Optimization of Army-Navy/Portable Special Search 

(AN/PSS)-14 Operator Training 

by Kristin M. Schweitzer, Bradley M. Davis, Bradley A. Pettijohn, 

Robert D. Clark, Alan D. Davison, and James J. Staszewski 

ARL-TR-3970 October 2006 

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Army Research Laboratory 

Aberdeen Proving Ground, MD 21005-5425 

ARL-TR-3970 October 2006 

Optimization of Army-Navy/Portable Special Search 

(AN/PSS)-14 Operator Training 

Kristin M. Schweitzer, Bradley M. Davis, Bradley A. Pettijohn, 

Robert D. Clark, and Alan D. Davison 

Human Research & Engineering Directorate, ARL 

James J. Staszewski 

Carnegie Mellon University 

Approved for public release; distribution is unlimited. 
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4. TITLE AND SUBTITLE 

 Optimization of Army-Navy/Portable Special Search (AN/PSS)-14 Operator 

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6. AUTHOR(S) 

 Kristin M. Schweitzer, Bradley M. Davis, Bradley A. Pettijohn, Robert D. Clark, 

 and Alan D. Davison (all of ARL); James J. Staszewski (CMU) 5f. WORK UNIT NUMBER 

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 Human Research & Engineering Directorate 

 Aberdeen Proving Ground, MD 21005-5425

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13. SUPPLEMENTARY NOTES 

14. ABSTRACT 

The research goal was to optimize Army-Navy/Portable Special Search (AN/PSS)-14 mine detector operator training duration 

and content. Results from training observations and analysis of Soldiers’ learning progression curves indicated that AN/PSS-14

operators who certified through the course were not adequately skilled. Results also showed that the operators learned little 

with regard to ground-penetrating radar (GPR) use and consequently were not confident in discriminating mines and clutter. 

The authors recommended a better understanding of GPR functionality and the teaching of target discrimination. Additional 

time needs to be spent on learning how to develop the spatial patterns (footprints) that different objects produce through metal 

detection and GPR signals. Training sessions need to be standardized and structured into the crawl-walk-run format with more 

“hands-on” experience. The Sweep Monitoring System needs to be used more fully. Instructors need to better provide prompt, 

consistent, and frequent performance feedback. We recommend more stringent quality control of mine simulants, controlled 

clutter in the mine lanes, burying of the test piece, and multiple grading standards (probability of detection, target discrimination, time standard) that are consistent and more accurate. Recommendations were integrated into a new program of instruction.

15. SUBJECT TERMS

 AN/PSS-14, mine, training, optimization, probability of detection 

16. SECURITY CLASSIFICATION OF: 

19a. NAME OF RESPONSIBLE PERSON

 Kristin M. Schweitzer

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Standard Form 298 (Rev. 8/98) 

Prescribed by ANSI Std. Z39.18
iii 

Contents 

List of Figures vi

List of Tables vii

1. Introduction 1

1.1 Background .....................................................................................................................1 

1.1.1 The Land Mine Threat.........................................................................................1 

1.1.2 Progress in Land Mine Detection........................................................................1 

1.1.3 Transfer of Training to the Operational Environment.........................................2 

1.1.4 Skill Decay ..........................................................................................................3 

1.2 Problem Statement ..........................................................................................................3 

1.3 Objectives........................................................................................................................4 

1.4 Approach .........................................................................................................................4 

1.5 Indications of Learning ...................................................................................................5

2. AN/PSS-14 (formerly known as HSTAMIDS) 6

2.1 Description ......................................................................................................................6 

2.2 Theory of Detection.........................................................................................................7 

2.3 Component Operational Skills ........................................................................................8 

2.3.1 System Preparation and Sensor Calibration ........................................................8 

2.3.2 Core Operational Skill Components....................................................................8 

2.4 Training Site..................................................................................................................12 

2.4.1 Training Aids and Functions .............................................................................13 

2.4.2 Training Schedule/Sequence .............................................................................15 

3. Method 15

3.1 Participants ....................................................................................................................16 

3.2 Apparatus and Materials................................................................................................16 

3.2.1 Training Experience Survey..............................................................................16 

3.2.2 AN/PSS-14 Ergonomics Questionnaire ............................................................16 

3.2.3 Daily Log...........................................................................................................17 

3.2.4 Sweep Drill Worksheet .....................................................................................17 

3.2.5 Iteration Cover Sheet.........................................................................................17 
iv 

3.2.6 Blind Search Observation Data Worksheet.......................................................17 

3.2.7 Mine Lane Maps................................................................................................17 

3.3 Procedure.......................................................................................................................17 

3.4 Anticipated Results........................................................................................................18 

4. Results 19

4.1 Time Distribution ..........................................................................................................19 

4.2 Probability of Detection ................................................................................................20 

4.3 Confidence Ratings .......................................................................................................23

4.4 Investigation Times .......................................................................................................24 

4.5 Rate of Advance ............................................................................................................26 

4.6 Qualitative Observations ...............................................................................................27 

5. Discussion 28

5.1 Time Distribution ..........................................................................................................28 

5.2 Probability of Detection ................................................................................................30 

5.3 Confidence Ratings .......................................................................................................30

5.4 Investigation Time.........................................................................................................32 

5.5 Rate of Advance ............................................................................................................32 

5.6 Performance Feedback ..................................................................................................33 

5.7 Certification Standards..................................................................................................34

5.8 SMS Equipment ............................................................................................................35

5.9 Limitations.....................................................................................................................36 

6. Recommendations 36

6.1 Curriculum: Content and Time Allocations .................................................................36 

6.2 Performance Feedback ..................................................................................................37 

6.3 Training Content............................................................................................................37 

6.4 Certification Standards..................................................................................................40

6.5 Equipment .....................................................................................................................41 

6.6 Training Facilities..........................................................................................................42 

6.7 Program of Instruction, Efficiency, Costs, and Skill Retention ....................................43 

6.8 Future Research.............................................................................................................44 

7. Conclusion 45
v 

8. References 46

Appendix A. Data Collection Forms 49

Appendix B. Probability of Detection 59

Appendix C. Confidence Rating 61

Appendix D. Investigation Time 63

Appendix E. Rate of Advance 75

Distribution List 76 
vi 

List of Figures 

Figure 1. AN/PSS-14 operated near Bagram Airport, Afghanistan, in 2004. ............................... 2 

Figure 2. Generic learning curves.................................................................................................. 5 

Figure 3. AN/PSS-14. .................................................................................................................... 6 

Figure 4. Target investigation...................................................................................................... 10 

Figure 5. Generic mine footprints: APM (top left), ATM (top right), APLM (bottom left), 

and ATLM (bottom right)..................................................................................................... 12 

Figure 6. Pole barn facilities; west facing view........................................................................... 13 

Figure 7. Sweep monitoring system (SMS)................................................................................. 14 

Figure 8. Scoring grid. ................................................................................................................. 15 

Figure 9. Median weekly time distribution.................................................................................. 20 

Figure 10. Probability of detection versus trial number for all mine types. ................................ 21 

Figure 11. Mean probability of detection versus adjusted trial number by mine type. ............... 22 

Figure 12. Mean confidence rating versus trial number: all mines versus clutter. ..................... 23 

Figure 13. Mean confidence rating versus adjusted trial number by mine type.......................... 24 

Figure 14. Median investigation times (total, MD, and GPR) versus trial number for all 

mine types and clutter. .......................................................................................................... 25 

Figure 15. Median rate of advance versus trial number............................................................... 26 

Figure 16. Recommended weekly time distribution.................................................................... 37 

Figure 17. Skill retention functions. ............................................................................................ 44 

Figure B-1. Mean probability of detection versus lane for all trials............................................ 60 

Figure B-2. Mean probability of detection versus adjusted trial number by participants’ test 

result...................................................................................................................................... 60 

Figure C-1. Mean confidence rating versus lane for all trials...................................................... 62 

Figure C-2. Mean confidence rating versus adjusted trial number by participants’ test result. . 62 

Figure D-1. Median total investigation time versus adjusted trial number by mine type............ 64 

Figure D-2. Median MD time per investigation versus adjusted trial number by mine type. ..... 64 

Figure D-3. Median GPR time per investigation versus adjusted trial number by mine type.... 65 

Figure D-4. Total investigation time versus adjusted trial number for APLM type mines. ........ 66 

Figure D-5. Total investigation time versus adjusted trial number for APM type mines............ 67 

Figure D-6. Total investigation time versus adjusted trial number for ATLM type mines......... 67 

Figure D-7. Total investigation time versus adjusted trial number for ATM type mines. .......... 68 

Figure D-8. Total Investigation Time versus Adjusted Trial Number for Clutter Targets.......... 68 

Figure D-9. MD Time per Investigation versus Adjusted Trial Number for APLM Type 

Mines..................................................................................................................................... 69 

Figure D-10. MD Time per Investigation versus Adjusted Trial Number for APM Type 

Mines..................................................................................................................................... 69 
vii 

Figure D-11. MD Time per Investigation versus Adjusted Trial Number for ATLM Type 

Mines..................................................................................................................................... 70 

Figure D-12. MD Time per Investigation versus Adjusted Trial Number for ATM Type 

Mines..................................................................................................................................... 70 

Figure D-13. MD Time per Investigation versus Adjusted Trial Number for Clutter Targets... 71 

Figure D-14. GPR Time per Investigation versus Adjusted Trial Number for APLM Type 

Mines..................................................................................................................................... 71 

Figure D-15. GPR Time per Investigation versus Adjusted Trial Number for APM Type 

Mines..................................................................................................................................... 72 

Figure D-16. GPR Time per Investigation versus Adjusted Trial Number for ATLM Type 

Mines..................................................................................................................................... 72 

Figure D-17. GPR Time per Investigation versus Adjusted Trial Number for ATM Type 

Mines..................................................................................................................................... 73 

Figure D-18. GPR Time per Investigation versus Adjusted Trial Number for Clutter Targets. 73 

Figure E-1. Median Rate of Advance versus Lane for all Trials................................................. 78 

Figure E-2. Median Rate of Advance versus Adjusted Trial Number by Participants’ Test 

Outcome................................................................................................................................ 78 

List of Tables 

Table B-1. Descriptive statistics: probability of detection by target type....................................61 

Table B-2. Descriptive statistics: probability of detection by lane..............................................61 

Table B-3. Descriptive statistics: probability of detection by participants’ test result. ...............61 

Table C-1. Descriptive statistics: confidence rating by target type. ............................................63 

Table C-2. Descriptive statistics: confidence rating by lane........................................................63 

Table C-3. Descriptive statistics: confidence rating by participants’ test result..........................63 

Table D-1. Descriptive statistics: total investigation time (seconds) by target type....................65 

Table D-2. Descriptive statistics: MD time per investigation (seconds) by target type. .............65 

Table D-3. Descriptive statistics: GPR time per investigation (seconds) by target type.............65 

Table D-4. Power curve (y = Cxb

) model summary: investigation time (y) versus adjusted 

trial number (x). .....................................................................................................................65 

Table D-5. Power curve (y = Cxb

) model summary: MD time per investigation (y) versus 

adjusted trial number (x). .......................................................................................................65 

Table D-6. Power curve (y = Cxb

) model summary: GPR time per investigation (y) versus 

adjusted trial number (x). .......................................................................................................66 

Table E-1. Descriptive statistics: rate of advance by lane. ..........................................................77 

Table E-2. Descriptive statistics: rate of advance by participants’ test outcome.........................77 
viii 

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1 

1. Introduction 

1.1 Background 

1.1.1 The Land Mine Threat 

Since World War II, land mines have posed a major threat to U.S. ground forces. An effective 

force multiplier, land mines play an especially important role in the asymmetric warfare in which 

the U.S. has engaged in conflicts of the past 15 years. Hambric and Schneck (1996) provided an 

assessment of the land mine threat stating, “Mines are a major threat in all types of combat and 

will be the major threat in operations other than war...which are expected to be the most likely 

missions for U.S. forces in the future...The widespread employment of land mines threatens to 

neutralize U.S. advantages in firepower and mobility by severely limiting our ability to maneuver 

and by disrupting our tactical synchronization.” Subsequent assessments from Operations Joint 

Endeavor (U.S. GAO, 2001; Schneck & Green, 1997) and Enduring Freedom (LaMoe & Read, 

2002) have validated this appraisal and suggest that its severity may have been underestimated. 

Moreover, the counter-mine problem seen in the contemporary operational environment was 

predicted to worsen (LaMoe & Read, 2002). Kern’s (2005) recent assessment of the threat echoes 

that of LaMoe and Read (2002): 

We must take this challenge [to defeat mine threats] seriously and field the best 

solutions quickly to protect our forces. We must learn how to detect at distance 

and speed to ensure our future operational concepts are not derailed by the old 

simple devices...this problem demands our best work now...asymmetric warfare 

using mines of multiple varieties. 

1.1.2 Progress in Land Mine Detection 

Land mine detection is the core task in counter-mine operations. Discovering the locations of 

hidden mines remains an extremely hazardous task because it puts dismounted troops who are 

operating hand-held detection equipment close to buried and thus hidden, live, lethal ordnance. 

Significant advances have been achieved recently in detection capability, related to the development and fielding of new equipment and training. Current systems are less than perfect, however, 

and further work on detection is needed to protect our troops and ensure maneuver capability. 

The recent deployment of a new hand-held detection system, the Army-Navy/Portable Special 

Search (AN/PSS)-14 (see figure 1) represents a major technological advance. The first detector 

to combine two sensors, an electromagnetic induction subsystem, and ground-penetrating radar 

(GPR), this system has been deployed for use in Operations Enduring Freedom and Iraqi 

Freedom and has received favorable feedback from its users in the field (82nd Airborne, 2003). 
2 

Figure 1. AN/PSS-14 operated near Bagram Airport, Afghanistan, in 2004. 

Significant progress has also been made in training troops to operate the AN/PSS-14 and its 

predecessor, the AN/PSS-12, both of which are employed in current operations. Training 

programs based on cognitive science research have raised detection rates sufficiently beyond 

those produced by previous training programs (Staszewski & Davison, 2002), resulting in the 

Army’s adoption of these programs to train AN/PSS-12 and AN/PSS-14 operators. As demonstrated in the initial stages of system development and recently confirmed in the field, the 

performance of the AN/PSS-14 and dismounted mine detection capability depends crucially 

on the skills of its operator. 

