taught to use.

How Do You Determine Target Type?

Step 7 asks that a judgment be made concerning the probabl e target

type . For this particular exercise it will not be necessary to do this.

Usual ly an estimate of target type is based upon an estimated speed greater or less than 150 me ters/minute . Since you will be reporting estimated

speed , we can score these later using any desired standard .

Mon i tor Check

Before you beg in Part II bel ow , take your materials to the monitor

and take a short break.

-: 

31 

~~~~~~~~~~
PART II - PRACTICE TARGETS

Figure C presents an X-T plo~ 01 operationally collected targets for

you to practice on using the patching technique and principles that you

have just learned. After you are finished reading this booklet , study

this X-T plot for targets starting at the bottom and working upwards in

the order you woul d see them on a field recorder. For each target that

you detect report on it in Fi gure D .

Fi gure D presents a blank 9-sensor grid Target Log. Pul l it out of

your booklet , wri te your name in the upper ri9ht-hand corner and place it

in a handy area . Take your other Target Log (Figure A), fol d it in hal f ,

and place it under your papers where it will not get in the way . As you

report on each target , remember to circle all the activations associated

with that tar get by row , num ber aijyour circles , and fill in the sevenstep procedure in the Figure 0 Target Log .

USE ALL THREE FUNCTIONS OF YOUR UGS RULER:

SENSOR ROW GROUPS , DISTANCE MEASUREMENT ,

AND TIME MEASUREMENT .

As you work through these operationally-collected practice targets ,

remember that they are not the sterile , i deal examples wh i ch you have

just worked with . THE PRACTICE TARGETS CONTAIN VARIOUS SOURCES OF BACKGROUND NOISE AND THE EFFECTS OF MALFUNCTIONING SENSORS AND VARIATIONS

IN SENSOR DETECTION RANGE DUE TO GAIN SETTING , GROUND/TERRAIN CONDITIONS

AND WEATHER . To be ab le to do a good UGS report i ng job , you must learn

how to detect and extract target info rmation from X-T plots collected in

the field.

Consul t the Training Monitor when you feel the need. When you are

f i nished wit h your p racti ce targets , take your work to the Training

Monitor. He will determine whether you n

~ed additional practice and/or

rev i ew.

32

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(practice targets).

33

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35

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ç - -

~:~~~~( 

_J

: , 7 _i. 8 9 ‘

~ ~ - 7 ~~~~~ - .

- _ -,

/

STEP 1 STEP 2 ~

;i i ;i’ ~ STEP 4 STEI’ 5 STEP 6 STEP 7 -

ESTJ MA Tr ‘ CON I l)EN ( E FL RST -

D [STANCI-. low —~ t I I ~I AND l AST MI D—I OIN I - .

TARGET (METERS ) 25 50/50 SENSORS TIME (miii ESTIMATEI TARGET

_N UMIWR — - - - - 

. 7~~,1O0 -

~ Lv A-~

-u~ 1)IJ- t- ERENC _S1~

EJ

~

D TYPE

____ i/so - 

1, 7 7 /(~4L 

-

_____ 

1

~

7OO -- _________ ____ ____

________ —-__ _____ /1 ~oo ____

7 __ ____ 

Z~~3

_____ _________ 

*

Figure F. Target log (school solution ) .

• 36 

-- - - -- 1-- - 

- -

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

,
__ - --- -

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

APPENDIX B

TARGET QUALITY DISTRIBUTION--NORFOLK SCENARIOS a

Field 1 Field 2

T~~p~~ Tota l

r,ooi

b FairC poor

d Good Fai r Poor

5 4 6 A 7 3 2 28

8 4 2 B 7 6 1 28

5 4 3 C 7 5 3 27

Trai ning 0 Training

5 7 4 E 6 4 4 30

23 20 15 27 18 10 113

aFrom Pilette , S., Biggs , B., Edw ards, L., & Marti nek , H. Optimum

patching technique for seismi c sensors employed in a gri d array . AR!

Technical Pape r 320 , Augus t 1978 .

bFlve targets were detected between 6Th and 100% of the time . These are

called good or easily detected targets .

CFj~~ targets were detected between 33% and 66% of the time . These are

of medi um difficulty.

lx targets were detected between 0% and 32% of the time . These are

difficult targets.

eExtra targets unassessed.

1

_________________________________________________________ •
APPEN DI X C

ILLUS T RA TION OF SENSOR GRID REVE RSAL

TARGET ~ SENSOR FIELD X

1.’

’ 3 .

4. 5. ’ 6 -

7’ 8

In the reversal the following Sensors were transposed:

Sensor 1 wi th Sensor 3

Sensor 4 wi th Sensor 6

Sensor 7 w ith Sensor 9

This reversal produced the grid below :

SENSOR FIELD X-REVERSED

1 • 2~~ ~~~ 3.

.

•

: 

•

.

• 

1

