Technical Report 419 L

ANALYSIS OF MANUAL THREAT EVALUATIOkSAND WEAPONS ASSIGNMENT (TEWA) IN THEC AN/TSQ-73 AIR DEFENSE SYSTEM

0 Charles C. Jorgenien and Michael K. Strub

ARI FIELD UNIT AT FORT BLISS, TEXAS

SS-P2

U. S. Army

Research Institute for the Behavioral and Social Sciences

~ j October 1979, Approved for public rmleese; distrlbulon unlimited.

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REPORT DOCUMENTATION PAGE BEFORE C TO.7. REPORT NUMBER I MGOVT ACCESSION NO. S. RECIPIENT'S CATALOG NUMRER

Technical Report 419 -/ )"'

NALYSIS OF-MANUAL D REAT IDVALUATION ANDr,•. /-APONS-.SSMNIMENT IZEW IN THE A•NITS73 Z To r"- • .R F'.p],

WiR DEFEMRE SYSTEM . • . ... r-.'"-=- , _"•..""•* • '""" • "'lm 1. CONTRACT ORGRANT NUMmEP00'o)

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U.S. Air defense systemsFot lisHuman factors

i')l• Mnull weapons assignmentM.DITRI 1UI threat evaluation

20""J(. A" ACT renhw as ara eneswebb N noem aind 1l 6hl7 by loc* nueebni,)

As tactical ai.r threats have increased, so has the need to efficientlycoordinate ground defense. With the advent of computer aided command .Andcontrol systems, the identification of human strengths and limitations has

become critical to the success of the Army air defense mission.

7 SThe research reported in this paper was conducted in 2075 during thef

" ~~early development of the AN/TSQ-73 missile minder. The missile minder is \S, , I(Continue]) ,

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representative of a class cf emerging air defense systems which place unusualdemands on the processing capabilities of the human operator. The purpose of

the research was to evaluate human operator performance under realistic taskloading, aircraft threats, and manning configurationsi. As a result of thisstudy, procedures were developed which can effectively be applied to assessoperator performance ,"r.dr a wide variety of emerging air defense systems.The procedure can also be utilized to aid in firing doctrine development,assist human factors specification, and improve interoperability decisionsin linked air defense systems.

I

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Unclassified

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Tinhclnial Report 419

ANAYLSIS OF MANUAL THREAT EVALUATIONAND WEAPONS ASSIGNMENT (TEWA) IN THE

AN/TSQ-73 AIR DEFENSE SYSTEM

Chaeles C. Jorgensen and Michael H. Strub

Submitted by:Michael H. Strub, Chief

ARI FIELD UNIT AT FORT BLPSS, TEXAS

Approved by:

E. Ralph DueekPt.RSONNEL AND THAININGCESEARCH LABORATORY

U.S. ARMY RESEARCH INSTITUTE FOR THE BEHAVIORAL AND SOCIAL SCIENCES5001 Eisenhower Avenue, Alexandria, Virginia 22333

Office, Deputy Chief of Staff for PersonnelI' Department of the ArmyOctober 1979

Army Project Number Human Factors In2Q762722A?65 Air Defense Systems

Approved for public release; distribution unlimited.t ! iii

ARI Research Reports and Technical Reports are intended for sponsors ofR&D tasks and for other research and military agencies. Any findings readyfor implementation at the time of publicationare presented in the last partof the Brief. Upon completion of a major phase of the task, formal recom-mendations for official action normally are conveyed to appropriate militaryagencies by briefing or Disposition Form.

iv

'A

FOREWORD

The Army Research Institute Field Unit at Fort iliss is actively engagedin a research program designed to improve the evaluation of human per-formance in air defense 3ystems. As ta:tic..fl air threats have increased,so has the need to efficiently coordinate gro~und defense. With the ad-vent of computer-aided command and control systems, the identificationof human stv'engths and limitations has become critical to the success ofthe Army air defense mission.