1.1.3 Transfer of Training to the Operational Environment 

An in-theater assessment of AN/PSS-14 following its deployment in support of Operation Enduring 

Freedom addressed issues about the AN/PSS-14’s capabilities and use in the operational environment (Maurer, 2003). Evaluators concluded that the equipment was performing to expectations: 

(a) Soldiers could safely detect very low metal mines from flush emplacement to depths of 4 inches; 

(b) Soldiers could detect low metal mines close to metal clutter and in metal-laden soils; (c) Soldiers 

reported confidence that they could detect low metal mines using the AN/PSS-14. 

Evaluators’ conclusions contained an important caveat related to operator skill, however. Intheater testing showed that the techniques of most operators were deficient after a month or more 

without system use, resulting in problematic detection rates (73.6%). Fortunately, delivery of 

refresher training restored performance to desirable levels (98.6%) and increased operators’ 

confidence in their detection capabilities. These observations underscored the critical role of 

operator training and skill and implied that many operators’ skills had deteriorated in the interval 
3 

between initial training and operational use of the AN/PSS-14. Moreover, evaluators observed 

that noncommissioned officer (NCO) personnel with supervisory responsibilities who were 

unfamiliar with operator training and proper operational technique lacked the knowledge 

required to detect these deficiencies. 

Another later in-theater assessment of operator skills conducted by U.S. Army Engineer School 

(USAES) personnel also showed that Soldiers’ detection rates had fallen substantially below the 

standard for successful completion of AN/PSS-14 training (Mincey, 2005). Evaluation of 

operators’ techniques revealed major deficiencies. This decrement was also attributed to an 

unspecified interval without practice between Soldiers’ completion of initial new equipment 

training (NET) and subsequent in-theater evaluation. 

1.1.4 Skill Decay 

The phrase “use it or lose it” accurately describes the fate of skills that go unpracticed. Extensive 

scientific literature supports this saying (Healy & Bourne, 1995; Farr, 1987; Rose, Czarnolewski, 

Gragg, Austin, Ford, Doyle, & Hagman, 1985; Shields, Goldberg, & Dressel, 1979). Generally, 

the longer the interval without practice, the greater the loss in proficiency. Although the length of 

the retention interval plays a critical role in predicting how much proficiency is likely to suffer, the 

level of skill at the start of the retention interval is also an important determinant of the deterioration that occurs with the absence of task practice (Anderson & Schunn, 1995; Bahrick & Hall, 

1991). It follows that efforts to understand and mitigate skill decay must examine the original 

level of learning achieved and the effects of denial of practice. 

This reasoning applied to the in-theater performance of AN-PSS-14 operators motivated (1) the 

assessment of operator training reported here and (2) a subsequent experimental investigation of 

skill retention in progress. 

1.2 Problem Statement 

Evaluations of Soldiers trained to use the U.S. Army’s AN/PSS-14 mine detector in support of 

ongoing operations suggested that operator skills decayed between completion of original 

training and operational use. Such losses can compromise our forces’ counter-mine capability, 

threaten mission success, and jeopardize operators and other mission-related personnel. An 

understanding of the factors contributing to this problem is required for the formulation of 

mitigating policies. These factors include the level of skill that novice operators acquire in 

AN/PSS-14 NET. 

The U.S. Army Engineer School, Training and Doctrine Command (TRADOC) System Manager 

for Assured Mobility (TSM-AM), Counter-Explosives Hazards Center (CEHC) provided the 

AN/PSS-14 NET. The training program consisted of 40 hours’ classroom instruction and handson training. Typically, three NCOs were in charge of the training, along with training assistance 

provided by Cyterra or Battelle contractors (or both). The training duration evolved from the 
4 

initial 40-hour block of training employed for testing the AN/PSS-14 prototype, the Hand-Held 

Stand-Off Mine Detection System (HSTAMIDS), in 2000. Its effectiveness was confirmed by 

its inclusion of successful operational tests of the system (Santiago, Locke, & Reidy, 2004). 

Modifications of the system have followed, including incorporation of an algorithm that supports 

the aided target recognition function, but the 40-hour duration of training has not been changed. 

Effects of varying the training time or examining its adequacy or efficiency of AN/PSS-14 

training have not been investigated. 

1.3 Objectives 

The TSM-AM and the USAES Director of Training commissioned this effort to evaluate current 

AN/PSS-14 NET delivered by USAES, TSM-AM, CEHC and to identify and recommend means 

to maximize its effectiveness and efficiency. A specific issue for USAES leaders was whether 

the 40-hour-long training program was needed to train Soldiers to meet the current standards. A 

related task was to determine the amount of training that Soldiers need to achieve current performance standards for USAES operator certification; current records indicated that these 

standards were being met with the 40-hour program of instruction. 

The scope of inquiry was comprehensive. It included consideration of the training infrastructure, 

including the site, facilities, training and testing aids, personnel needs, and procedures. Issues 

for examination included 

a. What were the infrastructure requirements needed for training Soldiers to use this mine 

detector? How did the design of the training site and available resources impact training? 

b. How efficient was the training? Were significant amounts of time being lost in teaching 

topics that were not relevant? Could more efficient ways be established to teach the 

different tasks and subtasks in mine detection? 

c. What areas were being over- or under-taught, and how should that guide reallocation of 

training time to drills on the basis of need? 

1.4 Approach 

The evaluation approach was based on an empirical observation of training activities and focused 

on trainees’ skill acquisition and performance and their drivers. A team composed of personnel 

from the U.S. Army Research Laboratory’s (ARL’s) Human Research and Engineering 

Directorate and Carnegie-Mellon University (CMU) executed the evaluation. 

Personnel responsible for planning the study first observed 2-week-long training cycles delivered 

at USAES sites. The purpose was to familiarize themselves with the training in its current form 

and the training environment. The finding supported planning and preparation for 3 weeks of 

comprehensive, systematic field observation. This included collection of empirical data about 

the temporal organization of training activities, the activities of training personnel, and the 
5 

behavior and performance of trainees. A priority was collection of data that tracked changes in 

trainee performance as a function of training activities or in other words, learning. These data 

would document individual trainee performance from initial mine detection efforts to the level of 

land mine detection performance achieved at the time of certification. The training events 

driving trainee learning were recorded as well, and evaluation focused on examining how these 

events related to Soldiers’ learning trajectories and the skill levels they attained at the end of 

NET cycles. 

1.5 Indications of Learning 

Two common metrics used to investigate and assess learning are success rates and speed of task 

execution. Success rate is the proportion of opportunities for which an individual achieves a 

designated goal. Learning is reflected in an increasing proportion of successful trials (to an 

asymptotic level) as task practice accumulates. The relation between performance and practice 

takes a curvilinear form typically, as illustrated in the dark green function in figure 2, relating 

success rates on the y-axis scale on the left of the chart to number of practice trials on the x-axis. 

0

20

40

60

80

100

Practice Trials

Success Rate (%)

Success

Time

0 1...............................................................................N

0

250

150

75

25

125

200

175

225

100

275

Time Per Trial (sec)

0

20

40

60

80

100

Practice Trials

Success Rate (%)

Success

Time

0 1...............................................................................N

0

250

150

75

25

125

200

175

225

100

275

Time Per Trial (sec)

Figure 2. Generic learning curves. 

Learning can also be measured as acceleration of task execution with increasing task practice 

(Newell & Rosenbloom, 1981). According to the Power Law of Practice (Newell & Rosenbloom, 

1981), individuals typically demonstrate rapid decreases in task execution time initially but gain 

more slowly with further practice, thus producing diminishing performance returns. This is 

illustrated by the light green function in figure 2 relating practice to task execution times (shown 

on the right-hand y-axis). 

It is important to note that these descriptions of learning trajectories make several assumptions 

about the learning environment. First, the descriptions assume that reliable, accurate, and timely 

feedback about a learner’s performance is available to the learner. The absence of this critical 
6 

ingredient can impede or negate learning. These characterizations also assume that learners 

engage in a task for which they have had no prior experience and that the task remains the same 

throughout the practice period. 

This evaluation of mine detection training focused on two measures one can use to infer a mine 

detector operator’s skill acquisition: (1) probability of detection, and (2) task completion time. 

Additional measures of interest included target and clutter discrimination, operators’ subjective 

ratings of confidence in locating buried mine targets, and rate of advance (ROA). 

2. AN/PSS-14 (formerly known as HSTAMIDS) 

2.1 Description 

The AN/PSS-14 is a lightweight, human-portable, hand-held mine detector that can detect 

metallic and low-metallic mines (see figure 3). The major components of the AN/PSS-14 are 

battery case and cable, electronics unit (EU), earpiece and cable, control grip, wand assembly, 

and sensor head. The AN/PSS-14 is used to support off-road movement of units, clear lanes, and 

help identify leading edges of minefields. Non-engineer units use the AN/PSS-14 to confirm or 

deny the presence of mines in support areas and logistics sites. 

Figure 3. AN/PSS-14. 
7 

2.2 Theory of Detection 

The AN/PSS-14 uses two different sensors for the detection of mines: electromagnetic induction 

(EMI) or metal detection (MD), and GPR. Each sensor returns a unique audio signal and can be 

heard by operators individually or in combination with the other. 

MD operates on the principle of EMI, employing components that transmit electromagnetic 

signals and receive such signals to detect the presence of conductive material. The transmission 

component sends an electromagnetic signal into the soil, which induces a secondary magnetic 

field in conductive objects and materials. If the strength of the secondary magnetic field 

(dependent upon the composition and quantity of the material) is above a set threshold, 

algorithms that monitor return signals produce an auditory signal indicating the presence of 

conductive material (Department of the Army, 2003). The metallic components of mines within 

the range of the EMI signal produce MD responses. 

GPR can locate objects buried as deep as 6 inches in the soil by transmitting radar waves into the 

ground and analyzing the reflected waves. As the search head passes over buried objects whose 

dielectric constant differs from that of the surrounding soil, changes in the radar returns occur. 

Algorithms that monitor return signals and register these changes can thus reveal locations of 

buried objects. The AN/PSS-14’s generation of GPR output signals depends upon more than the 

system’s registration of changes in return signals, however. The MD system must also register 

the presence of conductive material in its sensor field, although the strength of the MD signal 

does not need to reach the threshold required for an MD output signal. 

The sensitivity of the MD and GPR systems to different properties related to mine targets 

significantly augments the system’s detection potential. Co-location of both signals provides 

highly constrained information for inferring the presence of a buried land mine. Although many 

buried objects (and terrain features for GPR) can produce output signals on one or the other 

sensor operating independently, far fewer objects (other than mines) will produce output from 

both sensors. Moreover, both sensors are sensitive to variation in signal dimensions; the MD 

subsystem can reveal greater or lesser quantities of conductive material and the GPR subsystem 

can reveal the spatial dimensions of buried objects. These capabilities provide information that 

further constrains interpretation of output signals to broad categories of mines. If properly 

interpreted by a well-trained operator, the AN/PSS-14’s responses offer innovative and powerful 

detection capabilities. 

Mine detection with this system depends on its operator’s ability to recognize the spatially 

distributed patterns of auditory output from his equipment produced by land mines. The 

equipment and the information it provides when operated correctly offer enormous potential for 

land mine detection. However, this potential can only be realized by training operators to 

(1) produce reliable and valid signals by applying proper operational techniques, and (2) interpret 

and recognize the spatially distributed patterns of auditory output from the equipment produced by 

land mines to infer their locations. 
8 

2.3 Component Operational Skills 

Operators must acquire multiple skills to effectively operate the AN/PSS-14. First, before the 

system is used for land mine detection, procedures for preparing the system must be performed 

properly. Two primary operational sub-skills that determine a Soldier’s proficiency with the 

AN/PSS-14 beyond proper system preparation and calibration are search sweep technique and 

footprint development. Soldiers must also learn supporting skills such as safety measures and 

equipment maintenance. 

2.3.1 System Preparation and Sensor Calibration 

An important functional feature of the AN/PSS-14 is its capability to adapt to varying soil and 

terrain conditions, which vary widely throughout the world. Exploiting this capability involves 

training operators to correctly perform preparatory sensor calibration procedures that enable the 

system’s subsystems to adapt to the characteristics of the environment in which the system will 

be used (Glumm, Reinhart, Sexton, & Waugh, 2001). Before using the detector, the operator 

must first prepare and calibrate the AN/PSS-14 to filter soil scatter and eliminate the effects of 

mineralized soils and “train” the GPR. 

After the system is unpacked and assembled, preparation and calibration procedures are 

performed in the following sequence: (1) attach the earpiece, (2) turn the detector on, (3) allow 

the detector to warm for 5 minutes, (4) turn the detector off, (5) wait 10 seconds, (6) turn the 

detector back on, (7) perform noise cancel to establish an environmental noise baseline for the 

detector, (8) perform ground balance to eliminate soil mineralization effects, (9) train the GPR to 

filter soil scatter, and (10) verify the calibration process with a test piece to ensure proper 

signaling and sensitivity. Once the detector is successfully calibrated, the operator is prepared to 

search for mines. Audio signals alert the operator when a target is present. The operator first 

finds the origin of the metal signature and then uses GPR to establish whether the target is a mine 

(returns a GPR signal) or clutter (no GPR signal). 

2.3.2 Core Operational Skill Components 

2.3.2.1 Search Sweep 

Search sweep is the initial technique applied in detection activities. Its purpose is to identify 

locations in the area to be cleared (USAES training lane dimensions are 1.5 m by 15 m). These 

locations are identified by an output signal on the MD channel, the GPR channel, or both. 

Effective search sweep involves complete spatial coverage of the designated area for search with 

the sensor head. Complete coverage is necessary but is not a sufficient condition for effective 

search sweep. Effective search sweep sensor head movements fall within the kinematic ranges 

needed for effective sensor operation. Violation of these thresholds can compromise the 

sensitivity of the system sensors and result in missing land mines. Even though the sensor head 

may pass over a mine, if it is too high or moving too quickly, no return signal will sound. 
9 

Proper search sweep technique is the first of the primary operational skills in which Soldiers are 

trained. The multiple requirements for effective search sweep that an operator must learn to 

produce are as follow: 

• Sensor head must be parallel to the ground. 

• Sensor head must be swept as closely as possible to the ground without contact and never 

in excess of the 2-inch upper limit. 

• Sensor head trajectories should be perpendicular to the long axis of training lane in as 

straight a line as possible. Trainees are explicitly instructed to avoid arc-shaped paths.