~~~~~~~~r TT i 

-- -_-.--—- - ---- _--------- _

~

L - --~~ L__ T~~~~~~~ _

~~ 

1 _ ~_.
r

~ ~ - 

-

~~~~~

APP EN ~flX 0

TARGET QUALITY DISIRIBUTION FOR TARGETS PRESENTED IN THIS STUDY

a .b c Good Fair Poor

Scenario

1 3 1 2

2 3 3 1

HIGH 3 4 4 0

TARGET 4 3 1 3

ACTIVITY 5 2 3 3

6 2 4 0

7 3 3 1

8 1 1 0

9 2 1 0

LOW 10 2 0 0

TARGET 11 1 0 1

ACTIVITY 12 2 0 0

13 1 0 1

14 1 1 0

30 22 12

a Targets were detected between 67. and 100% of the time . These are called

good or easily detected targets .

b Tar~

jets were detected between 33~ and 66. of the time . These are of

medium difficulty .

c Targets were de tected hett-i~en 0 and 32 . of the time . These are diffi cult

targe ts .

41

A 

~~~~~~~~~~~~~~~~~~~~~~~~~ - —
p.— - 

~~~~~~~~~~~~~~~~~~~~~ — —=------ --- 

— - 

- - 

APPENDI X E

ORIEN TATIO N BRIEFING

Monitor: Paraphrase the following:

I want to wel come everyone here today and thank you for coming. We

are glad that you could make it and can participa te in the exercises we

have planned. We think you will find it worthwhile. You will be participating in a fi ve—da y program and we will be spending the next several

• hours briefing you and giving you an orientation as to what it is all

about . Before going any further I want to introduce myself and my associates and find out who you are .

- Introductions -

Our purpose in coming nere is to eval uate , with your assistance , several different display/workload conditions using seismi c sensors

deployed in a grid. We have been asked by the Army Research Insti tute

for the Behaviora l and Social Sciences and the Department of the Army

to administer this exercise to you. The Army is interested in the

development of improved displays of unattended ground sensors to maxi -

mize information output and make the job easier for you. Your task in

this study will be to act as a sensor operator and interpret various

X-T plot presentations . Many of the skills you have acqui red in school

and on the job will apply to these tasks , however, some of the patching techniques will be new to you and details such as measurement and

reporting procedures will differ. In these cases, training and instructions will be provided. If at any time during your work wi th us you

do not unders tand something or you are not sure of what you are to do 

ASK. You will not be pena lized and asking might prevent your

having to repeat some of your work . We will be using simulated RO-376

dri ve mechanisms . if any of the equipment appears to be malfunctioning,

inform one of us i niiiediately.

Previous studi es of this kind have dealt primarily with sensor

strings emplaced along roads , trails , or other infiltration routes . Here, we are applying seismic sensors to an area intrusion problem . In such a situation , we would have sensor fields emplaced over a wide

geographical area that an enemy force would utilize should he elect

to maneuver his forces cross-country and not along the existing road

netwo rk . Such a situati on coul d be expected in a mid-intensity conflict in Western Europe . This type of sensor field woul d be used to

help detect and identify different tactical maneuvers such as recon—

naissance probes , feints , or major attacks and is referred to as a Gated

Array .

43 ____________
I

For our experiment, we have tapt-d actual sensor activations from a

Gated Array during field exercises using various types of targets . The

target activations we re collected under simulated battlefield conditions

complete wi th noise activations produced by artillery fi re, helicopters , and wind. These tapes will not be played back to you in real time , but

in the form of pre-prepared X-T plot scenarios . You will interpret these

scenarios and extract information using our procedures and forms . Since

we know where and when target activations actually occurred, we can score

your reports for accuracy and thereby determine which patching technique

can best be used in this particular situation.

Each of you will participate three times this week. Your NCO IC will

post the schedule each day . During that time , you will be given training

on the row patching technique and multi-displ ay training. During the

program you will be given appropriate breaks , lunch , etc. If you cannot

be here during the time in which you are scheduled , tell us so we can

reschedule you. You must be here for all scheduled times or we cannot

use your results .

I would like to emphasize that we are not giving a test to see how

good an operator you are . The purpose of this study is to determine what

are the effects of different multi-display workload conditions . We are

not interested in how good you are as an operator. However , you and your

superiors are interested in how good you are . I am sure they will not

base the next promotion on how well you do on these practical exercises . Still , these activations are actual activations recorded in the field and

your accuracy in interpreting is one indication or example of what you

can do. You will be able to compare what you can do to what others did

as a group. You will be able to get your score and the gro u p average

from your coni-nanding officer. He will be abl e to objectively assess you

against the others on this one sample of one of your duties . However , there are no standards of performance -- even if you do worse than everyone you still could be a competent operator.

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

ability and try to ma ke sense out of what sometimes mi ght appear to you

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

records as realistic as we could.

You arc important because you as a group represent the hundreds of

specialists that have graduated and will graduate from the UGS school

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

personnel will be partly infl uenced based upon what ~ can do.

Monito r: Begin the briefing on grid deployment patterns .

44
APPEND i X F

INTRODUCTION TO THE GRI t DEPLOYMENT PATTERN

(LECTURE/DISCUSSION)

The Grid array consists of unattended ground sensors (UGS) deployed

in a mat rix wi thin a designated field area as opposed to the string

pattern in which UGS are deployed in sequential ali gnment along a road- way. The gri d array can be used for area intrusion surveillance probl ems

encompassing entire border areas or smaller gate (gap) areas where coverage by radar or other means is limited or not feasible. It is desi gned to

max imize the probability of detecting and acquiring enemy forces intruding

in any portion or in any direction within a covered geographica l area.

The UGS in the g’-’id array are deployed in a systematic way with pre -planried

distances between the sensors so that information extraction is enhanced.

For this exercise we are utilizing a sensor grid , consisting of 9 sensors , each sensor is 500 meters apart . X -T plot readouts of various

target runs through this sensor gri d will be presented to you. Your task

wi ll be to detect these targets , track their path through the sensor grid , and provide further inforiiiation about them. You have already received

some information concerning this task. At this time we wou ld like to

provi de you with further information which should aid you in monitoring

sensors in the sensor grid.

After you have detected what you believe is a target, your next

objective is to chart or trace its path across the sensor grid. In the

past , when you have worked with sensor strings , targets coming down a

road will generally activate all the sensors in order. However , in a

grid formation , the targets may come from any direction and take any

course across the grid. They will also come closer to some sensors than

they will to other sensors . This presents more of an interpretation

problem to the monit or.

We have prepared some examples of targets entering the sensor grid

from different angles and taking different paths through the grid. We

also have copies of the sensor acti vations caused by these targets .

Example 1 - Here is a target entering a gri d , and crossing the firs t line

of sensors , passing di rectly over one of them .

2