The research reported in this paper was conducted in 1975 during theearly development of the AN/TSQ-73 missile minder. The missile minderrepresents a class of emerging air defense systems which place unusualdemands on the processing capabilities of the human operator. The pur-pose of the research was to evaluate human operator performance underrealistic task loading, aircraft threats, and manning configurations.As a result of this study, procedures were developed which can effec-tively be applied to assess operator performance under a wide varietyof emerging air defense systems. The procedure can also be utilized tohelp develop firing doctrine, assist human factors specification, andimprove interoperability decisions in linked air defense systems. Thisresearch is in response to requirements of Amy project 2Q762722A765and special needs of the U.S. Army Air Defense School (USAADS), FortBliss, Tex.

EPH ZNER

hnical Director

Ii

II

!, V

WqII 1

Analysis of Manual Threat Evaluation and Weapons Assig ient in theAN/TSQ-73 Air Defense System

BRIEF

Requirement:

To investigate human performance under varying air defense threats.

To determine human overload points requiring transition from manual toautomatic operational modes.

Procedure:

Air defense crews were evaluated over a six-day period under changingconditions of crew configuration, number of available fire units, andattacking aircraft threat. Switch action times were reccrded by theAN/TSQ-73 computer and matched against event times in predeterminedthreat scenarios. Analysis of operator actions utilized switchactuation latencies and operator errors (identified via incorrectswitch sequences). Results were subjected to advanced multiple regress-ion analysis modeling in order to generate predictive formulas foroperator performance under load.

Findings:

Hostile aircraft engagement latency averaged 3,47 minutes for systemcontact, identification, and weapon assignment during the simulatedcombat exercise. The chances were at least 50 percent that the air-craft would complete its run if it was in - major assault wave. Amanning configuration in which the officer implement, decisions directlythrough the weapon assignment console significantly improves assignmenttimes. Wave size of aircraft had the greatest effect on the weaponassignment operator although the aircraft identification operator timesincreased linearly as a function of the number of aircraft. Manualweapon assignment operators tended to overload at eight Pircraft andreaction times increased rapidly. Greater numbers of fire units improvedweapon assignment times but only if eight or more were available.Operator fatigue may be a siqnificant factor in weapon assignment underheavy task demands.

Utilization:

The techniques developed in this report can be applied in any air defensesystem having built in microprocessors that can record operator switchactions, such as the developing PATRIOT system. The resulting improvedestimates of operator actions and re~ction times can be applied tofiring doctrine evaluation, system software development, the man/machineinterface,-and interoperability studies involved in linking togethercommand and control systems.

vii.Preceding Page Blank

TABLE OF CONTENTS

I Introduction.......... ................................................. .1

II Procedure .. .. ....... . ........ .. ... . .. ...... .. ....... 3

III Results and Discussion. .. .. ........ .. ... . ....... . .....

IV Conclusions........ ...... . .... .. . .. .. .. .. .. .. .. ... 14

Appendix. .. ...... .. ... ........ ... ... .................................. 21

Distribution .. . . . . . . . . . . . . . . 25

LIST OF TABLES AND FIGURES

fable Accuracy Data (days 5 and 6).......................... 8

Figure 1 Experimental Design .................................. 5

Figure 2 Mean R'-action1 Times for ID as o Functionof Six Wave Sizaes ................................... 15

Figure 3 Mean Re~action Times~ for WA as a Functionof Six Wave Sizes................................... 16

I 4Figure 4 Mean Reaction Times and Estimated ReactionTimes for Total Reaction to a HostileAircraft as a Function of Wave Size................... 17

Figure 5 Best Fit Estimated ID Reaction Times asY.a Function of Day of Test............................ 18

Figure 6 Bist Fit Estimate of WA Reaction TimesasdFunction of Day of Test..................... 19

ix

I. INTRODUCTION

The Army is fielding a new air defense system for command and

control of Hawk and Hercules Fi,'• Units. Called the AN/TSQ-73 (Missile

Minder), the system contains software which will automatically perform

threat evaluations and weapon assignment (TEWA). The chief advantage

of the automatic TEWA is its speed in assigning hostile aircraft to

available fire units. Given sufficient time, it is likely that the

tactical director, by virtue of being able to take into account complex

information and recognize event patterns, would make more "intelligent"

TEWA than the machine since the machine TEWA is software limited.