• Sensor head velocity with the lane boundaries should be with the 1.0- to 3.6-ft/sec range. 

• Lane traversals continue to the point at which one-half of the sensor head extends outside 

the lane boundary. 

• Forward progress should proceed with trajectories that overlap the area covered on the 

previous traversal by one-third of the sensor head. 

Accurately evaluating novice operator movements of the sensor head accurately is an extraordinarily difficult (if not impossible) perceptual task for trainers and observers. Therefore, to provide 

accurate performance feedback for trainees and evaluative information for trainers, the training aid 

called the Sweep Monitoring System (SMS) (Herman, McMahill, & Kantor, 2000) was made an 

integral component of AN/PSS-14 training. This computer-based training aid collects and 

graphically displays information about these features of an operator’s search sweep for use by 

trainees and trainers, providing them with critical performance feedback needed for effective and 

efficient training. 

2.3.2.2 Footprint Development 

The second critical operational skill that AN/PSS-14 operators must acquire in training is the 

procedure for “footprint development” and interpretation of the procedural results. 

A land mine “footprint” is the spatially organized pattern of auditory signals produced by a handheld detector when it senses buried land mines. After the origin of an alerting signal obtained in 

search sweep is located, this location serves as a point of reference for acquiring the localized 

sensor output from which the pattern or footprint of a potential mine target is constructed by an 

operator. The operator then compares the resulting pattern to the patterns of mines stored in the 

operator’s knowledge base from previous encounters. If the pattern developed is recognized as 

similar to that of a mine pattern, that judgment leads to a mine declaration. 

Training includes instruction in the sequence of procedures that are used to build footprints. 

Repetitive application of these procedures on training mine targets provides practice in their 

application and familiarizes trainees with the generic patterns of AN/PSS-14 response signals 

produced by mines. This latter experience builds the knowledge that is the basis upon which 
10 

operators later recognize mine patterns and make “mine/no mine” decisions in training and in 

subsequent live operations. 

Footprint development procedure involves two sequentially organized steps. The first involves 

investigation of the area of the alerting signal with the MD sensor and afterward, the GPR sensor. 

The MD investigation maps an area around the origin of the alerting signal whose contours are 

defined by the onset or offset of output from the MD sensor. This area defines the region in which 

the operator will employ the GPR sensor to verify whether the suspected target is a mine. 

For MD investigation, operators are instructed to move the detector head in a semi-circular 

fashion around a suspected target, establishing a small spiral pattern to find the outer boundaries 

of the target’s signal or halo (see figure 4). These boundaries are defined by the offset or onset 

of an MD output, depending on the trajectory of the sensor head. When the sensor head is within 

the MD “halo,” MD output persists; movements that end the response identify a halo edge. MD 

investigations involve sequentially finding MD onset/offset points at the 3-, 6-, and 9-o’clock 

positions of the MD halo by continuously tracking its edge between these reference points. At 

each halo edge point, operators mark each edge position by placing poker chips. These visual 

markers are intended to support operator learning so that they can later visualize the MD halo 

without the aid of the physical markers. 

Figure 4. Target investigation. 

When the MD halo is completed, its geometry directs the operator where to proceed with GPR 

investigation. In initial drills, operators are instructed to place a chip at the center of the “clock 

face” defined by the 3-, 6-, and 9-o’clock edges of the MD halo. If the investigation involves a 

Halo 

(MD signal) MD Alerts

3 o’clock 

approach 

Mine body 

(GPR signal) 

6 o’clock 

approach 

9 o’clock 

approach 
11 

mine, the strongest MD response should occur at this point. As trainees show proficiency in 

locating the center of MD halos, trainers remove the requirement of chip placements. 

This MD halo center point serves as a reference for the first part of the GPR investigation, GPR 

“short sweep”. The results of GPR short sweep are the basis for identifying the source of the 

MD signals as a mine or clutter. Short sweep consists of movements of the sensor head that 

obey the technique requirements of search sweep but whose length is limited by the spatial 

extent of the MD halo about the center point. The outer limit for sensor head movement is the 

MD halo boundary, which should never be exceeded. If GPR signals reliably occur in repeated 

short sweeps, the decision rule operators are given dictates that they declare a mine. The absence 

of GPR signals indicates clutter if and only if proper GPR short sweep technique is applied. 

Violations of proper techniques frequently produce GPR signals, leading to operators making 

false alarms, that is, declaring clutter as mines. With the proper short sweep technique, many 

commonly found high metal objects, such as a nail or other metal fragment, are often small 

enough that the GPR will not detect them, thus allowing an operator to identify such items as 

clutter. 

If short sweep produces GPR output, operators are instructed to extend short sweep farther from 

the footprint center to identify the outer edges of the mine target at the 3-, 6-, 9-, and 12-o’clock 

positions. Locating these points, defined by the onset and offset of GPR signals, confirms the 

likely center of the mine target, which should be spatially coincidental with the MD center point 

for most mines (and all mine simulants used for training) with no adjacent metallic clutter. Such 

confirmation increases the likelihood of a declaration being scored as a correct detection or a 

“hit.” This is because the very stringent accuracy standard for scoring requires that poker chips 

used to declare mines be placed over or immediately adjacent to the body of a mine. 

Mine footprints vary systematically as a function of mine category. Figure 5 shows typical 

footprints for targets varying in size and purpose, antitank (AT) versus antipersonnel (AP), and 

varying metallic content, metallic (M) versus low metallic (LM). Note that the variability in the 

relations of the MD and GPR halos varies considerably across the four major mine categories 

(ATM, APM, ATLM, and APLM) represented in the set used for training. 

In figure 5, the black circles represent outer contours of mine targets (not drawn to scale). 

Shaded green regions indicate MD halos; red marks indicate where trainees are instructed to 

place MD halo marker chips. Orange marks indicate GPR return signals and are expected when 

the sensor head follows the trajectories shown by the thin black lines. Note the coincidence of 

the centers of the MD and GPR halos at the center of the mines. Also note that the sensor head 

trajectory for the ATLM (bottom right) extends beyond the MD halo—something that should 

not be done operationally but is illustrated here to demonstrate the location of GPR return 

signals. 
12 

Figure 5. Generic mine footprints: APM (top left), ATM (top right), APLM 

(bottom left), and ATLM (bottom right). 

Adjacent metallic clutter typically distorts the symmetry typical of the MD halos of mines in a 

clutter-free environment. The degree of distortion is related mainly to the size and shape of the 

clutter halo and its proximity to a mine’s MD halo. The shapes of MD halos for clutter are 

typically more variable than the MD halos for mines. MD clutter also generates subtly different 

audio signals (in terms of frequencies and amplitudes) than those produced by the mine simulants 

used in training. A significant implication of clutter-related distortion to MD footprints is that it 

increases the difficulty of correctly inferring the location of the MD center point used as a 

reference point for subsequent GPR investigation and declaration chip placement. 

2.4 Training Site 

The NET occurred at two different sites at Fort Leonard Wood, Missouri: Training Area 206 and 

the “pole barn” (see figure 6). The latter was a relatively new site with a one-sided pole barn that 

provided limited cover from bad weather. Initial observations for planning data collection occurred 

at both sites. Data collection was conducted only at the pole barn site because training that occurred 

during the time scheduled for evaluation was performed only at that site. Preparatory observations 

occurred at both sites. 
13 

Figure 6. Pole barn facilities; west facing view. 

The pole barn facility included five sterile (non-cluttered) lanes and nine off-route or tactical 

lanes. All lanes were 1.5 m wide by 15 m long and were divided into 10 equally sized cells. The 

sterile sand lanes were intended to have no clutter, but several items of clutter could be found in 

most of these lanes. The tactical lanes were in the wooded area surrounding the site. All had 

natural soils mostly cleared of surface vegetation. These lanes contained pre-existing clutter and 

clutter placed by trainers, although clutter locations were not mapped before this study. All lanes 

contained buried targets that included mine simulants with diameters of 6, 9, and 12 cm 

(representing APLMs), 20, 25, and 30 cm (representing ATLMs) as well as high metal M15s 

(ATMs) and M16s (APMs). Although all lanes had nine targets, often with one of each type and 

two mine simulants (SIM6s), the number of each type varied for some of the lanes. The 

implications of this lane-to-lane variability in target content, as well as the substantial variability 

discovered in the number of clutter items between lanes, are discussed later. 

2.4.1 Training Aids and Functions 

Two training aids are integrated in the training program. One is the SMS mentioned in the 

earlier discussion of search sweep and illustrated in figure 7. The second are scoring grids, 

devices used first for emplacing and documenting the locations of mine targets in lanes when 

they are constructed and later in training for scoring trainees’ mine declarations. 

The role of the SMS is to accurately and objectively assess the qualities of search sweep 

technique and provide feedback needed for Soldiers to learn proper technique. The motivation 

for including this device in the training package stems from the extreme difficulty that even 

highly skilled human observers experience in reliably and accurately judging whether a trainee’s 

sweep is within acceptable ranges on the multiple parameters listed earlier. 
14 

Figure 7. Sweep monitoring system (SMS). 

The SMS’s two cameras track the motion of the detector sensor head and continually document 

its position within a lane. When an operator moves the detector too quickly, too slowly, too high 

from the ground, or creates a gap in lane coverage, the SMS produces a voice message indicating 

the violation. The SMS records the head position data continuously over time as well as video of 

the operator sweeping. The data are displayed on a color-coded interface that maps the operator’s 

sweep activities (speed, height, gaps) for the entire drill. This graphical interface enables trainers 

watching the SMS monitor during the drill to easily detect and diagnose technique flaws and 

enables an operator to review his search sweep and identify problem areas. 

Scoring grids (see figure 8) are used to determine whether mine declarations made by trainees in 

training and certification testing can be classified as mine detections. The devices consist of a 

square frame made of plastic tubing with strings spaced at 15-cm intervals and extending vertically 

and horizontally parallel to the frame components. The matrix arrangement of strings, each 

labeled with a letter (A through J) on the horizontal axis or a number (1 through 10) on the vertical 

axis, creates a reference grid. Lanes are constructed with reference pegs along the boundaries so 

that the scoring grid can be reliably placed in the same location for each of the ten 1.5-m cells that 

compose a lane. Mine targets are emplaced with their centers at specific intersections of the grid, 

denoted by a unique letter and number combination for each cell (Cell 2, B-9, for example). Thus, 

by measuring the distance from a declaration chip to the grid location specifying a target center, 

adjusting for the target’s radius, and applying due diligence with respect to grid placement and 

measurement, we can accurately and easily categorize the declarations as hits or misses. 
15 

Figure 8. Scoring grid. 

2.4.2 Training Schedule/Sequence 

Training documents list the content and planned delivery sequence for course components as 

follow: 

• Day 1 – Classroom (6 hours), sweep technique demonstration and practical exercise; 

• Day 2 – Startup and calibration demonstration, mine footprint demonstration and practical 

exercise, 1.5 sterile lanes, two 2-minute runs on the SMS; 

• Day 3 – Tactical lane practical exercise; 

• Day 4 – Tactical lane practical exercise, kneeling and prone mine detection demonstration, 

written test review; 

• Day 5 – Written and performance tests. 

3. Method 

Evaluation methods focused on empirical observation of trainees engaged in AN/PSS-14 mine 

detector operator training. The collection of quantitative data documenting trainee performance 

was prioritized because learning occurring over the training periods represents arguably the best 

index of training efficacy. A variety of qualitative observations was collected, some 
16 

systematically, if they were anticipated based on events and observations encountered in the 

earlier training familiarization phase. Other unanticipated but significant events that occurred 

during the formal observation period were noted and described qualitatively in the results that 

follow. 

3.1 Participants 

Candidates for detailed observation were drawn from Active Army, Army Reserve, and Army 

National Guard units from Indiana, Ohio, Alabama, Alaska, and Colorado, who were scheduled 

for three separate week-long training sessions at Fort Leonard Wood, Missouri. All units but one 

deployed by January 2005; the remaining unit deployed by August 2005. Six operators from 

each session were randomly selected for detailed observation for the duration of their training. 

Participants’ ages ranged from 19 to 47 years with a median age of 29. All Soldiers selected were 

male except for one female, and their ranks ranged from Private (E-2) to Sergeant First Class (E-7), 

with a median rank of Sergeant (E-5). Of the 18 Soldiers who were observed, 7 had no previous 

mine detection experience and the remaining 11 had AN/PSS-12 training. Of the 11 Soldiers with 

training experience, one had AN/PSS-11, Minelab, and HSTAMIDS training experience, and one 

had used his AN/PSS-12 experience in a combat environment. 

All participants provided informed consent before any observation as prescribed in Army Regulation 70-25 and required by the internal review boards for the protection of human subjects of the 

authors’ institutions, ARL and CMU. A copy of the consent statement is shown in appendix A. 

3.2 Apparatus and Materials 

Equipment for data collection consisted of digital stop watches used to time and record events in 

trainees’ mine detection drills and certification testing. 

Several structured forms tailored for specific purposes and training exercises were designed to 

facilitate and standardize data collection. 

3.2.1 Training Experience Survey 

This is a participant survey to collect information about past experience with mine detection 

systems to include the type of mine detector, training, and if the individual had used the detector 

in counter-mine operations. 

3.2.2 AN/PSS-14 Ergonomics Questionnaire 

This is a questionnaire for participants to answer demographic questions and to rate the level of 

pain or discomfort with certain parts of their bodies before and after training. 
17 

3.2.3 Daily Log 

This is a form used to record time duration of the daily activities of participants. Activities of 

participant included arriving and departing site, classroom training, demonstration training, mine 

detecting, assisting other participants or instructor, breaks, and lunch. 

3.2.4 Sweep Drill Worksheet 

This is a form used to record the time trainees spent on sweep drills and support “battle buddies” 

engaged in these drills. 

3.2.5 Iteration Cover Sheet 

This is a form used to record the participant’s name, detector serial number, starting and stopping 

times, data collector’s initials, and the lane. 

3.2.6 Blind Search Observation Data Worksheet 

This is a form used to collect the timed observations of participants while they were operating the 

mine detector in a lane. The researcher tracked the location of the operator in the lane by cell 

number. Times were recorded for each activity that the operator completed such as search sweep, 

MD footprint development, GPR verification, GPR footprint development, or detector recalibration. The location of each target investigation was numbered and recorded on the lane map and 

data sheet. After each investigation resulting in a mine declaration, data collectors asked their 

respective operators for a subjective confidence rating on a Likert scale (1 to 5 scale range in 

which 5 = confident that the target is a mine, 1 = confident that the target is clutter) and recorded 

their responses. Events such as quick calibration of the system, noise canceling, presence of an 

instructor or trainer assisting the operator, and any other events or instructor comments deemed 

significant were recorded. 