~~~ 3 • ’

Activations would firs t appea r on the middle sensor. As the target

proceeds the sensors to the right and left woul d activate for a shorter

45 
peri od of time . The sensors to the i ight and left wou ld cease activating before the middle sensor thus the activations woul d appear as below:

1 2 3

Example 2 - A target traveling in parallel with a line of sensors would

‘I

4 ’ 5 ’ 6~ -

appear like this on the X-T plot.

6

5

4

This would be very similar to the activation of a sensor string with

a stair-step pattern . All sensors wou ld activate for approximately the

sable length of time .

Example 3 — Shows a target approaching a line of sensors at an oblique angle.

Here the left hand sensor would activate fi rst followed by ~

.he middl e

sensor and the right -hand sensor , however , the middl e sensor woul d be

activated for a longer time because the target woul d come closest to it.

9

8

7

In all three of the above examples , other groups of sensors in the

grid woul d,in the same way , indicate the path of the target as it traveled

the grid. A good genera l rule to remember when monitoring a sensor gri d

is to look at the overall pattern of the sensors being activated , and then

make a determinati on from this overall pa ttern , where the target is traveling.

46

- 

—- -—----- -.-—--------- - . _ • ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
At times , there may be more thai’ one target present in the sensor

field. ?-lonitors should be abl e to & tect this again by studying the

overal l pattern of activations

Example: 10 . 11 • 12 ‘

l 3~ l4~ 15

In this example , with sensors activating on the left and right but

not in the middle , it must be assumed that two targets are present. In

these situations it is important to take note of sensors that are not

activating as well as sensors that are activa ting.

13 14 15

10 11 12

47

_______________________ —----~~~~‘- --- ---~~~- - _— - - ---.
- 

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

APPEND I X G

TEST PROCEDURL TRAINING

Our purpose in coming here this week is to eva luate several display and

target conditions for seismi c sensors patched to an R0376 readout device . We want to determi ne how different display and target activity conditions

affect your ability to detect and report on targets . You are all familiar

wi th th~ idea of deploying sensors in a string confi guration along a road.