The tactical director performing manual TEWA is subject to increased

information loading and stress as the number of aircraft in an attacking

wave increases. The present research sought to investigate human TEWA as

a function of wave size to assist in the determination cf a manual satura-

tion point. Such a point would suggest the level at which the system

should transition from manual/semi-automatic control to automatic control

as the intensity of a battle increases and the number of radar tasks

become too numerous for manual weapons assignment. While some argue for

exclusive manual/semi-automatic mode operation and others for an alli1,"

automatic mode, it is more likely that the system will reside in the manual/

semi-automatic mode until the operators and tactical directors are over-

loaded by the sheer volume of tracks requiring attention. At this point,

the operators and tactical directors would transfer the system to the

automatic mode but still maintain constant monitoring and override

capabilities.

'if

The purpose of this experiment was to collect baseline data from

which overload points could be determined. It was judged that such

points would be a function of the number of hostile aircraft in an

attacking wave or scenario, the number of fire units under direct control

of the Q-73, and the rate at which the attacking wave approaches. The

first two variables were systematically changed in the experiment, while

the third was fixed. Also, a key conmmand and control question concerned

whether the tactical director could coordinate activities better from behind

the console operators or at the weapons assignment console where he could

implement his fire unit assignment decisions directly through the console.

Thus, the third primary variable in the experiment was the manning

configuration. In one configuration the officer was behind the console

op~eraitors, while in the second configuration the tactical director-sat at

the weapons assignment console. Also included for control purposes were

three minor variables. They were the specific raid scenario, the kr*est

day, and the crew.

2

11. PROCEDURE

Personnel participating in the experiment (crews) consisted of

three Air Defense officers and six enlisted men from the US Arm~y Air

Defense School (USAADS) recently detailed to Ft MacArthur. CA, in

connection with the TACS/1ADS effort in 1975. (Pilot data were collected

from an "expert" team of one officer and two enlisted men who had been

assigned to the TACS/TADS project for over a year.) While the crews did

not receive a formal training program on the AN/TSQ-73, their arrival at

the testing site approximately three weeks prior to the start of the

experiment allowed sufficient time for them to become familiar with the

functions and operations which would be required of them in the experiment.

Although some practice effects were expected to be found over the six

experimental sessions, all crews were Judged to be qualified for operating

in the Q-73 at the start of the experiment.

The testing environment consisted of the interior of a prototype

Q-73 van. The principal items of equipment were two operator consoles,

identical in configuration, which were placed side by side at the front

of the van. The console on the left side was used for track identifica-

tions and the right console for weapon assignments. Other equipment

included cc'nuunication lines for cross talk between the simulated Group

73 and Battalion 73, and between the Battalion 73 and the fire units.

An officer from USAADS served as Group 73 and issued directives to the

Battalion 73 as required. Four experimenters rotated in the role of

simulating "Squawk" from the fire units, e.g., acknowledgment of assign-

ment, etc.

3

Data collection occurred during six consecutive evenings between

2200 and 0600 as shown at the bottom of Figure 1. Data was collected

for the expert team on the morning of the seventh day between 0600 and

0800. Each team served for a two-hour period each evening. Each period

consisted of two one-hour sessions. (Simulation equipment constraints

precluded simulated raid tapes from being over one hour in length.)

USAADS prepared scenarios from which twe raids were scripted and two

raid tapes were developed for use in the Q-73's simulation mode of opera-

tion. To assure comparable group data, all video viewed by operators on

their radar screens was generated from the tapes rather than from live

radar signals. The simulation package also included the capability for

periodic recordings of the status of all actions taken by the operators

and the times of these actions. In addition, the system periodically

recorded the status of all fire units under control of the Battalion Q-73.