3.2.7 Mine Lane Maps 

These are maps of the mine and clutter locations for each lane. 

Copies of all forms are shown in appendix A. 

3.3 Procedure 

Data collection began in the morning of the first day of each training week. Data collectors 

initiated recruitment by briefing all assembled trainees about the study’s objectives, the voluntary 

nature of their participation, and informed consent requirements. Those providing informed 

consent completed the training experience survey; the ergonomic questionnaire was then 

administered. Training proceeded with the classroom phase of instruction. 
18 

Upon completion of the classroom introduction, six randomly selected volunteers were each 

introduced to the data collector assigned to observe and document all of that person’s training 

activities. Data collectors recorded information about participants’ activities in a daily log. 

When trainees proceeded to initial drills on sweep techniques, data collectors “shadowed” their 

respective trainees as unobtrusively as possible to observe component activities, time stamp their 

starts and stops, and record instructors’ comments. At the end of the drill period, another 

ergonomic questionnaire was given to participants. 

On the second day of training, data collectors recorded events for their respective trainees in daily 

logs, beginning with start-up and calibration demonstration and drills, a demonstration of footprint 

development by an instructor, and trainees engaging in the footprint development exercises. As 

initially observed in training familiarization, footprint drills were not performed as focused 

exercises, as designed in the initial HSTAMIDS training. Instead, the footprint development drill 

was combined with search sweep to create a “blind search” exercise in the “sterile” lanes. Observations were therefore recorded on the Blind Search Observation Data Worksheets for subsequent 

practice on the sterile and tactical lanes. To better anticipate trainees’ activities and thereby facilitate data recording in blind search exercises, lane maps were constructed showing locations of 

mine targets and clutter based on data collectors’ observations. 

After each mine declaration made by each trainee undergoing observation, the data collector 

asked for a subjective confidence rating using the scale described previously which reflected that 

operator’s confidence that the declaration marked the location of a mine of any type. Following a 

trainee’s completion of blind search on a given lane, data collectors observed instructors’ scoring 

of declarations, noting the observations associated with successful detections and missed targets. 

The fifth day of training consisted of a certification test. Data collectors again used the same 

procedures and forms for events as those used in previous blind search exercises. Trainees were 

assigned a tactical lane that they had not previously completed in training and were required to 

successfully detect all the mines in the lane in order to pass. If, after completing the test lane, the 

participant did not detect all the mines, the participant was assigned another tactical lane for 

retesting. Only perfect detection performance in the first or second test met certification 

requirements. 

Following completion of field observations, data collectors entered all hand-coded observations 

into computer files for subsequent analyses. Anticipating later analyses by target type (APLM, 

APM, ATLM, ATM) or clutter, data collectors added appropriate categorical labels. 

3.4 Anticipated Results 

Several results were anticipated. First, based on performance in AN-PSS-14 operational tests 

(Santiago, Locke, & Reidy, 2004), one of the authors’ prior experience with HSTAMIDS 

operator training, and anecdotal reports about training effectiveness, the tracking of trainees’ 

detection rates over the course of blind search practice was expected to reveal learning curves 
19 

that peaked in the 97% to 100% range. Because the training was expected to provide trainees 

with prior knowledge and experience at footprint development before blind search exercises, it 

was anticipated that this prior experience would produce initial trial probability of detection (PD) 

well above where it would be expected to be, if no prior training had been given in those subskills (as suggested by the functions in figure 2). It was expected that first trial PD would be in 

the 70% to 80% range and would increase with practice to the 97% to 100% range. 

With feedback and review of any missed targets with trainers present to provide coaching, 

trainees’ increasing familiarity with the patterns of information that defined mine targets led to 

the expectation that they would gradually begin to distinguish mine targets from clutter. 

Trainee ability to recognize the patterns of AN-PSS-14 output that defined mine targets was 

expected to increase with practice, and with the feedback and coaching they were expected to 

receive, gains in operators’ confidence ratings were anticipated as a function of practice. 

Regarding the tracking of trainee MD and GPR investigation times for mine targets, a trajectory 

conforming to the power law of practice (illustrated in figure 2) was expected; however, specific 

ranges were not expected for starting times or ending times for either of the measures since these 

measures had never before been collected systematically. 

4. Results 

4.1 Time Distribution 

Data from the daily log worksheet were aggregated over the three observation periods to create a 

weekly time distribution to examine time allocations to events and activities occurring within the 

40-hour block of instruction. A summary of time allocation to various events is shown in figure 9. 

Lane time is defined as the duration an operator was in a lane engaged in blind search for mine 

targets. “Calibrate” or “sweep” was the time spent in calibrating the AN/PSS-14 or performing 

sweep drills without investigating targets (the detector was turned off for the drills). “Chip” or 

“observe” was the time spent in placing chips for another operator’s footprint development of 

targets during blind search or watching another operator use the detector. “Class” was time spent 

by participants in the classroom, listening to lectures or performing preventive maintenance checks 

and services. “Demo” was the organized time that all operators spent watching the instructors 

demonstrate specific techniques. “Lunch” reflects time spent on the daily meal break. “Break” or 

“waiting” was time spent warming on a cold day, standing around and talking with buddies, 

waiting for an instructor to grade a completed lane, waiting for a lane to open, and so forth. 
20 

Break/Waiting

5.6 hrs

Lunch

5.7 hrs

Demo

1.6 hrs

Class

7.1 hrs

Chip/Observe

4.8 hrs Calibrate/Sweep

2.1 hrs

Lane Time

8.7 hrs

Figure 9. Median weekly time distribution. 

These activities took 35.6 hours of the available training period on average. Of the 4.5-day 

training week, more than 30% of the time was consumed by lunch periods (4), breaks, and waiting 

periods. The proportion of time in non-training activities exceeded that spent practicing mine 

detection in the test lanes; note that the lane time for individual trainees ranged from a minimum of 

7.2 hours for one operator to a maximum of 16.0 hours for another. Chipping and observing time, 

whose instructional value is suspect, also varied widely, from 1.4 hours to 9.0 hours for 

individuals. Time allotments for remaining event categories showed relatively little variability. 

4.2 Probability of Detection 

PD measures the capability of an operator to detect the locations of mines and in this case, mine 

simulants. PD is the proportion created when the number of mine declarations scored as hits is 

divided by total number of mines encountered. 

Figure 10 displays overall PD for all trainees in the observed sample as a function of practice. 

The authors created the dimension of practice by ordering blind search trials in which all trainees 

engaged, noting that in most cases, the first two trials were labeled Footprint Development in the 

program of instruction (POI) but in effect, constituted blind search trials performed in the 

“sterile” lanes. Trial 7, also performed on a tactical lane in which a trainee had not practiced, 

represents each trainee’s first attempt at qualifying for certification. Results of re-test trials 

given to those who failed the first test are not shown. Error bars indicate the 95% confidence 

interval of the proportion (PD) as calculated with the modified Wald method (Agresti & Coull, 

1998). Caution should accompany the interpretation of the PD and confidence intervals because 

of measurement issues, discussed next, which threaten their validity. 
21 

Figure 10. Probability of detection versus trial number for all mine types. 

Two features of the function shown in figure 10 are noteworthy. The first is the surprisingly 

high initial trial PD. The second is the decline between the first two trials and the third. 

Differences in PD between Trials 1 and 3 were statistically reliable (z2, N = 233, = 5.39, p < .02), 

as were those between Trials 2 and 3 (z2, N = 282, = 11.3, p < .001). 

These features of trainee performance were examined as a function of mine category because the 

footprints that are the basis for accurate mine detection with the AN/PSS-14 differ considerably 

across categories. PD as a function of practice for APLM, ATLM, APM, and ATM targets is shown 

in figure 11. Trial 1 detection rates again show high performance levels, with the slightly lower 

performance for low metal targets (more difficult to find) versus high metal targets (expected). 

Differences between second and third trial performance vary considerably for different target 

categories. PD for ATMs show the form of classic learning curves, curvilinear monotonic increasing functions. In contrast, sharp declines of 30% and 20% are shown for APLMs and APMs, 

respectively, between Trials 2 and 3. 

The declines in PD between Trials 2 and 3 motivated examination of PD as a function of sterile 

versus tactical lanes (see appendix B for a detailed description of PD as a function of trials and 

lanes). A striking contrast was the difference in between-lane ranges in PD for the sterile (.05) 

and tactical lanes (.14). An analysis of the differences between the tactical lane with the highest 

overall PD (Lane I, PD = .93) and the three tactical lanes with the lowest PDs that were completed 

by more than one trainee, produced reliable differences between this lane and H (PD = 0.93, 

N = 187, z2

 = 6.13, p < .05), M (PD = 0.82, N = 151, z2 = 4.95, p < .05), and F (z2 = 3.55, p < .05). 
22 

Figure 11. Mean probability of detection versus adjusted trial number by mine type. 

Observations of training and testing produced two significant qualitative findings relevant to 

interpretation of PD and the related confidence intervals, which raised concern about their reliability. First, trainers or trainers in training often interrupted trainees while they were performing 

footprint development exercises and blind search drills in the tactical lanes in order to model the 

procedures and proper technique. The interruptions frequently consisted of the trainer (or a trainer 

assistant) seizing control of the AN/PSS-14 sensor head, performing the component steps of 

footprint development, and placing the declaration chips on targets. All declarations were scored 

and recorded, however, as if they were produced by the operator. This practice represents a source 

of measurement error likely to inflate PD for initial trials artifactually. 

A second source of measurement error was observed related to scoring conducted by trainers and 

trainers in training in the tactical lanes. Scorers were observed to score trainees’ declarations on 

most occasions by visually estimating the distance between a placed chip and a target’s reference 

point on the scoring grid placed on a lane from distances of 4 to 8 feet away, rather than using a 

tape or ruler to measure distance. An instance of this practice was captured on a video, and it 

shows a trainer making “eyeball” estimates of declaration-target distances at speeds (mean 4.4 

seconds, min = 2, max = 7 sec per “measurement”), hardly conducive to accurate measurement. 

Scoring accuracy was challenged by trainees on occasions. In three observed cases, declarations 

judged as misses by trainers performing scoring and protested by the operators involved were 

later shown to be hits upon a later careful re-examination by observers. Such lax scoring 

practices, whose incidence beyond the observed samples is unknown, invite measurement error 

in scoring. Such errors raise doubts about the accuracy of PD measures and produce inaccurate 
23 

feedback upon which trainee learning depends. The scoring errors documented here had 

negative consequences for the morale of the trainees involved. 

4.3 Confidence Ratings 

Figure 12 summarizes subjective confidence ratings given by each observed trainee for all mine 

declarations as a function of practice, distinguishing ratings given for mine targets and those 

given for false alarms (clutter mistaken for a mine). Error bars in this figure represent the 95% 

confidence interval for each mean. Confidence as a function of practice for each of the four 

target categories is shown in figure 13. 

Figure 12. Mean confidence rating versus trial number: all mines versus clutter. 

The salient feature of the functions shown for mines in figure 12 is their negligible slopes. These 

functions and related summary statistics in table C-1 show that the mine detection practice 

provided over the course of training does not reliably increase an operator’s self-assessed 

confidence in his or her capability to detect targets—an effect contrary to the gains expected from 

training. Although the obvious differences in confidence ratings for targets and clutter items 

suggest that operators should develop some sensitivity to the signals that distinguish targets from 

clutter early in training, subsequent practice does not improve this sensitivity from its baseline 

level. Note that the value of 5 represents that an operator feels “confident” that a given declaration 

marks the location of a mine target. 
24 

Figure 13. Mean confidence rating versus adjusted trial number by mine type. 

Figure 13 shows differences between operator confidence for declarations related to metallic and 

low metallic targets, with high metal targets consistently receiving higher confidence ratings over 

the course of blind search trials. Examination of the summary statistics for confidence ratings in 

table C-1 confirms no effect of practice for ratings for APLM or ATLM targets, the threats that 

heavily motivated the development of the AN/PSS-14. 

4.4 Investigation Times 

An investigation event was defined as an operator’s sequential application of MD techniques and 

GPR techniques to an area where an alerting signal occurred. This definition ignores the order of 

technique application, noting that trainees are instructed to first perform an MD investigation on 

a suspected target and then use its findings to guide GPR investigation. Because investigation 

times include sensor-specific investigation activities as well as acts such as quick calibration or 

grip adjustment, investigation time in such instances exceeds the sum of MD and GPR investigation times. 

Figure 14 illustrates investigation times, MD investigation times, and GPR investigation times as 

a function of practice. Medians summarize the temporal measures attributable to the consistently 

skewed form of these time distributions. Medians were calculated after removal of outliers, 

defined as times that were greater than three times the value of the fourth spread beyond the 75th 

percentile value (Hoaglin, Mosteller, & Tukey, 1983). Additionally, the lowest percentile and 

other clearly erroneous times, such as investigation time with zero duration, were trimmed before 

median calculations. 
25 

Figure 14. Median investigation times (total, MD, and GPR) versus trial number 

for all mine types and clutter. 

Investigation time for all targets (mines and clutter) decreases substantially (57%) with practice, 

also showing a curvilinear trend consistent with the power law of practice (Newell & Rosenbloom, 

1981). This general description, as well as the magnitude of the apparent training effect, applies to 

the functions for investigation times for targets and clutter and for the durations of MD investigations for targets and clutter. Decreases for GPR investigation times as a function of practice tend 

to be much more modest, about half the percentage decrease seen for investigation and MD 

investigation times. 

Results from fitting the power curve function (y = Cxb

) to the temporal investigation time measures 

are shown in appendix D in tables D-4, D-5, and D-6, and in figures D-4 through D-18. Despite 

high variability resulting in relatively poor fits, three noteworthy consistencies emerge. First, 

comparative examination of R2

 values in tables D-4, D-5, and D-6 shows that the best fits are 

achieved for investigation times and MD times related to mine targets. Second, fits of GPR 

investigation times are quite poor across all target types and clutter. Third, fits to the investigation 

times, MD times, and GPR times for clutter are poor. Examination of slope estimate (b) magnitudes 

in tables D-1, D-2, and D-3 shows that the lowest values are related to the functions for GPR 

investigation and clutter targets. Inspection of figures D-4 through D-18 shows consistently greater 

dispersion of individual data points from the predicted values at each practice level for the poorer 

fitting functions, with one noted exception: high dispersion is characteristic of investigation, MD 

investigation, and GPR investigation times for metallic targets. 
26 

4.5 Rate of Advance 

One measure of operator performance that is of considerable operational importance is ROA. 