Now you will be working with sensors deployed in a grid confi guration and

in a field such as that shown in the top half of Figure 1

Pull Fi gure 1 and Figure 2 out of this booklet and lay them on your

desk where you can see both of them clearly. As you can see , Fi gure 1

shows 9 sensors deployed in a gri d which is 1 000 meters on a side . Compare

this with Figure 2 which shows 24 sensors also deployed in a gri d 1000

meters on a side. The sensor identifi cation numbers are shown in both

fi gures . In an operational situation , grids this size coul d be a small

section out of a long sensor network or they cou ld be place d between natural barriers . For our purposes , assume th at each gri d is located in a

flat partialjy wooded field between rugged terrain on the left and marshy

terrain on the ri ght.

The expected direction of enemy approach is from top to bottom. As

you can see , target 1 in both gri ds has come from the expected direction

and has passed throug h the center of the sensor field. In the case of

the 9—sensor grid, the target has passed over sensors 11 , 15 , and 14. In

the case of the 24 -sensor grid , at least three more sensors are invol ved.

As you can see by inspection , the target has passed over sensor 11 ,

between sensors 9 and 23 , and then over sensors 15 , 13 , and 14. These

additional sensors may help when reporting on a target from an X-T plot.

The bottom half of Figures 1 and 2 shows bl ank spaces and a se ven

step procedure which you will use to report on targets .

YOUR JOB DURING THIS EXERCISE WILL BE TO FIND

TARGET S ON X-T PAPER AND FOR EACH ONE THAT YOU

FIND , FILL IN THE BLANKS FOR THE SEVEN STEPS .

You will be working with X-T chart paper and targets similar to that

shown in Figure 3 (seco n d to the last page). Study Figure 3. Notice the

pen/ ID chart at the side showing that the X-T p

~g numbers correspond to

the same sensor ~~~~ numbers .

• At this time we will define what we mean by the word “target ’ . A

target is any vehicle or personnel activity in the field which is distinguishable from other personnel or vehicle activity . For example , three

49

a

P!~ CEDING P~3 BId~

MC-NOT tIU4~D

—-- —- --- --—-------- -- •- —.----- ---- - i•~~~~~~~_ —-- ~~ — .
r ---

~

---

~~~~

- - —•- -—--- --- --- 

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

Target 1

- I_________ 1 /11 41

/

W U-,

v

_

I V)

Ci

~

1 

49 fl ~ 10’

____ 

~14

I I ‘ ‘ ‘ I I

0 ~ -

~u J

~~U 4 J ~ ~ 0 600 70~ 800 900 - 1000

u[u’ ,s

S F~~ 1 ~; L ’ 

~ 

‘ rslLp 5 STEP 6 STEP 7

I I—I ~~~~

I ‘\ FLU I U —b III I LA ST NI I)— POT N I

TA ’ ; T ~IS~i-~ .L ,!)/~U, ~

[U~) U

~ 

TTNII (iiiin ) ESTIMATED TARGET

~

J i i ,

~~~ I ) ‘U A (j1~

j

~~~ ) UI 1 I L ~ [N LL SPELD TYPE

1050 ()

~~~~ //j~~ _______ 

/ 7/ — ____

I _ _ _ _ _ _

Figure 1. 9—sensor target log.