During each one-hour session, a team would be exposed to three different

assaults or waves of varying size. As soon as an aircraft track entered

the system and three simulated radar sweeps verified its presence, the

track became available to the ID operatnr seated at the left console. All

tracks entered with an unknown identity. Simulated messages into the Q-73

resulted in change of status symbols replacing unknown symbols on the

operator's screen. When the ID operator observed this special symbol, he

"hooked" the track by placing his cursor over the syinbol and pressing the

appropriate function switches to reveal whether the track was friendly or

hostile.

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When a track symbol changed to hostile, it became the duty of the

weapons assignmen~t officer to select a fire unit to engage the track.

The Q-73 system has limited software to provide automatic assignment of

fire units, but it was the purpose of the presevit experiment to ass.,ss

human performance capabilities in the manual weapon assignment mode.

For each two-hour session, there were either four, six, or eight

fire units under control of the Q-73 (see Figure 1). The manning config-

uration consisted of having the tactical director behind the console

operators or seated at the weapons assignment console. Thus, each

combination of fire unit number and manning configuration resulted in

six different conditions constituting the six experimental se-sions.

I6

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6

'I _____

I ~¶r - ~ - -

IF ___________________________

III. RESULTS AND DISCUSSIONS

The analyzed data consisted of 383 sets of reaction times corres-

ponding to complete actions taken by AN/TSQ-73 operators on hostile

aircraft during days 1 through 6. Thirty-three additional sets of times

were obtained from the expert group and were used in non-parametric

analysis of operator training and familiarization. Each set was composed

of three values for a given hostile aircraft: (1) the total time to identify

an aircraft and assign a firing unit; (2) the proportion of the time required

by the ID operator; and (3) the proportion of the time required by the

weapons assignment operator. As an estimate of terminal system effective-

ness, percentages of successfully engaged aircraft were tabidlated for

days 5 and 6. A breakdown of these percentages into detailed categories

of actions, e.g., number of friendly aircraft incorrectly engaged, was

precluded due to extraneoL factors such as uncontrolled instructions to

the ope~rators, system problems, and errors on the radar track tapes. It

was still possible, however, to estimate overall performance against

7 hostile aircraft. These percentages are reported in Table 1.

This -fable shows the percentage effectiveness of the operators. It

-is based on ratio of the average number of completed identification/

;~ weapon-assignment sequences to the average number of completed identifica-tions in a wave. Effectiveness remains at about 70% for low- and medium-

I~ size waves. It drops to about 49% for high-wave sizes. In this experimentShigh-wave size was 25 or more aircraft. It is possible that these

estimates may be conservatively low. Effectively completed sequences

7

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may have been restricted by uncontrolled instructions issued during the

experiment to reduce extraneous noise on the operators' screens, such as

bogus track identifiers created by rapidly turning aircraft.

A detailed investigation of operator reaction times added insight into

the variables influencing overall effectiveness. By examining operators'

switch actions on the AN/TSQ-73 console, it was possible to accurately

determine ID and weapon assignment times. These times were analyzedin relation to the experimental variables of manning configuration,

number of fire units, number of aircraft in an attacking wave, training

group, day of test, and raid-tape scenarios. To maximally explore the

relationships ri-esent in the data, times were subjected to multiple linear

regression analysis using an IBM 360-65 computer. The data were tested

against 90 different models corresponding to plausible psychological

outcomes. Multiple F-tests were then used to choose the most parsimonious

models with the greatest degree of explained variance.1

F The following conclusions were supported by reaction time data. Theaverage total time to identify and successfully engage a hostile aircraft

was 208 seconds. (Start thime was estimated at about 24 seconds after the

system first contacted the radar track.) The average time to correctly

It should be noted that the degrees of freedom used in these Fstatistics represent model comparisons and are not always directly relatedto the number of experimental variables as is the case in the usual ANOVATable. The reader is referred to the appendix for reference detailingthis procedure.

r 9

identify a friendly aircraft was 57 seconds. The iD and weapons assign-

ment (WA) operators did not always respond in the same manner to the

experimental variables. Manning configuration had a significant effect on

UA reaction times (F(l, 31 8 )'9.49 P'ý.01). When the officer implemented

decisions through the console his mean reaction time was 91.6 seconds

versus 131.4 seconds when he served as tactical director. This wds an

average improvement of 39.8 seconds, or about 30%.