ROA measures the speed with which a given area can be cleared of mines and made safe for 

maneuver. Slow mine detection and clearance compromises operational tempo and threatens to 

desynchronize various tactical elements of mission and disrupt plans. 

The areas or lanes on which participants performed blind search exercises were 1.5 m wide by 

15 m long, whose perimeters were marked and whose interiors were divided into ten 1.5-m by 

1.5-m cells. Not all cells were swept on all trials, e.g., Trial 1 typically involved a search of five 

contiguous cells, but trainers sometimes truncated the first and latter trials on an arbitrary basis. 

To measure advancement, taking into account the different areas actually covered in trials, ROA 

values are presented in units of square meters covered per minute (m2/min), making ROA values 

independent of the specific area covered. 

Figure 15 illustrates the median rate of advance for all participants as a function of practice. The 

medians displayed were computed after the removal of outliers, defined as values greater than 

three times the fourth spread from the 75th percentile (Hoaglin, Mosteller, & Tukey, 1983). 

Error bars indicate the 95% confidence intervals for the resulting central tendency estimates. 

Despite the absence of any speed requirements, a trend indicating increased coverage speed is 

seen through Trial 6. A regression in speed was observed for the final trial, which represents a 

trainee’s initial attempt to qualify for operator certification. 

Figure 15. Median rate of advance versus trial number. 
27 

Summaries of ROA as a function of variables other than practice are presented in appendix E. 

Included are descriptive statistics for ROA by lane (table E-1) and by participants who passed 

the first test (Trial 7) and those who did not (table E-2). The information is also presented 

graphically in figures E-1 and E-2. 

A noteworthy finding shown in figure E-2 is that ROA functions diverge after Trial 3 for trainees 

who pass the initial certification trial (Trial 7) and those who fail, with the successful operators 

showing faster ROAs. The unsuccessful operators also show a greater reduction in ROA 

between Trials 6 and 7, with Trial 7 falling slightly below the ROA that this group demonstrated 

in its initial trial. 

Noting that no time limit was imposed on testing and operators were told to take all the time that 

was needed, extreme differences among operators were observed. Some completed their lanes in 

as few as 35 minutes, but one took 3 hours 45 minutes to complete one lane. 

4.6 Qualitative Observations 

The number of trainers varied substantially from week to week. For the first training week, the 

three regular NCO trainers were supplemented by two civilian contractor trainers from Cyterra, 

the manufacturer of the AN/PPS-14. For the second training week, there were no civilian 

trainers. In the third training week, three civilian trainers were supplied by Battelle Corporation. 

In addition, as many as ten trainer assistants (TAs) in one week and as few as one in another 

functioned as trainers by observing, critiquing, and coaching trainees. 

The quantity and quality of training that trainees received varied substantially within weeks and 

between weeks for several reasons. First, TAs were Soldiers who had trained and qualified for 

operator certification only the previous week and so possessed relatively little experience with 

the AN/PSS-14. Their training skills varied considerably as well. Numerous instances were 

observed in which a TA seized the detector head from an operator who was thought to exhibit 

poor technique, proceeded to investigate a target from a kneeling position using poor technique, 

and then ended his demonstration lesson with comments such “see that?” or “get it?” Different 

TAs also gave contradictory advice about technique to trainees, which often resulted in trainee 

confusion and frustration. 

Problems with the operation of the SMS, which occurred frequently, reduced the pool of 

appropriately qualified trainers available to observe and coach trainees. Only the regular trainers 

had sufficient familiarity with the SMS to diagnose and (sometimes) fix the problems. 

Simultaneous responsibility given to the resident NCOs for supervising, coaching, and evaluating 

the TAs further reduced their availability to work with the trainees. 

Supervision of trainees fell dramatically once training exercises moved to the tactical lanes for 

several reasons. One is that the tactical lanes were dispersed in the wooded area around the pole 

barn, requiring a trainer to be close to an operator to observe his technique. Because as many as 
28 

six operators might be engaged on different lanes simultaneously, experienced trainers, 

especially when their numbers were low, could only split time among operators by walking from 

lane to lane. Because trainers scored completed lanes, this task further reduced their availability 

for observing trainees. 

Finally, during test and practice trials on the tactical lanes, the experienced trainers showed a 

marked tendency to congregate under and around the pole barn, venturing out occasionally to 

observe and coach (if deemed necessary) trainees for short periods. This tendency to congregate 

under the shelter of the barn was exaggerated during conditions of harsh and inclement weather, 

which dominated for the three observed weeks. In fairness, longer periods of observation and 

often excellent coaching were devoted to trainees regarded as needing coaching on the basis of 

their performance. At the same time, during substantial portions of trainee activity on the 

tactical lanes, observers frequently noted deficient technique as well as safety violations that 

went unnoticed by trainers, even during certification testing. 

Regarding SMS usage, reliability problems resulted in frequent down time, limiting the amount of 

time that it could be used to provide trainees with the feedback needed for achieving proficiency. 

This shifted the burden of accurately assessing trainee technique (a difficult task for even the most 

experienced personnel) and providing feedback to the available trainers. When the number of 

trainees engaged in sweep drills exceeded the number of available trainers, they were denied 

consistent feedback. 

5. Discussion 

This study was undertaken with the assumption that the AN-PSS-14 training conducted at the 

USAES was effective and that efforts focused on identifying means to improve its efficiency. 

Our observations have raised doubt about the validity of our assumption and issues about the 

effectiveness of AN/PSS-14 training as it is being delivered. 

The remainder of this section discusses the bases for questioning training effectiveness found in 

the results, organized by sequence of results reported in the previous section. Following 

discussion of results, recommendations for changes are made whose implementation, we believe, 

can raise the quality of AN/PSS-14 operator training to the standards of the USAES and the 

capability of operators to the level demanded by the current mine threat. 

5.1 Time Distribution 

A major concern related to the Army’s adoption of the AN/PSS-14 is the costly 40-hour block of 

training required for its operators. Individual operators, however, do not receive 40 hours of 

training. Results from this small sample of training sessions show that the average operator 
29 

spends but a fraction (22%) of the 40 hours on the most important component of training: mine 

detection drills (blind search). A larger proportion of each cycle’s training time is expended on 

lunch, waiting, and breaks. Realistic task practice accompanied with accurate and timely 

performance feedback and coaching is essential for skill acquisition. Because maximizing task 

practice (within the available boundaries) is the key to maximizing learner capabilities, and 

maximizing the returns of practice requires a prior base of knowledge and basic skills, increased 

individual detection practice time following essential preparatory instruction and drills should 

improve training. 

Surprisingly, little time was spent on footprint development, the core and most complex 

component of AN/PSS-14 operation. The extent of instruction focused explicitly on this critical 

subskill was a 15- to 20-minute demonstration, although in one week, roughly half of that time 

was used to demonstrate footprint development for only two of the four mine types. Moreover, 

footprint development exercises were eliminated. Instead, as described earlier, footprint development practice was merged with search sweep into blind search drills with sporadic and often 

inconsistent instructor guidance while the operator practiced. Few Soldiers appeared to execute 

the techniques involved correctly without direct instruction from trainers. In the case of the 

training period with a severely shortened instructional demonstration, observers from the Night 

Vision and Electronic Sensors Directorate of the U.S. Army Research, Development, and 

Engineering Command who were present (an NCO and a civilian) intervened and initiated 

individualized footprint development tutoring for trainees in response to the obvious confusion 

they exhibited in executing this task in the context of blind search drills. 

The time allocated for sweep and system calibration drills appeared sufficient, based on trainee 

performance, although the amount of time spent on the SMS during sweep drills was sharply 

limited because of the unreliable operation of this system. Because the performance feedback 

that the SMS provides (when working properly) is likely far more accurate than that a trainer can 

provide, maximizing the proportion of SMS time with the current limits of that allocated for 

sweep drills is desirable. Given the purchase cost of this equipment and the sunken costs related 

to its deployment, its limited use provides a very low return on investment. 

The 7-hour block of time of classroom environment, even with interleaved breaks, challenged 

Soldiers’ ability to maintain concentration and to acquire and retain the volume of detailed 

information presented. Much of this information had to be represented outside the classroom to 

enable all Soldiers to perform drills correctly, which suggests information overload in the 

classroom. 

Although breaks in training are needed for recovery from physical fatigue and relief from intense 

concentration that AN/PSS-14 operation demands, a disproportionate amount of trainee time was 

spent off-task for lunch, hourly breaks, and waiting. Chipping or observation time provided 

limited benefit to participants; often, the time was spent watching surrounding activities or 

chatting with a buddy. 
30 

5.2 Probability of Detection 

Detection rates are the core measure of operator skill and the effects of training. Interpretation of 

detection rates in the results section in order to evaluate training effectiveness is problematic for 

several reasons. Two reasons described in the results are the tendency for trainers (or assistant 

trainers) to intervene in blind search drills and make declarations for trainees, and the outrageously 

imprecise declaration scoring procedures used. These raise questions about the accuracy of the PD 

measures recorded. 

In addition, PD, especially in test trials (Trial 7), is likely inflated by some operator strategy of 

lowering the criterion for making a mine declaration and increasing the number of declarations 

placed, thus increasing the likelihood of hits along with the false alarm rate. Trainees talked 

openly about using this strategy to “pass the test” and receive certification. In one observed 

instance, a participant placed multiple chips near each declaration in hopes that at least one chip 

would be near enough to count as a hit. It worked; 63 chips were laid to mark the nine mines (and 

miscellaneous clutter), enabling the participant to pass the test. Another test strategy involved 

exploiting speed/accuracy; the ROA results show a distinct decrease in ROA from Trial 6 to 

Trial 7, while PD for APLMs and ATLMs shows an upward inflection at the same point. The 

absence of performance standards for false alarm rates or ROA invites a test-wise shift in operator 

strategy. The strategies that appear to have been implemented confound interpreting changes in 

PD as a function of practice as a reflection of trainee learning. 

Still another issue challenging the interpretation of PD measures as indicators of training effectiveness involves test conditions. Test lanes differed not only in the number of clutter items but also in 

the proximity of that clutter to targets. Observations reveal that the presence of clutter adjacent to 

low metallic targets increases the difficulty of their detection. Thus, the tests taken by some 

operators were more difficult than the tests taken by others. It follows that an operator who can 

successfully detect all targets in a lane with few clutter items adjacent to the LM targets would have 

a much easier time meeting the certification criterion and could do so with a lesser level of skill 

than if he had been assigned a lane for testing on which clutter items were adjacent to LM targets. 

Acknowledging the scoring and test strategy issues, 6 of the 18 operators missed mines on the 

first test (Trial 7)—a costly attrition rate. In addition, PD for the group on low metallic APs and 

ATs on Trial 7 is well below the certification criterion. These observations, plus the suspiciously 

shallow slope of PD function between Trials 3 and 6, raise concerns about training effectiveness. 

PD is the primary basis for operator certification. The observed measurement and scoring 

problems raise concerns about the validity of the certification process. 

5.3 Confidence Ratings 

The unchanging confidence ratings for clutter and mines through the week indicates that participants perceived little change in their capability to detect targets or distinguish target from clutter 

as a result of the instruction and practice they received. 
31 

The clear separation between the functions for mines and clutter in figure 12 indicates that trainees 

acquired some sensitivity to the difference between the signals produced by mine targets and those 

produced by clutter. However, clutter confidence hovering around the value of 3 suggests that 

participants were “confident” that clutter items were targets but less so than for actual targets. 

Participants frequently stated a confidence rating of 3 accompanied by the comment “There’s 

something there; I just don’t know what it is.” 

One of the purposes in transitioning from the AN/PSS-12 to the AN/PSS-14 was the added 

ability to discriminate mines from clutter through the use of GPR and to consequently reduce the 

number of targets that must be confirmed as mines by probing. Instructions to trainees stated 

that GPR signals occurring over the center of a metallic halo confirmed a mine target. 

Conversely, if no GPR output occurred over a metal signature, then the target was probably 

clutter. However, if the operators were unsure about the identity of a target, they were instructed 

to mark it as a mine. 

Beyond this decision rule, clearly specified characteristics for correct GPR investigation techniques 

were not given to trainees. In fact, different NCO trainer demonstrations of this technique over 

targets showed wildly different search head velocities; this variability was reflected in trainee 

techniques, often with the consequence that the swings artificially produced GPR signals over 

clutter items. 

Another phenomenon confused trainees about GPR operation and interpretation of GPR signals. 

Even over mine targets, the production of GPR signals varied from swing to swing with the 

variability clearly related to two factors: the characteristics of the sensor head movement and the 

metallic content of targets. Regarding sensor head movement, increases in swing velocity and 

length unheeded by the operator could often produce GPR output where previously he had 

received none. For metallic targets, longer GPR investigations over the high metal targets often 

produced an increasing number of GPR returns over a larger area than occurred initially. Execution of a quick calibration operation followed by resumption of GPR investigation of the target 

returned GPR output to the original levels and area. This variability in GPR response appeared to 

confuse operators. 

Signs suggesting confusion included statements by trainees such as “What’s wrong with the 

system?” or “What’s going on?” Less explicit signs took several forms. Observation showed 

numerous occasions when an operator received no GPR signal but marked the target as a mine 

nevertheless because “there must be something there.” In other instances (even seen on Trial 7, 

the certification test), operators performed investigations with MD only, without any GPR 

investigation, thus ignoring the functions of GPR sensing and using the AN/PSS-14 essentially 

as a metal detector. 

We attribute the inferred confusion, consistent with the differential confidence ratings for M and 

LM targets in figure 13, primarily to three factors: (1) lack of explicit training guidelines for GPR 

investigation technique, (2) absence of explicit footprint development drills, and (3) absence of 
32 

timely performance feedback telling an operator if a mine declaration was a target. Changes in 

training addressing these factors are included in the recommendations discussed in section 6.3. 