50

________________ - -~~~~~~~~~~~~~~~

• 

~~~~~~~~~~~~~~
___ ---——-~~~__-

~~~ --~~~~ —-- • -

~~

- -• •-

~~~

-— - - -

T~ — güt 1

(I - ———~~

—~~~- - C -—— ~~~— — -~~ UI 8 4

0 () 0

3 9 23 5

.

~~ v_I 1/)

-

~ ‘ I 0 0

lcf

L~

)

‘/,

16

~

12 19 13

o u r

—/-- -)

2 1 14 22 6

I I I I I I I ‘ 1 Li IOu) 200 3~id 400 iii 600 700 800 900 1000

M( Il S

STEP 1 ST[P 2 s I l P ~ STEP 4 STEP 5 STEP 6 STEP 7

cu~~Iuua ;E FiRST AND

ESTIt-tAT[D LuW -—~l l l (;l I LAST MID-POINT

TARGET DISTAN CE : 25,!,O/ 5U, SENSORS TIE-1[ (nin) ESTIMATED TARGET

NUM ULR (iuIeLers ) /SJIJU A C1I VA rLU DIF IEREN CE — SPEED TYPE

___ - / v.50 J

~~4- C~ L

~ i4L~ 

2 c / 31 ______

Figure 2. 24-sensor target log.

51
tanks 50 meters apart. travel in 9 in a convoy formation woul d be one target

as wou ld a tank traveling alone. Th - ~e two targets m ay enter different

sections of the gri d simultaneous ly t-r at different times . Because their

activation patterns can be separated from one another , they are classified

as sepa rate targets .

Step 1 on the Target Lo

~ - TAR GET NUMBER

Target acti vations are presented in Figure 3 for the same target as

they m i ght occur for bo th the 9-sensor and 24-sensor grids. You will

not ice that the target activations are circled and numbered. Circle all

the target’ s activations and number them with the number of that target.

Since this is the firs t tar get , the activations caused by this target are

la bele d target 1 and a number 1 is recorde d in Step 1 of the Target Log

as shown in both the 9—sensor grid and 24—sensor grid.

Step 2 on the Target Log - ESTIMATED DISTANCE (Meters)

Study the charactc -ris tics of the sensor activations and draw the

probable path of the target through the sensor fiel d on the Target Log

grid. Estimate the total distance (in meters ) that the target traveled

through the sensor fiel d using the distance scal e shown . Estimate the

distance to the nearest 50 meters - for example , 200 or 250 meters . In

the case of Tar t l , the path ~~~~~~~~~~~~~~~~~ been on botiyrids. The

estimateo distance -is about 1050 meters and this has been reco rded in the

Step 2 blanks .

St

~j~~~ on the Target Log - CONFIDENCE LOW HIGH

T hi s s te p seeks to answe r the question , ‘How confi dent are you that

what you tUin k is a target really is a target?” Reco rd your confi dence

using the following four -point scale:

l00

~ - This means you are positive or certain.

75 - Thi s means you are highly confident , but not pos itive .

50/50 - This moans that you think it probably is a target , but

you ar e uncer ta i n — i t may not be a tar get .

25 • — T Il ls ~‘a~i

~ that you have only a suspicion , but it should

be reco rded and checked out. You have low confi dence

that this is a target.

A 100 . - confI dence ild ~ alrea dy been p lace d in this column on the Target Log.

— 

52

____ ___ ~~~~~~~~~-

~ -- — -~~~~:=-

_ - - —- —
Step 4 on the Ta1·gc t Loq - Fii<ST AND t AST SENSORS ACTIVATED 

Record the sen$or numbe r of the first sensor which activated \'lhen the 

target entered the gri d and the Jast sensor \'lh i ch activated when the target 

left the grid. As shO\'IIi fo r both the 9-sensor and 24-sensor grids, the 

first sensor is 11 t~ nd the last is 14 which is the same as pens 11 and 14 

on the X-T plot. Check this yourself by looking at the pen/ID chart on the 

right- hand side of Fig1.1re 3. This information is important because it will 

be used for the next steps. 

Step 5 on the Ta!·get Log - 11 -POINT TmE (Hin) DIFFERENCE 

On t he X-T plot, find the mid-point of the activation patterns for the 

first and last sensors. Now determine the time difference between the t\'10 

mid-points . This is done directly off the X-T ~art per as shown in 

Figure 3 for bott1 t he 9-sensor and 24-sensor grids. Remember, there are 

2 minutes bet~<J n l i nes (l"C\·Js ) on the X-T chart paper. Estimate this time 

to the nearest half mi nut e, for example 3 or 3.5 minutes. For Target 1 the 

n:id-point time difference is minutes. Check your answer with tiie 

appropri ate Target Logs for the two grid sizes. If you missed it, reread 

this section and/or see the Training Monitor. 

Step 6 on the Targe t Log - STI~~TED SPEED 

Havi ng an est i wat2 of ti:c time that a target traveled through the 

sensor f ield and ~ di st "nce t hat was traveled wi ll permit you to get an 

estimate of t l1e s pcGd of t he target. Only an estimate is possible, hO\'Iever. 

si nce_ycu \·Jill not kn ov{._f_ J:.. ~! e hO'II c1ose t he target traveled to any of 

tile en sor . It i s poss i ble to obtain a more accurate estimate of speed 

\'lhen the sensors are d~ loye d along a road because the target is normally 

traveling on t he road and t he distance between the sensor and the road is 

knovm. 

An estimate of speed can be obtained by using the speed table provided 

for this purpose. The speed table is enclosed in plastic and will always 

remain at your desk . To use t he s peed tab1e, find the time column (using 

the answe r from Step 5) along the top. Line this up with the distance ro\'1 

(using the ns\~er fro1a Step 2) along the left-hand side . The place where 

the column and ro1·1 conver ge gi ves you the speed. In t he case of target 1 

t he speed is . Check your answer with the one a 1 ready provided in 

the Targe t Logs:-! f you missed it, reread the instructions and/or see the 

Training Mon i tor. 

St ep 7 .on tile Targe t Log - TARGET TYPE 

Step 7 requires a judgment as to whether the target is vehicle or 

pe rsonnel. As a rul e , if the t arget is traveling 150 meters per minute 

or fas ter, label it "IJ " for vehicle. Any speeds lower than this are 

us ually labe l ed "P" fo r personnel. but of course this judgment could be 

incorrect si nce it could also be a sl0\'1 novi ng vehicle. 

53 \ 

~' 
..... 

...., 

QJ 

0'1 

s... 

t1l 

.... 

11;) 

.... 

. I 

; .. , ! ..., 

I 

'-' 

i 

I 

! 

~ '"' 

. 

r~ 

! I 

1.··1 , '-' 

: I 

I ' 

I i 

I 

~ 

I 

_, 

I 

I 

,,. ~· I 

I 

I. 

i I 