Number of fire units also effected WA time (F2 ,380)=4.14 P

-. OMI II9

values for ID times are plotted in Figure 2 as a function of wave size.

For WA the linear trend seen in ID times was not evident, F:gure 3 shows

mean reaction times already rising rapidly at eight aircraft, suggesting

that the WA operator was already overloaded. Latencies reach a peak

of 176 seconds per aircraft at 16 aircraft and recede to a steady state

level of 100 seconds thereafter. Though dropping from the highest value,

terminal WA times are still well over a minute longer per aircraft than

at a wave size of eight. This decrease coincides with a loss in overall

effectiveness and may be due to the forced adoption of faster but less

optimal WA strategies for assigning hostilc targets to the most appropriate

fire units. Comparisons between possible wave models-showed the WA data

was best fit by a cubic equation:RTwA= 3.23w-.012w3 -29.37

The cubic fit was a significantly better predictor than either a linear

or a second order equation (F(1 ,380)=4.29P

more sensitive to the attacht configuration than -the ID task, since

the raid tapes generated different numbers of artificial tracks on the

radar screens depending on the aircraft maneuvers utilized in the raid.

Reaction time data show a significant effect over days on ID and WA

times (FID(5,377)= 2 .59 P

Due to the low number of expert scores and the possible violation

of normality assumptions, a non-parametric Wilcoxen matched pairs signed-

ranks test was chosen. The results showed no significant difference for

ID times (Z=1.03 p

IV. CONCLUSIONS

Tentative conclusions may be drawn for some of the original research

questions. First, TEWA in the semi-automatic mode is not instantaneous.

Average time for system contact, identification, and weapons assignment in

the AN/TSQ-73 system was 3.47 minutes. Second, manning configuration in

which the officer implements decisions directly through the WA console

significantly improves assignment times. Third, wave size has its greatest

effect on the WA operator, although ID times do increase linearly as the

number of aircraft increase. Fourth, WA is overloading at eight aircraft

and reaction times increase rapidly. Increased numbers of fire units do

improve WA times but only if eight or more are available. Finally, oper-

ator fatigue could be a consideration in WA under heavy task demands.

L I REFERENCES

Ward, Joe H. and Jenninqs, Earl, Introduction to Linear Models, 1973,

Prentice-Hall, Inc.

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APPENDIX

The techniques used in this report to determine predictive formulas

involved a multiple linear regression program modified by Jorgensen to

permit rapid generation of model vectors. A discus;ion of the statistical

logic, model construction, and general programing methods is available

in "An Introduction to Linear Models" (Ward & Jennings, 1973).

Briefly the technique involves solving for parameters in a theoretical

equation previously defined by the experimenter to reflect specific

psychological'assumptions. This is done through a least squares fit of

the equation parameters to raw or transformed data. The program then

generates the standard beta weights and regression constant for that solution.

The predictive power of the equation is specified by M2 , the squared multiple

correlation coefficient. M2 is mathematically equivalent to the percent

of explained variation. Through the use of alternate equations, F ratios

can be set up to compare various assumptions in terms of their explained

variation. Analysis of variance and factorial analysis of covariance are

two of the many possible model formulations which could be utilized within

the regression framework.!n

Usually the most efficient strategy for finding optimal moaels

consists of postulating a general all-encompassing equation which takes

-into account a linearly independent set of predictor variables based on

conditions used in the experiment. The M for this model serves as a

maximum against which the predictive power of other simpler models is

06. 21 p' .c-W'. i.- .... 3¶*iSS

judged. The simplest possible predictive model is the mean of the

distributions. An F ratio formed between the general model and the

mean model tests the usual null hypothesis for equality of means. By

using the same technique with more complex models, F tests can be set up

comparing various models to the general model and to each other. This

is analogous to analysis of covariance. The pattern of significant F

ratios as well as the M2 efficiency of the models quickly points out the

most efficient and parsimonious equations for a given set of assumptions

and predictive power.