5.4 Investigation Time 

One approach to identifying and evaluating operator skill development throughout the training 

week was to examine changes in performance and subjective confidence as a function of 

accumulated task practice. The expected form for time-based performance measures is the 

exponential decrease illustrated earlier in figure 2, i.e., large reductions in task execution times in 

early practice trials followed by continuously diminishing reductions as task practice accumulates. 

Results show that learning curves of this form are observed for investigation times and MD 

investigation times. The GPR functions, on the other hand, suggest minimal learning on this 

component of AN/PSS-14 operation. We therefore attribute the gains in overall investigation 

times largely to increasing proficiency in MD investigation with practice. 

Why might gains in MD investigation skill occur but not in GPR investigation? Part of the 

answer was discussed earlier; training content and procedures offer little support for learning to 

use GPR effectively. In contrast, the robustness of the MD system produces output more 

reliably. MD signals are far more consistent in yielding the results described in instruction and 

demonstrated by trainers, thus providing implicit feedback needed to support learning. The 

performance feedback given after each trial is likely to lead trainees who rely heavily on MD 

signals to make declaration that such a strategy can yield acceptable performance and enable 

them to meet the certification standard (especially in the absence of any false alarm criterion). 

In short, training content and practice may unintentionally lead trainees to operate the advanced, 

very capable AN/PSS-14 much in the same fashion as its predecessor the AN/PSS-12 and other 

EMI detectors in the Army’s inventory. 

5.5 Rate of Advance 

Several factors appear to contribute to improvements in ROA that occur with practice. The 

improvements seen in MD investigation times are one factor; increased efficiency in search 

sweep is likely another. 

It is unclear, however, how well ROA measures reflect learning. On one hand, the divergence of 

tactical lane ROAs for trainees passing their first attempt at certification suggests that ROA is 

predictive of skill. Evidence for a speed-accuracy trade-off in Trial 7 suggests otherwise, noting 

that the trainee with the longest lane time (3 hr 45 min) passed the first test. It is reasonable to 

ask whether individuals whose lane coverage times exceed those of other successful operator 

really understand the fundamentals of AN/PSS-14 operation. A negative feature of exceptionally 

slow ROAs is that lengthy trials stifle the flow of training and leave operators who are scheduled 

for the occupied lanes waiting idly and unproductively for extended periods. 
33 

Another problem in interpreting ROA as a measure of an operator’s skill is the variability among 

lanes in the amount of clutter they contain. The mean number of clutter items per lane is 25, but 

the count ranges from 11 (Lane N) to 42 (Lane H). Generally speaking, more clutter items 

demand more investigations, which result in longer trial durations and lower ROAs. This is 

reflected in an inverse relation between number of clutter items in lanes and median ROAs. In 

short, the practical implication is that any valid comparison or interpretation of individual ROAs 

must control at least for the number of clutter items in a lane. 

5.6 Performance Feedback 

A number of results, including those suggesting successful learning (MD investigation times), 

questionable learning (PD), and negligible learning (GPR investigation times), can be explained 

in terms of the performance feedback provided. Performance feedback (i.e., information about 

the success or failure to achieve the goal set for a task) is critical for effective and efficient 

learning. Task practice without accurate and timely feedback yields negligible learning. 

In blind search trials, feedback consisted mainly of an operator receiving information about the 

number of mines missed after scoring occurred. Locations of missed targets were marked and the 

operator returned to each and conducted another investigation in the area of the marker, supervised 

and critiqued by a trainer. Unless a target was missed, operators had little opportunity to associate 

the patterns of signals produced by individual investigations with targets. This policy provided 

little useful feedback to trainees to support development of mine detection skills. This would 

account for little improvement in PD over the course of practice on the tactical lanes and the flat 

confidence functions. The limited feedback provided minimal opportunity for learning to differentiate the patterns of signals produced by mine targets and those produced by clutter. Trainees 

were uncertain whether declarations should be marked as targets or as clutter, as was evidenced by 

the confidence ratings they gave to clutter items. 

The paucity of feedback also appeared to cause morale problems that likely impeded the learning 

of some. Expressions and signs of frustration as to what was in the ground were abundant. 

Doubt and frustration often turned into an attitude of indifference. 

In contrast, for MD investigations, implicit feedback about performance was available, and 

trainees’ exhibited learning curves were of the sort expected. 

The negligible improvement in GPR investigation times can be interpreted in terms of the 

feedback available. The inconsistency with which GPR signals could be produced and trainees’ 

lack of knowledge about the buried items producing GPR signals denied implicit feedback. The 

absence of clear, objective criteria for what constituted proper GPR short sweep technique made 

it impossible for trainers or operators to assess the quality of the search head movements 

executed. 
34 

5.7 Certification Standards 

USAES certification of trainees is based primarily on PD, the accurate measurement of which 

involves several standards. First, the performance standard requires that an operator find all nine 

targets in his first or second test. Measurement of performance (i.e., PD) is based on a scoring 

standard: to be scored as hits, a declaration marker (a poker chip) must be placed so that it 

overlaps or is adjacent to the body of a given target. Valid scoring of declarations depends on 

meeting a measurement accuracy standard: that the distance from the edge of a marking chip to 

the nearest edge of a target’s body is accurately measured. 

Problems observed and related to each of these standards call the validity of the certification 

process into question. The practical implications of this situation are that “certified” operators 

can vary considerably in their capability to operate the AN/PSS-14 effectively and safely and 

that some may actually fall below the desired level of proficiency that certification procedures 

were instituted to ensure. 

Obtaining accurate target-chip measurements was problematic for several reasons. First, as 

described earlier, quick visual estimation rather than careful measurement predominated. Such 

procedures surely introduce error, especially if they are made in 4 seconds by a grader standing 

8 feet away from and 5 to 6 feet above the points to be measured. Second, one of these reference 

points is the intersection of two strings on a scoring grid. The accuracy of any measurement using 

that intersection point depends on accurate placement of the scoring grid. Careful placement of the 

scoring grid was inconsistent. Third, mines tend to migrate beneath the ground surface after burial 

and there are several indications that some targets did so. Care must be taken to locate their actual 

centers and record their position on grading sheets; these new positions should serve as reference 

points for measurement. No such notations were found on the grade sheets. Instead, in some 

cases, graders probed the ground to find the mine and estimate its center point. Two draw-backs 

make this solution untenable; the ground can only be probed when it is not frozen, which it was for 

several days during the last week of observations. Successful probing, when possible, creates 

another problem; it leaves visible cues indicating the locations of targets for later trials. Some 

graders obscured the probe marks by scuffing the ground surface, thus substituting visible scuff 

marks for signs of probing! Such marks were noticed and clearly used by trainees, with the likely 

consequence that it made the targets in question easier to detect. 

In short, very stringent accuracy standards have been adopted for scoring and laudably so; equally 

stringent standards and quality assurance should apply to chip-target measurement distances. 

Indeed, accurate feedback needed to support trainee learning depends first upon accurate 

measurements and scoring. 

A second issue arises regarding the scoring criteria adopted. A far more liberal scoring criterion 

that adds a 6-inch halo to the perimeter of target bodies was employed by USAES and for 

operational testing of the AN/PSS-14. The current, stringent scoring criterion could account for 
35 

the failure to observe the PD achieved in operational testing and reported by Santiago, Locke, 

and Reidy (2004). 

Issues were also discovered regarding the criteria used for certification. Specifically, the absence 

of false alarm rate or test time standards puts at risk the certification of operators who may not be 

qualified to operate the AN/PSS-14 in operational environments. Omission of standards for these 

measures invites strategies for operators to “game” their way to certification. Trading speed for 

detection accuracy, as observed and noted earlier, can produce certification under the current 

standards. However, application of this strategy in the operational environment would be likely to 

compromise operational tempo, possibly threatening mission success. A strategy that accepts high 

false alarm rates to achieve 100% PD in the test environment would likely pose a similar problem 

in live operations, since the time needed to confirm declarations via probing would absorb 

prohibitive amounts of time. 

Finally, application of existing certification standards to trainees tested on different lanes applies 

the same standard to tasks of differential difficulty. This is because the lanes used for testing 

differed in the number of clutter items they contained by a factor of more than 3; the test lane 

with the lowest number of clutter items contained 11 (lane N), and the test lane with the highest 

number had 36 (lane K). If, as it appears, clutter placements adjacent to low metal targets 

increase the difficulty of their detection, lanes with higher clutter counts are more likely to 

produce this condition (assuming random placement of clutter), making such test environments 

more difficult than lanes with less clutter. One practical, hypothetical consequence of de facto

differential standards is that meeting the 100% PD standard on tests that are easy may certify 

operators who lack the skills needed to accomplish missions in an operational environment. 

Alternatively, testing on excessively difficult lanes may results in operators failing to receive 

certification, who have the skills needed to successfully execute counter-mine operations. The 

latter “error” scenario reduces the pool of operators available and wastes resources invested in 

training the individuals who are erroneously denied certification. 

Apart from the PD criterion for certification, safety violations committed by trainees constitute 

grounds for denial of certification. Such violations committed by trainees, some of whom 

received certification, were observed in training and testing, although many were not noticed by 

trainers. 

5.8 SMS Equipment 

The problems experienced with the SMS resulted in the use of this training at a level lower than 

planned. The SMS offers a very powerful tool for providing feedback critical to trainees’ learning 

of effective search sweep technique and providing trainers and trainees with information to 

identify and diagnose technique problems. 

The reliability problems observed had two negative consequences. First, the problems denied 

trainees feedback, which even experienced trainers are challenged to provide. Second, time 
36 

devoted to system setup, diagnosis and solution of its operational problems by NCO trainers 

reduced the number of experienced trainers available to observe trainees in ongoing sweep drills 

and to provide feedback and diagnose problems. 

Considering the purchase cost of the SMS and the sunken costs related to its deployment, its 

limited usage represents a poor return on investment. 

5.9 Limitations 

Limitations of this research include two main issues. The first is the issue of generality. Quantitative data were collected from a relatively small sample of 18 operators participating in three 

different training sessions, of the approximately 150 Soldiers trained each year. Second, the 

collection of data outdoors in challenging weather was arduous and demanding. Although all 

involved sought the highest levels of accuracy, some errors of commission and omission in 

recording and transcription must be expected. To counteract threats to validity that such errors 

might introduce and to mitigate their effect by statistical means, we have attached confidence 

intervals to the applicable results. When measurement error was beyond our control, that is, in 

PD measures, we have explicitly noted the problems posed for interpreting the results in the text. 

Regarding the issue of generality, it is important to note that many of the significant qualitative 

observations made during the 3-week sampling window (e.g., PD scoring issues, minimal 

focused footprint development instruction, SMS problems and under-use) were seen not only in 

the 2 weeks of preparatory observation at the USAES but also in a training session conducted for 

USMC trainees at Camp Lejeune, North Carolina, by Cyterra trainers in which one of the authors 

participated. This convergence undermines arguments that the observations reported in this 

study cannot generalize beyond their narrow sampling context. 

6. Recommendations 

6.1 Curriculum: Content and Time Allocations 

The recommended distribution of time for tasks throughout the week should include an additional 

category for footprint development and eliminate time for chipping and observing. Figure 16 

shows the proposed time allotment for tasks. The 6 recommended hours for footprint instruction 

should include multiple demonstrations, practice time in a sterile area, experimentation time where 

multiple targets can be laid in proximity, and practical time when instructors can observe operators 

in an unmarked, low-clutter lane. Actual lane time should be increased by 5.5 hours to 14.2 hours. 

Class time should be reduced; shorter, spaced classroom sessions interspersed with hand-on exercises will help operators to better remember the information needed to practice proper techniques 

and develop sweep and footprint skills. Chipping and observing should be eliminated in favor of 
37 

practical exercises. “Wasted” time for lunch, especially the usual inflation of allotted time related 

to travel off site, can be eliminated if the lunch break is limited to 30 minutes and trainees are 

required to bring lunches. More disciplined administration can easily reduce time wasted on 

inflated break times and waiting for lanes or equipment to become available. Time allocations for 

demonstrations and calibrate or sweep drills should stay the same. 

Lane Time

40%

Calibrate/Sweep

6%

Footprint Development

17%

Class

8%

Demo

4%

Lunch

11%

Break/Waiting

14%

Figure 16. Recommended weekly time distribution. 

6.2 Performance Feedback 

Operators need more supervision. Part of the difficulty in increasing supervision and the delivery 

of immediate feedback is the limited availability of instructors, but that does not diminish the need 

for prompt feedback on what the operator is doing, right or wrong. Effective and efficient skill 

acquisition demands it. 

These statements equate feedback with accurate feedback. The scoring problems and SMS 

problems observed need to be fixed to provide trainees with the needed feedback. 

6.3 Training Content 

The most important substantive change recommended in training content is the inclusion of 

footprint development and allocation of time to its instruction and practice. Absent footprint 

development drills, trainees can rarely, if ever, know that the MD and GPR signals received in 

an investigation are those produced by a mine, unless they have missed a target. Denial of information impedes a trainee’s learning and undermines effective and efficient acquisition of mine 

detection skill. The suggested time distribution invests 6 hours of the 40-hour instruction week 

to footprint development instruction and practice. 

Training content needs to be standardized. One of the largest difficulties encountered across the 

3 weeks of observed training was the variability with which instructors were present. Each of 

the instructors had different ideas about how much information to present, how the detector 
38 

worked, which technique to use, and what content should be emphasized. As an example, 

several instances of instruction promoted the use of chipping an inner halo on high metal targets 

to facilitate finding the center of the target. The outer halo that is normally chipped is located at 

the first audible sound the detector produces surrounding the target (for high metal mines, this 

halo can be 30 inches in diameter). The inner halo is located where the detector tone distinctly 

jumps from a low pitch to a high pitch. The trouble with the inner halo technique is that if the 

operator in any way misunderstands or forgets that the area between the outer and inner halos is 

not assuredly safe, someone may step on a “hidden” mine, a low metal mine whose signature is 

hidden within that of the high metal target. Techniques must be standardized to prevent these 

mistakes and the hazards they create. 

As another example, instructors differ in what constitutes proper sensor head velocity for GPR 

short sweep technique. In the absence of clear and accurate specification of an effective and 

acceptable range, trainers and trainees have only their intuition to rely upon to assess technique. 

Unfortunately, such intuitions can be contradictory and simply wrong. 