!· 

I 

I ! o I 

' I . 

I 

' I I 

' I I 

I I 

... 

I 

2 I, 

... ; ·: 

.. 

- ; 

; . .. 

:2 :.1 

~ ~ 

; 

6 ·a 0 12 ;!' ~o : .. :J;; 

I 

~L .. 

. ··. 

:r! ;'.: ... .. , 

. . 

. :ni mltes - I 

I 

I 

... . .I 

:·IJ ~() _ , 

. . 

. . . . . . . . . .. . . . . .. . . . 

'-· . 

. : . : - : : : , ; ; : ·~ 

; I 

Figure 3. 9- and 24-sensor grids. 

54 

Se·1 c; or J 

Pen 10 -- 1 1 

2 2 

3 3 

4 4 

::> 5 

6 G 

7 7 

8 8 

9 9 

10 10 

l1 11 

12 12 

13 13 

14 14 

15 15 

16 16 

17 17 

18 ~8 

19 19 

20 20 

21 21 

22 22 

23 23 
' ' ' 

.. ,: 

! 

I ..., I I 

I "" : !. y ' ' 

~ 

. 

rl "' i 

• ..., . , . 

I "" I 

"" ! 

y 

I 

I l 

.. 

I M 'f ..... 

Q) ·-

! l ~ ~· TT . ~ ·~ 

-· ; ___ : __ : .. ;_ . 

~ : ~ ·ti: .... . . . : : . . 

a: 10 

. . . .. .. 

12 

. I .1-1 16: 

--·:--·-·-. 

'"I ~() 

._. 

·:.:. ~.:.. 

:''.! ' .,, 

.. ·;t. :tu :;o 

,• .· 

:--. 

c::n I : : ~ 

IU 

._ .,.. 

I 

! . : I 

I · 

' 

. . _ .. . :; .. : 

. . 

H 

: : : 

. . .. -· : ·: 

: ·: . . ·-

·- • . ! I . -. -: 

-~se 2~ n~or i6 L~g ~ 

I . 

:.·.· 

~c den~or ~<i ~ Loy 

· : : a rgc t 2 ~ · 

'------l--2--4-__G~..--_n w •{_"! . ;lUI 10 , : ,._, " 

Figure 4. 9- and 24-sensor grid logs. 

55 

- . 

Sensor 

P1~11 I D ~---

~ ~ 3 3 

4 4 

5 5 

6 6 

7 7 

8 8 

9 9 

10 10 

11 11 

12 12 

13 13 

14 14 

15 15 

16 16 

17 17 

18 18 

19 19 

20 20 

21 21 

22 22 

23 23 
N0\'1 you \'lill receive practice Oi! what you have just learned concerning 

the EVEN STEP target reporti ng proct dure. Study target 2 presented on the 

X-T plot in Figure 4. Target 2 is tt•e 9-sensor grid target. The sensor ID 

and pen number combinations ar~ the same as those for Figure 3. 

When you have completed all seven target reporting steps for target 2, 

start ~tlork·ing on target 3 of the 24-sensor grid. These tC!_rgets are not the ~ne! When you are finished with target 3 take your booklet to the Train1 ng No:1 itor. 

If you feel you need to vie~tl the test procedure before working the 

practice targets , 9_2 ! If ycu have any questions, ask the Training 

Monitor at Station 1 or Station 2. 

PART II - PRACTICE TARGETS 

Figure C presents an X-T plot of operationally collected targets for 

you to practice on using the patching technique and principles that you 

have just l earned. After you are finished reading this booklet, study the 

X-T plot for targets starting at the bottom and working up\'lards in the order 

you should see them on a field recorder. For each target that you detect, 

report on it in Figure D. · 

FigureD presents a blank 9-sensor grid Target Log. Pull it out of 

your booklet, ~ttri e your name in the upper right-hand corner and place it 

in a handy area. Take your other Target Log (Figure A), fold it in half, 

and place it under your papers \'/here it will not get in the way. As you 

report on each target, remember to circle all the activations associ a ted 

\'lith the targe_UL_rO\'I,_!!umber all your circles, and fill in the sevenstep procedure in the Figure D Target log. 

USE ALL THREE FUNCTIONS OF YOUR UGS RULER: 

SENSOR ROW GROUPS, DISTANCE MEASUREMENT, 

AND TIME MEASUREMENT. 

As you work through these operationally-collected practice targets, 

remember that the,; at·e not the sterile, ideal examples which you have just 

worked \·lith. THE PRACTICE TARGETS CONTAIN VARIOUS SOURCES OF BACKGROUND 

NOISE AND THE EFFECTS OF MALFUNCTIONING SENSORS AND VARIATIONS IN SENSOR 

DETECTION RANGE DUE TO GAIN SETTING, GROUND/TERRAIN CONDITIONS AND WEATHER. 

To be able to do a good UGS reporting job, you must learn how to detect 

and extract target information from X-T plots collected in the field. 

Consult the Train i ng i'1onitor \'/her. you feel the need. ~lhen you are 

finished \•lith your practice targets, take your work to the Training Monitor. 

He will detennine v1hether you need additional practice and/or review. 

56 
There is one add itiona l poin t wh ich must be made because it is an

impo rtant pa rt of your response. Each time that you draw the path of a

target through the grid , at the end of the target path draw an arrow

showing the direction that you think the target will continue to travel . Assume that yo ur target di rections and speed info rmation will be used by your CO for fi re control purp oses . 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~ ~~::
- -

APPEND IX H

MULTI -DISPLAY PROCEDURE TRAINING (LECTURE/DISCUSS ION )

Monitor: Paraphrase the following:

To familiarize you wi th the procedures needed to monitor one 30-pen , two 30-pen , and four 30—pen displ ays simultaneously using the seven—step

reporting procedure . Each person will have an opportunity to interpret

targets at each displ ay condition. Each 30-pen display contains three

9—sensor gri ds . The following diagram clarifies the grid arrangement.

Monitor: Draw this picture on the blackboard and paraphrase the following.

Display

Gri d 1 2 3

Pens 1 -9 1 1 - 1 9 21 -29

As you can see in the diagram there are three 9-sensor grids in each

display . For each displ ay :

Gri d 1 is composed of sensors 1-9 and uses the green Target Log.

(verify this)

Gri d 2 is composed of sensors 11- 1 9 and uses the yellow Target Log.

(veri fy this)

Grid 3 is composed of sensors 21 -29 and uses the salmo n Target Log.

( veri fy this )

Take the target logs located on your desk and study them in relation to

the th ree grids . Notice how the grids are geographically related to each

other.

When you detect a target you will report on it using the seven-step

procedure that you have already learned. However , there is one important

exception.

Fo r each target that you report, you mus t include a display letter

(A , B , C, or D). At this time , check to see wh i ch display or displays

you are working with . The purpose in you doing this is so that we know

wh ich display the target falls in. For each target that you report , therefore, always incl ude the displa y letter in which the target is

located.

59

- --

~

-

~

u-

~

—~~~