For example, in this experiment the three general models were all

predictive equations taking into account raid tapes, low, medium, or

high wave sizes, days, manning configuration, groups and fire units.

A different general equation was generated for total, ID, and weapons

assignment times. In this analysis four types of models were condidered:

orthogonal component models for each variable of interest (these are

equivalent to a one-way analysis of variances for each variable), linear

models (equivalent to simple linear regression fits), second and third

order polynomial models (which investigated parabolic curves) and mixed

models, such as a linear model going second order at a specific point.

The following are examples of a general 12-element orthogonal model for

[ .total times, a model based on six wave sizes, a linear model, and apolynomial model:

22

a7i P 77

7I

Time (total) " aoXI a1S2 Ja2 13 " ". l7

Time (total) -aoYI+aIY 2+a2Y3Y4+a4Y5 +a5Y6Time (total)

Tite (total) U+aW

2 3Time U+aWI~aW +a W

where X1... X12 are colrmn vectors of O's and I's partitioning total data

times into orthogonal sets as a function of such variables as days, t *ves

or raid tapes.

Y...Y 6 are column vectors of O's or l's partitioning total times

into sets for wave size one through 6, respectively.

U is a unit vector of l's.. W is a column vector containing the

numbers one through 6 corresponding to the size of the wave.

W is the direct product of W with itself.

a is a beta weight for the regression.

Though many models were considered and fit, only the most parsimonious

and experimentaly meaningful are reported in this paper. The equations

derived represent best fits for the available data. Their generalizability

assumes the generalizability of the experimental situation to the combat

usage of the AN/TSQ-73.

23

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TRAINING MNAhGEMENT

1 USA FIFLU ARTILLL.RY SCHOOL ýOjkklb StvET[ LIBRARYI USA INTITUTE Ui AUMtNISI"A;IUN ALAU04IC LIUI4ARYI USA WAI4 CULLEOL ATTN: LidU.y[I USA LN(AN~kW SCtiUOL LIUNANY ANU LtAN'41N(, REWDURUES CENTER4I USA A4MOW SCHOUL (USARMS) A17N: L1BRARY1 OHtANIIATLONAL LfFtZCIIV4LNL!.S 11413 CtN + SCM ATTN: L1IOPARIAN1 US ARMY INTELLliv4(C. CLNILH + SCHOOL ATTN: ATSI-ToI 1U~S ARMY INTLLLIuL'4tL CL~i~tr( * !bLHOOL ATTN: ATSI.'Rm-mI US ARMY INTELL1INCE CEIMI~ + lioiuuL AITNt ATSI-ToLDI US AHMY IN~TELL~iU~4Ct C.Idt~it + SCHOOL ATTN: AISI-CO'CS-CI US ,ýRMY INTELLI~jtNCE CL.NILH + SL.)OUL ATTN: ATSI-DT-SF-IM

4 RRTISH LMAASSY jkIfIbH UJtkLNCt. STAFF2CA14AUIAN JOINT S1AIF

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15Sý LIBRAHY OF* CON~3HLSS UNIT UO(.UmLNIS EJIPEDITIN4 PROJECT1 EDITOR. Rt ANU U MA1,iAL'NE ATTN: UNCut-LNIUS (30VFI4NMENT VRL4~TING UH'. LI.HMAHY, PUbLIC UUCU14LNTS DEPARTMENTIUS GOVFHNMINT PH147NGI1 Utt. LIHNARY A4U STATurORY, L119 DIV (SLI)

1 THF ARmY LlbRAHY

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