The long continuous block of classroom instruction on the initial day of training should be 

shortened, with its contents redistributed and interspersed with hands-on activities. Doing so 

would better support operators’ retention of the theory and procedures presented, which are 

necessary to practice and learn effective techniques. In addition, efficiency would be gained; 

we found that much of the content presented in the continuous block of instruction was being 

repeated before hands-on exercises because trainees had not retained it. Following an overview 

of training and an overview of the system and its operation, the content of each subsequent 

instructional segment should be limited to just the information needed to support trainees’ proper 

execution and practice of the activities covered. 

An explicitly “scaffolded” approach to instruction (also expressed as the “crawl, walk, run” 

instructional strategy) will facilitate skill development, and we recommend its adoption. Basic, 

component skills should be taught in isolation. Tests should follow each instructional unit to assess 

trainees’ proficiency in these sub-skills. Testing at each stage or level of training would help 

instructors determine which operators are struggling early in the week so that focused diagnosis, 

remediation, and additional practice can be given. Such early intervention allows struggling 

operators to clarify task requirements while the instructor is present, specifically to answer questions, coach proper technique, and provide feedback. Most participants did not seek instructors 

with questions; they only asked if instructors were conveniently near or if an instructor had already 

engaged them in conversation—events that were too infrequent. Practicing improper or weak 

techniques led to the acquisition of “bad habits,” which are difficult and costly to reverse later. 

Trainers’ effectiveness is diluted by the dual responsibilities assigned; they are to instruct, coach, 

and assess new operators, and when TAs are present, they are to instruct, evaluate, and test TAs. 

Training personnel should be assigned and dedicated to one instructional task or the other. Implementing this recommendation carries nontrivial immediate costs: it would require additional 
39 

qualified trainers. We believe that the benefits that would accrue by enhancing the training of new 

operators and new trainers could offset and justify the cost, especially if it decreases the trainee 

failure rate. 

There are two elements of training in which instructors and trainees are handicapped by a lack of 

information about AN/PSS-14 operation: system calibration procedures and GPR short sweep. 

In both cases, the gaps in knowledge result in (1) trainees lacking clear descriptions of the 

techniques that become their goals to acquire and practice, and (2) trainees and trainers lacking 

clear standards for assessing trainee performance of these significant functions. Trainers can 

only “eyeball” an operator’s technique and guess whether it is good or bad, lacking clear and 

specific guidelines for distinguishing between techniques that prepare the sensor systems for 

effective use and those that do not. The validity of any feedback they provide is therefore 

suspect, if any feedback is given to a trainee. 

Instructions describe system calibration procedures as critical for safe and effective operation of 

the AN/PSS-14. However, no objective empirical standards are available for reliably and validly 

assessing whether the procedures executed have effectively prepared the system for use. 

Acquiring the needed information to assess system calibration and documenting the procedures 

for doing so, beyond its benefits for training, could resolve a chronically controversial issue with 

regard to system preparation procedures. Some parties have advocated checking sensor response 

by burying the test piece that comes with the system. Others have argued for performing these 

checks with the test piece on the ground surface. Procedures for objectively describing the state 

of the system, following along with delineation of states that produce acceptable sensor 

responses and those that compromise sensor performance, could provide measures that resolve 

the controversy experimentally. 

Trainers have been observed to give operators contradictory information about appropriate 

sensor head velocities for GPR short sweep, as related earlier. This situation arises because no 

explicit specification of the velocity ranges required for optimal and valid GPR sensor response 

is available to trainers. These operating thresholds for GPR short sweep should be established 

and validated empirically (if they have not been already) and disseminated to trainers. We note 

that an experimental investigation of this issue should involve a factorial design that includes 

manipulation of the variables of sensor head roll and head height because our observations 

suggest that increases in these dimensions are correlated with increasing velocities. Training 

personnel describe this phenomenon as “cupping,” which some sources speculate produces 

artifactual GPR responses, which in turn, lead to false alarms. 

A final issue related to operation of AN/PSS-14 GPR is the changing response observed during 

lengthy investigations of high metal targets. An accelerating frequency of GPR response occurs 

over an area growing in size around a target’s location. Trainers report observing this 

phenomenon in previous training sessions. One of the authors has experienced it while operating 

the system in training at Camp Lejeune. Indeed, training personnel described “unofficial” 
40 

techniques for mitigating the difficulties it created for accurate declaration placements. These 

latter observations suggest a generality that extends beyond the context of this study. 

The features of this phenomenon are similar to those that are observed when GPR sensitivity is 

increased manually. Regardless of the underlying mechanisms, if this phenomenon can be 

shown to occur with any regularity, trainers and trainees should be clearly informed of the 

features by which it can be recognized, its consequences, procedures for preventing it, and 

appropriate responses to its appearance. Otherwise, confusion and loss of confidence in the 

equipment are the likely responses of new operators. 

A final issue with regard to training content is whether instruction for discriminating mines from 

clutter should be included in the POI. This is a controversial policy issue whose resolution is a 

matter for USAES leadership. How it is settled has important implications for the content and 

duration of AN/PSS-14 operator training. 

Training operators to distinguish clutter from mines is feasible. Experienced operators have 

demonstrated in test settings that a low false alarm rate can be achieved while extraordinarily 

high detection rates are maintained. In addition, an enormous body of scientific knowledge has 

established effective procedures for training discrimination skills. In many instances, it has been 

applied in military training, notably in training personnel to make friend/foe decisions. Moreover, 

Biederman and Schiffrar (1987) have demonstrated that techniques used to analyze expertise in 

discriminating between complex perceptual categories produce knowledge shown as highly effective for training novices. This same approach has been applied to designing the currently used 

AN/PSS-12 and AN/PSS-14 training programs and will be applied to a proposed study of the best 

AN/PSS-14 operator. 

Although we believe that Soldiers can be trained to develop clutter discrimination skills without 

sacrificing high detection rates (and safety), the costs of doing so are unknown. If the recommendations proposed here are implemented, however, especially those that can increase training 

efficiency, these costs can be reduced. 

6.4 Certification Standards 

Several changes should be implemented to achieve the effects intended by instituting an operator 

certification policy. 

First, procedures for measuring target-declaration distances must be specified, monitored for 

quality assurance, and enforced with standards as stringent as the accuracy standards demanded 

of trainee declarations. Greater use of tape measures, careful placement of scoring grids, 

accurate recording of distances, and professionalism in the application of all costs will minimize 

measurement error. 

Second, regarding scoring standards, we urge adoption of principled distance criteria for 

computing PD that would resolve the discrepancy between two apparently arbitrary standards 
41 

applied by USAES and discussed earlier. One reasonable basis for developing the needed 

standard involves the distances between declaration and mines of various sizes that maximize the 

safety, effectiveness, and efficiency of probing. Allowing that “to err is human,” an extra 

“cushion” for unavoidable errors in taking measurements should be incorporated in setting the 

standard. 

Third, related to the testing environment, testing should take place on lanes equated for 

difficulty. Although imposing the same design standard, especially with regard to the density 

and placement of clutter, to all training is not necessary, such uniformity should be required of 

lanes used for certification testing. 

Fourth, operators can adopt strategies to “game” testing and achieve certification by exploiting 

the absence of any time limit or false alarms. We recommend setting and applying reasonable 

standards for these performance dimensions to ensure that certification procedures validly 

distinguish between trainees who have the capability to safely and efficiently accomplish 

counter-mine missions and those who lack such capability. 

Introducing reasonable time limits in training as well as for testing holds two other potential 

benefits. First, limiting lane time will facilitate more accurate scheduling and lane use by 

reducing the unproductive waiting time that occurs when a trainee takes extraordinary amounts 

of time to complete a lane. Second, lane traversal times exceeding 1.5 to 1.75 hours appear to 

produce levels of mental and physical fatigue that result in trainees’ practicing sloppy techniques, leading to skepticism about the quantity and quality of learning that occurs beyond these 

durations. We propose that more productive practice time would result for such operators if such 

excessively long trials are truncated and the operator resumes practice on another lane after a 

mentally and physically refreshing break. 

6.5 Equipment 

Effective demonstrations of AN/PSS-14 operations require that trainees see the detector’s 

movements relative to targets and hear its output. The latter often proved to be a problem when 

a full complement of trainees (12) gathered around the trainer giving the demonstration, and 

especially when noise from other sources (e.g., wind, machinery, traffic, aircraft) was present. 

The use of attaching equipment (e.g., amplifier, speaker) capable of clearly broadcasting the 

detector’s auditory output over a wider area and other interfering sources would remedy the 

problem and enhance the instruction. 

Quality assurance issues are chronically reported for the low metallic training mines. Effective 

and efficient training requires targets that function reliably. If the vendor for these training aids 

cannot or will not remedy the problems experienced with these very expensive targets, we 

recommend searching for a supplier who will provide targets of the quality needed. 
42 

The SMS was underused, being used only for 4 minutes per operator, two runs of 2 minutes 

each. In order to receive full benefit from this device, it should be used several minutes every 

day to provide accurate and objective feedback to support trainees’ learning and to assess the 

development of their sweep skills. Its potential training benefits are considerable, but they can 

only be realized if the system is used. Chronic reliability problems have made trainers (USAES 

as well as Cyterra) justifiably reluctant to invest the time needed for setup, only to find that 

breakdowns prevent its use and diagnosing and fixing the problems divert time that could be 

spent more productively observing trainees. If the vendor for this system cannot or will not fix 

these problems, we recommend that USAES look elsewhere for other equipment that can serve 

the function of the SMS. 

De-milled mines produce responses from the AN/PSS-14, which differ from those produced by 

mine simulants. The availability of samples of de-milled mines for use in training to supplement 

the use of simulants can help familiarize trainees with the subtle differences between mines and 

training simulants and thereby promote transfer of the skills developed in training to the 

detection of live mines in actual counter-mine operations. 

6.6 Training Facilities 

Many features of the new pole barn site at Fort Leonard Wood make it an excellent training 

facility. The following recommendations are made with the goal of making an even more 

effective environment for mine detection training. While some are specific to this site, the 

majority are more generally applicable. 

• Results of several measures suggest that lanes differ considerably in difficulty. For 

implementing a “crawl, walk, run” instructional approach, we advocate lane designs that 

differ systematically in their clutter content. For initial blind search trials, sterile lanes are 

desirable. Trainees who demonstrate proficiency in these lanes should graduate to lanes 

with clutter, half of which is placed adjacent to targets. Still another set of lanes should 

pose a greater challenge with more clutter items and more challenging placements. 

Implementing this recommendation will likely involve construction of additional lanes. 

• To promote transfer of training to natural environments, we recommend selection and use 

of clutter items likely to be found in the operational environment (e.g., brass, cartridge 

chain links, barbed wire) in the orientations in which they are likely to be found (as 

opposed to driving 10 penny nails straight into the ground, as has been done in pole barn 

lanes). In addition, the positions of all emplaced clutter should be recorded on maps; such 

maps facilitate evaluation of trainees’ skills and especially identification and diagnosis of 

problems that they experience in detecting mines and clutter. 

• Sterile lanes need to be sterile. This means ensuring that lanes designated as sterile should 

be thoroughly cleared when constructed and maintained in this state by regular monitoring. 
43 

• Several lanes need improved drainage. For example, sterile lanes C, D, E flood after 

heavy rains, making them unusable for training. In several other lanes standing water 

collects, precipitating repeated built-in test (BIT) failures in the older model AN/PSS-14s 

used for training. Subsequent use of the system after BIT failure requires the timeconsuming processes of start-up and sensor calibration. Repeated BIT failures multiply 

these costs and frustrate operators. 

• High densities of natural clutter at the staring points of several lanes required trainees to 

expend time searching for a clutter-free area to ground balance the MD subsystem. 

Clearing the area in front of each lane would eliminate this unproductive time spent in 

doing so and thus increase the time available for productive training. 

6.7 Program of Instruction, Efficiency, Costs, and Skill Retention 

The recommendations from this research have been incorporated into a new POI. Priority in its 

design has been given to achieving a level of training effectiveness consistent with USAES 

standards of excellence. The recommended changes in training incorporated in the proposed 

program borrow time saved by the elimination of discovered inefficiencies observed, allocating 

the savings to increased practice time for trainees. 

With regard to training efficiency and costs, the redesign still assumes a 40-hour training period 

for training as many as 12 operators. If and when empirical evaluation demonstrates that the POI 

achieves the training standards of USAES, efforts to maximize its efficiency and minimize its 

cost should be pursued. The recommendations also entail added costs; adding lanes entails 

acquiring more targets. Increasing the number of appropriate qualified trainers imposes a nontrivial personnel cost. 

Are such costs justifiable? The true effects of NET training on mission capability for operators 

of the AN/PSS-14 (and its cost effectiveness) need to be assessed and studied in a context that 

extends beyond the terminal performance of trainees completing training successfully and the 

costs involved in producing it. The skill retention functions shown in figure 17 suggest that 

initial investments that produce the highest levels of skill may reduce requirements for refresher 

training and may be offset in the long run by lower resource expenditure requirements to 

maintain operator and mission capability. 
44 

0 10 20 30 40 50 60

0.0

0.2

0.4

0.6

0.8

1.0

Beyond Calculus

Calculus

Strong School Algebra

Weak School Algebra

Years Since Last Algebra

Percent Correct

Figure 17. Skill retention functions. 

6.8 Future Research 

Understanding GPR response to kinematic variations in the movement of the search head in the 

context of GPR short sweep will benefit training. We recommend that the appropriate experimental studies be undertaken. A clear and specific understanding of the movement parameters 

that optimize the reliability and validity of GPR output will provide trainees with clear goals for 

training. It will also provide trainees and trainers with information needed to assess the quality 

of trainees’ GPR short sweep and fix any deficiencies. 

Research should be undertaken to establish criteria for determining when the MD and GPR 

subsystems have been properly calibrated by operators and when they have not. Results should 

strengthen efforts to establish procedures for doing so in the context of training. Once the 

procedures have been validated, they should be disseminated immediately to trainers and 

certified operators. 

The changes in the training recommended here and incorporated in the POI need to be tested to 

ensure that they deliver the expected gains. We emphasize that rigorous evaluation would need 

to involve evaluation of trainer implementation of the POI; training content cannot achieve its 

goals if it is not delivered effectively. 

We recommend establishment of criteria for scoring mine declaration, which are principled and 

based on consideration of how different criteria interact with subsequent doctrinal procedures for 

mine clearance. A level of accuracy, that is, the distance(s) between mine targets and operators’ 
45 

declaration, that best accomplishes mission requirements should be the basis. Studies of probing 

effectiveness and efficiency should provide critical information. 