~~~~

T1

L ~~~~~~~~~~~~~~~~~~~~~~~~~ - - ~~~~~~~~~~~~~ 

- -

~~~~~:~~~~~~~- --—~

- -

~UUU L~~~~~i_~~~ -- ::t~~~~~~~iTJ~~~ ___ i___
The place to report the display letter is with the target n umber in

Step 1. Suppose the fifth target thet you have detected is located in

Displ ay A , Gri d 2. In Step 1 under the Target Number heading on the bl ue

Target Log, you woul d wri te A-S . Suppose that the tenth target that you

detect falls in Display B , Gri d 1. For this example , in Step 1 under the

Target Number heading of the (green/yel l ow/salmon) Target Log you woul d

w rite _________

f~bnito r: Go through several more examples to be sure everyone unders tands . Pa raphrase the following:

Find your job aid (UGS ruler). Turn to the side that has the 9-pen

scale. You wi ll be able to use this ruler effectively if you desire . The ru ler , as you have already learned, is divided int o three sections. Each

sectio n is a di ffe rent color and represents a different row of sensors .

This ruler can be used for each of the three grids that you will be working with in each display as shown in the diagram.

1 2 3 4 5 6 7 8 9 Grid l

11 12 13 14 15 16 17 18 19 Gri d 2

21 22 23 24 25 26 27 28 29 Gri d 3

Of course, when you are working with Gri d 1 , you will be working with

sensor 1-9. When you are working with Grid 2 , simpl y add 10 to each pent

sensor number and use the ruler as you have learned. When you are wo rking

with Gri d 3 simply add 20 to each pen/sensor number and use the ruler as

you have learned.

Monito r: Be sure that practice targets are in posi tion on all of the displays for a practice session . Paraphrase the follow ing:

You will now be given practice scenarios to work with . Detect and

report on two targets using the procedure that you have learned. After

you have completed renorting on these practice targets , take your target

log sheet or sheets to the training monitor. He will check your work

and determ ine if you need more practice targets .

After you have compl eted the practice targets you will be rotated

to a different display condition and you will report on two more targets . Since unde r some display conditions you will be monitoring more gri ds and

sensors there is a good chance that you will be detecting and reporting on more targets. As you work through the practice targets , think about

how yo u wou ld successfully hand le heavy target activity situations. In

60

_____________________________________ _____
- - -