We have recommended that changes in operator certification criteria be considered. Cost/benefit 

analyses of any such changes ordered and implemented should be undertaken to ensure that the 

expected benefits accrue and that they are justified by the investments required. 

Following any changes made in USAES AN/PSS-14 training, skill retention studies should be 

performed. The true effects of NET training on mission capability for operators of the AN/PSS14 and its cost effectiveness need to be assessed and studied in a context that extends beyond the 

terminal performance of trainees completing training successfully and the costs involved in 

producing it. Initial investments that produce the highest levels of skill may reduce requirements 

for refresher training and may be offset in the long run by lower resource expenditure 

requirements to maintain operator and mission capability. 

7. Conclusion 

The objective of this effort was to examine what was assumed to be an effective training program 

for ways to increase its efficiency. In the pursuit of this goal, deficiencies in AN/PSS-14 training 

were discovered, which we argue undermine its effectiveness, raise doubt about the validity of 

operator certification, and could have contributed to training and mission capability issues 

identified by two in-country evaluations of AN/PSS-14 operator capability. 

In addition to the identification of training problems, principled recommendations for changes in 

the AN/PSS-14 POI that represent potential solutions are offered for the consideration of USAES 

leadership and other stakeholders. These recommendations describe tactics for enhancing 

effectiveness and they do so by exploiting time gained by minimizing the inefficiencies discovered 

in the current training program implementation. Priority has been given to achieving a level of 

training effectiveness consistent with USAES standards in making recommendations; effort to 

maximize efficiency and minimize costs can and should be pursued after this standard is achieved. 

The AN/PSS-14 represents an important technological advance that holds potential to substantially 

improve the counter-mine capability of U.S. ground forces. Multiple studies have underscored the 

critical roles played by operator skill and operator training in achieving this potential. The findings 

and recommendations reported here offer a path for advancing toward that goal that is cognizant of 

needs and the resource limitations under which USAES works in meeting these needs. 
46 

8. References 

Public Affairs Office, 82nd Airborne Division. Media Release 03-018, Fort Bragg, NC, 2003. 

Ashely, S. Searching for Land Mines. Mechanical Engineering April 1996, 62–67. 

Agresti, A.; Coull, B. Approximate is Better than “Exact” for Interval Estimation of Binomial 

Proportions. The American Statistician 1998, 52, 119–126. 

Anderson, J. R.; Schunn, C. D. Implications of ACT-R Learning Theory: No Magic Bullets. In 

R. Glaser (Ed.), Advances in Instructional Psychology 2000, 5. Mahwah, NJ: Erlbaum 

Associates, 2000. 

Bahrick, H. P.; Hall, L. K. Lifetime Maintenance of High School Mathematics Content. Journal 

of Experimental Psychology: General 1991, 120, 20–33. 

Biederman, I.; Schiffrar, M. M. Sexing Day-Old Chicks: A Case Study and Expert Systems 

Analysis of a Difficult Perceptual-Learning Task. Journal of Experimental Psychology 

Learning, Memory, and Cognition 1987, 13, 640–645. 

Department of the Army. Detecting Set, Mine AN/PSS-14; Technical Manual 5-6665-373-10; 

Washington, DC, 2003. 

Farr, M. J. The Long-Term Retention of Knowledge and Skills: A Cognitive and Instructional 

Perspective. Springer-Verlag: New York, NY, 1987. 

Glumm, M. M.; Reinhart J. E.; Sexton, P. L.; Waugh J. D. User Training on the Hand-Held 

Mine Detection System (HSTAMIDS); unpublished manuscript; U.S. Army Research 

Laboratory: Aberdeen Proving Ground, MD, no date. 

Hambric, H. H.; Schneck, W. C. The Antipersonnel Mine Threat. Proceedings of the 

Technology and the Mine Problem Symposium, November 1996, 1, 18-21, 3-11−3-45, Naval 

Postgraduate School. 

Healy, A. F.; Bourne, L. E. Learning and Memory of Knowledge and Skills: Durability and 

Specificity. Sage Publications: Thousand Oaks, CA, 1995. 

Herman, H.; McMahill, J.; Kantor, G. Training and Performance Assessment of Landmine 

Detector Operator Using Motion Tracking And Virtual Mine Lane. In A. C. Dubey & J. F. 

Harvey & J. T. Broach & R. E. Dugan (Eds.), Detection and Remediation Technologies for 

Mines and Minelike Targets V, Proceedings of the Society for Photo-Optical 

Instrumentation Engineers’ 13th Annual Meeting 2000, 4038, 110-121. Orlando: SPIE. 
47 

Hoaglin, D.C.; Mosteller, F.; Tukey, J. W. Understanding Robust and Exploratory Data 

Analysis. Wiley & Sons: New York, 1983. 

Kern, P. Clearing the Roads in Iraq and Afghanistan. In Applications of Technology to 

Demining, Part 1, Vol. 1: Landmine countermeasures, A. M. Bottoms and C. Scandrett 

(Eds.) The Society for Counter-Ordnance Technology: Monterey, CA, 2005. 

LaMoe, J. P.; Read, T. Countermine Operations in the Contemporary Operational Environment. 

Engineeer April 2002, 21-23. 

Maurer, L. AN/PSS-14 Mine Detector Assessment for Operation Enduring Freedom. NVESD 

Trip report, U.S. Army Research, Development, and Engineering Command, 2003. 

Mincey, J.C. personal communication, U.S. Army Engineer School, Counter Explosive Hazards 

Center, Fort Leonard Wood, MO, October 2005. 

Newell, A.; Rosenbloom, P. S. Mechanisms of Skill Acquisition and the Power Law of Practice. 

In J. R. Anderson (Ed.), Cognitive Skills and Their Acquisition (pp. 1-55). Erlbaum: 

Hillsdale, NJ, 1981. 

Rose, A. M.; Czarnolewski, M. Y.; Gragg, F. E.; Austin, S. H.; Ford, P.; Doyle, J.; Hagman, J. D. 

Acquisition and Retention of Soldiering Skills; Technical Report 671; U. S. Army Research 

Institute for Behavioral and Social Science: Arlington, VA, 1985. 

Santiago, A.; Locke, M.; Reidy, D. Operational Test Results for the AN/PSS-14 (HSTAMIDS). 

Proceedings of the UXO/Countermine Forum, 9-12 March 2004, St. Louis, MO. 

Schneck, W. C.; Green, B. M. Techniques and Procedures for Route Clearance. Engineer 1997, 

26, 3–10. 

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U. S. Army Research Institute for Behavioral and Social Science Research, Arlington, VA, 

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Staszewski, J.; Davison, A. Supporting the Army Transformation through Cognitive 

Engineering: Evidence From Improved Landmine Detection Capability. Army Science 

Conference, Orlando, Fl, 2-6 December 2002. 

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Report to the Honorable Lane Evans, House of Representatives; GAO-02-1003. Washington, 

DC, 2002. 
48 

INTENTIONALLY LEFT BLANK
49 

Appendix A. Data Collection Forms 

Volunteer Agreement Affidavit 
50 
51 

Training Experience Survey 
52 

AN/PSS-14 Ergonomics Questionnaire 
53 

Time Log Worksheet 
54 

Sweep Drill Worksheet 
55 

Iteration Cover Sheet 
56 

Observation Data Entry 
57 

Mine Lane Map 
58 

INTENTIONALLY LEFT BLANK
59 

Appendix B. Probability of Detection Table B-1. Descriptive statistics: probability of detection by target type. Table B-2. Descriptive statistics: probability of detection by lane. 

Table B-3. Descriptive statistics: probability of detection by participants’ test result. 
60 

Figure B-1. Mean probability of detection versus lane for all trials. 

Figure B-2. Mean probability of detection versus adjusted trial number by 

participants’ test result. 
61 

Appendix C. Confidence Rating Table C-1. Descriptive statistics: confidence rating by target type. Table C-2. Descriptive statistics: confidence rating by lane. 

Table C-3. Descriptive statistics: confidence rating by participants’ test result. 
62 

Figure C-1. Mean confidence rating versus lane for all trials. 

Figure C-2. Mean confidence rating versus adjusted trial number by participants’ 

test result. 
63 

Appendix D. Investigation Time 

Table D-1. Descriptive statistics: total investigation time (seconds) by target type. 

Table D-2. Descriptive statistics: MD time per investigation (seconds) by target type. 

Table D-3. Descriptive statistics: GPR time per investigation (seconds) by target type. 
64 

Figure D-1. Median total investigation time versus adjusted trial number by mine type. 

Figure D-2. Median MD time per investigation versus adjusted trial number by mine type. 
65 

Figure D-3. Median GPR time per investigation versus adjusted trial number 

by mine type. 

Table D-4. Power curve (y = Cxb

) model summary: investigation time (y) versus 

adjusted trial number (x). 

Model Summary Parameter Estimates Target Type R2

 F df1 df2 Sig. C b 

APLM 0.122 44.088 1 316 0.000 149.887 -0.394 

APM 0.181 17.052 1 77 0.000 230.628 -0.489 

ATLM 0.151 60.751 1 342 0.000 178.576 -0.467 

ATM 0.115 11.917 1 92 0.001 248.733 -0.393 

Clutter 0.044 59.928 1 1,290 0.000 142.806 -0.333 

Table D-5. Power curve (y = Cxb) model summary: MD time per investigation (y) 

versus adjusted trial number (x). 

Model Summary Parameter Estimates Target Type R2

 F df1 df2 Sig. C b 

APLM 0.116 41.472 1 316 0.000 101.523 -0.517 

APM 0.165 15.262 1 77 0.000 153.729 -0.563 

ATLM 0.129 50.532 1 342 0.000 116.750 -0.524 

ATM 0.098 9.997 1 92 0.002 170.595 -0.458 

Clutter 0.034 45.976 1 1,290 0.000 83.189 -0.377 
66 

Table D-6. Power curve (y = Cxb) model summary: GPR time per investigation (y) 

versus adjusted trial number (x). 

Model Summary Parameter Estimates Target Type R2

 F df1 df2 Sig. C b 

APLM 0.012 3.695 1 316 0.055 26.804 -0.173 

APM 0.057 4.619 1 77 0.035 39.587 -0.345 

ATLM 0.033 11.739 1 342 0.001 32.771 -0.319 

ATM 0.028 2.649 1 92 0.107 35.218 -0.240 

Clutter 0.011 14.642 1 1,290 0.000 34.450 -0.221 

Figure D-4. Total investigation time versus adjusted trial number for APLM type mines. 
67 

Figure D-5. Total investigation time versus adjusted trial number for APM type mines. 

Figure D-6. Total investigation time versus adjusted trial number for ATLM type mines. 
68 

Figure D-7. Total investigation time versus adjusted trial number for ATM type mines. 

Figure D-8. Total Investigation Time versus Adjusted Trial Number for Clutter Targets. 
69 

Figure D-9. MD Time per Investigation versus Adjusted Trial Number for APLM 

Type Mines. 

Figure D-10. MD Time per Investigation versus Adjusted Trial Number for APM 

Type Mines. 
70 

Figure D-11. MD Time per Investigation versus Adjusted Trial Number for ATLM 

Type Mines. 

Figure D-12. MD Time per Investigation versus Adjusted Trial Number for ATM 

Type Mines. 
71 

Figure D-13. MD Time per Investigation versus Adjusted Trial Number for 

Clutter Targets. 

Figure D-14. GPR Time per Investigation versus Adjusted Trial Number for APLM 

Type Mines. 
72 

Figure D-15. GPR Time per Investigation versus Adjusted Trial Number for APM 

Type Mines. 

Figure D-16. GPR Time per Investigation versus Adjusted Trial Number for ATLM 

Type Mines. 
73 

Figure D-17. GPR Time per Investigation versus Adjusted Trial Number for ATM 

Type Mines. 

Figure D-18. GPR Time per Investigation versus Adjusted Trial Number for 

Clutter Targets. 
74 

INTENTIONALLY LEFT BLANK
75 

Appendix E. Rate of Advance Table E-1. Descriptive statistics: rate of advance by lane. 

Table E-2. Descriptive statistics: rate of advance by participants’ test outcome. 
76 

Figure E-1. Median Rate of Advance versus Lane for all Trials. 

Figure E-2. Median Rate of Advance versus Adjusted Trial Number by Participants’ 

Test Outcome. 
77 

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 ATTN AMSRD ARL HR MU M SINGAPORE 

 6501 E 11 MILE RD MAIL STOP 284 

 BLDG 200A 2ND FL RM 2104 

 WARREN MI 48397-5000 

 1 ARMY RSCH LABORATORY - HRED 

 ATTN AMSRD ARL HR MF MR C HERNANDEZ 

 BLDG 3040 RM 220 

 FORT SILL OK 73503-5600 

 1 ARMY RSCH LABORATORY - HRED 

 ATTN AMSRD ARL HR MW E REDDEN 

 BLDG 4 ROOM 332 

 FT BENNING GA 31905-5400 

NO. OF 

COPIES ORGANIZATION

 1 ARMY RSCH LABORATORY - HRED 

 ATTN AMSRD ARL HR MN R SPENCER 

 DCSFDI HF 

 HQ USASOC BLDG E2929 

 FORT BRAGG NC 28310-5000 

 1 NIGHT VISION DIRECTORATE 

 DEPARTMENT OF ARMY 

 ATTN AMSRD CR NV CM DSA 

 A L SANTIAGO 

 10221 BURBECK ROAD 

 FORT BELVOIR VA 22060-5806 

 1 SYSTEMS INTEGRATION DIVISION 

 US ARMY ENGINEER SCHOOL

 ATTN ATSE DE J BEACHAM 

 320 MANSCEN LOOP SUITE 235 

 FORT LEONARD WOOD MO 65473 

 ABERDEEN PROVING GROUND

 1 DIRECTOR 

 US ARMY RSCH LABORATORY 

 ATTN AMSRD ARL CI OK TECH LIB 

 BLDG 4600 

 1 DIRECTOR 

 US ARMY RSCH LABORATORY 

 ATTN AMSRD ARL CI OK TP S FOPPIANO 

 BLDG 459 

 1 DIRECTOR 

 US ARMY RSCH LABORATORY 

 ATTN AMSRD ARL HR MR F PARAGALLO 

 BLDG 459