~~~~~ _

these situations , your time would be at a p remium and you must know your

procedures 1-Jell. For example , if you ~

.uve detected three targets

simultaneously you woul d wan t to sha’e your time evenly with all th ree

ra ther than with just one of them. Time/task sharing is therefore

important.

Ronitor: Beg in the practice phase to comp lete the first cycl e of display

training and practices . Ro tate the students and complete cycle

2 and 3 in the same manner .

61

- - _ _ _ ~~~~~ ~~~~~~~~~~~ -- ~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
APPENDIX I

TARGET LOGS

63

CEDING ~~~~~ BLAPE NOT~~~~~~~~~~~~~~~~~~~~.

- - -~~~~~~~~~~ - - -_ - . - - ~~~~- 

~~~~~~~~~~ 

j
r - -_- — -- _

~~~~~~~

---_- - __-

~~~

_- __- — _-- __ 

G R I D I OPERATOR______________

Target Log

APPENDi X i—i

1 2 3 / 1

(

~ ~ 

Jf WHITE 

—0-- — -

~~~~~ .— -- —~ 

~ 4 5 6 NTAINOUS SWANP

STE P 1 STEP 2 STEP 3 STEP 4 STE P 5 STEP 6 STEP 7

DISPLAY ESTIMATE CONFID ENCE FIRS T

LETTER/ DISTANCE LoW —~-uIC}4 AND LAST ~

1I~~~ 0ThT

TARGET (METERS ) 25 soiso i SENSORS TIME (mm ESTIMATE TARGE T

NIJMBEJL __ ~~~~~~~~~~~~ j5~~~ (

~~~ lACT1VATED j)TLF~~~~~c ~~~~~~~~~ TYPE

_ __ 

*

~~~~~~ 

--_ —_- _. —-_

~~~

_

~~~~~

--- - -_- —- 

_________________ A
~ - -

~~~~~~~~~ -~—~ -- -~ 

_

~~ 

GRID I OPERATO R _______

Target Log

APPENDIX 1-2

/ - 

_

\ —— — — --— —- 0— - ——— — — —— —— a ( (

/

-

~~~~

‘- 11 12 13 \ ‘ 

-

~~~~~~ 

14 15 16 LAKES

Q--— --. -- — ---- ——— — -— 

I

~~~~~~~~~~ 17 18 19

/

STEP 1 STEP 2 STEP 3 STEP 4 STEP 5 STEP 6 STEP 7

DISPLAY ESTI~1ATE CONF.LDENdE FIRS T

LETTER! DISTANCE LO1J—~HIG1 AND LAST MID—POINT

TARGET (METERS) 25 50/30 SENSORS TIME (uiin ESTIMATE TARGE T

NUM P~

ER - _ ATLV ATE D 11

~~

REN~ ~~~~~ TYPE

iLii i;L:.:i *

-

~

- -_______
GRID II OPERATOR______

Target Log

APPENDIX ~-3 

— — — — — — — — - ,

‘ RUGGED

24 25 26 HILLS

~~~~

- ---------- 

~~~

- 

29

STEP 1 STEP 2 STEP 3 STEP 4 STEP 5 STEP 6 STEP 7

DISPLAY ESTIMATE CONFIDEN E FIRS T

LETTER/ DISTANCE LCW-

~-HIG AND LAST MID—POINT

TARGET (METERS ) 25 50/ 50 SENSOR S TIME (mm ESTIMATE TARGET

.NIJMBZL_ _______ 

~~s ioa . ACI1

~

1ATED... fl1EFF-.~~J

~ ~~~~ED TYPE

GE

-

~~~

-

~~~

—--

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

—--— 

_ —==--=-
___

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68

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