1. Potomac Management Group, Inc.1 Objective POD Estimation The Development of a Standard Method For Gathering and Using Detection Data R. Quincy Robe & Jack Frost

2. Potomac Management Group, Inc.2 Presentation Outline Define and Describe a “detectability index” Show how it is used with other data to estimate POD Describe a Procedure for doing detection experiments to determine a “detectability index”

3. Potomac Management Group, Inc.3 The Detection Process A series of “glimpses” as the searcher moves through the environment containing the object. Detection with any one “glimpse” depends on the Search Object (size, color, contrast, etc.) Environment (weather, terrain, vegetation, etc.) Search Resource (sensor and platform) Distance from the Resource to the Object

4. Potomac Management Group, Inc.4 What is Probability of Detection (POD)? Applies to some amount of area (e.g., a segment) Probability of detecting an object if present POD is a function of: Effort (Resources, Search Speed, Time) Size of the Area covered Search object “detectability”

5. Potomac Management Group, Inc.5 What is Effort? Total Distance traveled by searchers while searching in the segment Effort = searcher speed x time x number of searchers What is Area covered? Size of the area over which the searching effort is approximately uniformly spread

6. Potomac Management Group, Inc.6 What is Detectability? How can one measure or quantify how easy or hard it will be to detect a particular object with a particular type of resource (sensor) in a particular environment?

7. Potomac Management Group, Inc.7 What about Maximum Detection Range? Easy to measure directly. Measures how far from the sensor an object can be detected by an alerted searcher who knows where to look. Does not address whether the object will be detected within that range. Does not measure how much detecting can be expected from a searcher (sensor). No simple, predictable correlation with detection performance.

8. Potomac Management Group, Inc.8 What about direct estimation? Humans are very poor at estimating probabilities of any kind. Compare: How many of 10 objects would you have found? How many of 10 objects could you have missed? No such thing as “one size fits all” POD for everything from small clues to large objects. Direct estimation = Wild Guess

9. Potomac Management Group, Inc.9 Effective Sweep Width (Koopman) Cannot be measured directly Is an objective measure of detectibility Large value => easy to detect Small value => hard to detect Depends on the characteristics of Searcher/Sensor (What we are searching with.) Search Object (What we are searching for.) Environment (What we are searching in.) Terrain, Vegetation, Weather, etc. Has units of length (feet, meters, miles, etc.)

10. Potomac Management Group, Inc.10 A Uniform Random Distribution

11. Potomac Management Group, Inc.11 Effective Sweep Width Number detected = 40. Number missed within sweep width = 0. Number detected outside sweep width = 0. Effective Sweep Width (Unrealistic Ideal Sensor Making a Clean Sweep)

12. Potomac Management Group, Inc.12 Effective Sweep Width Number detected = 40. Number missed within sweep width = 16. Number detected outside sweep width = 16. Effective Sweep Width Max Detection Range (More Typical Sensor)

13. Potomac Management Group, Inc.13 Effective Sweep Width Notes In both of the previous examples, there were The same object density (# of objects/unit of area), The same length of searcher track, and The same number of objects detected (40). Therefore, The effective sweep widths are also the same. Effective sweep width represents the expected amount of detection.

14. Potomac Management Group, Inc.14 Lateral Range (Koopman) Distance to right or left of sensor at the closest point of approach (CPA) Lateral range curve

15. Potomac Management Group, Inc.15 Effective Sweep Width Key to Improved Search Planning and Evaluation Improves POD Estimation Allows us to Objectively Relate POD to Effort Expenditure Has both Predictive and Retrospective Value More Accurate and Reliable than Subjective Estimates Based on Observable Factors Improves Effort Allocation Makes known, proven (mathematical) techniques available Improves conceptualization of the search problem

16. Southern California

18. Western Washington State

20. Potomac Management Group, Inc.20 Objective POD Estimation For a searched segment Effort = z = Total Distance Searchers Cover = search speed  time  number of searchers Effective Sweep Width = W from detection experiments Area Effectively Swept = z  W Coverage = C = POD = 1 – e -C (Koopman) Area Effectively Swept Area of Searched Segment

21. Potomac Management Group, Inc.21 POD vs. Coverage Graph (Koopman) POD versus Coverage

22. Potomac Management Group, Inc.22 “Uncorrected” Effective Sweep Widths In Nautical Miles For Aerial Search Over Land ( IAMSAR Manual ) Meteorological Visibility ( Nautical Miles) Search Object Altitude (Feet AGL) 35101520 Person5000.4 0.5 10000.4 0.5 Vehicle5000.91.3 10001.01.4 1.5 Small Aircraft5001.01.4 10001.01.5 1.6 Large Aircraft5001.22.02.2 10001.82.73.0

23. Potomac Management Group, Inc.23 Effective Sweep Width Correction Factors For Aerial Search Over Land ( IAMSAR Manual ) (Multipliers) Search Object 15-60% vegetation or hilly 60-85 % vegetation or mountainous Over 85% vegetation Person0.50.30.1 Vehicle0.70.40.1 Small Aircraft0.70.40.1 Large Aircraft0.80.40.1

24. Potomac Management Group, Inc.24 Sweep Width Issues for Ground Search Too many different types and combinations of terrain, vegetation, search objects for a “universal” set of sweep width tables. Each locale needs sweep widths only for its area of responsibility, typical search objects, etc. Solution: Develop a standard, practical, and scientifically based procedure for local resources to use when developing sweep width estimates.

25. Potomac Management Group, Inc.25 The Logan, West Virginia Demonstration Project

26. Potomac Management Group, Inc.26 Project Support Sponsored by the U. S. National Search and Rescue Committee (NSARC) Funded by Department of Defense (NSARC member) Contract administered by U. S. Coast Guard (NSARC Chair) via the USCG Research and Development Center; performed by Potomac Management Group Endorsed by NASAR and U. S. Air Force RCC Hosted by Logan Emergency Ambulance Service Authority

27. Potomac Management Group, Inc.27 Demonstration Project Principal Investigator: R. Quincy Robe Location: Chief Logan State Park, Logan, WV Host: Roger Bryant, Director, Logan Emergency Ambulance Service Authority (LEASA) Participants: Attendees at Logan SAR Weekend on 15-16 June 2002 Outstanding support and hospitality!

28. Potomac Management Group, Inc.28 Demonstration Project Objectives Design Practical Detection Experiment Procedures to determine Effective Sweep Width values for ground wilderness/rural searches. Supervise a Demonstration of the Procedures Using Ground SAR Personnel. Describe Method for Objectively Estimating POD from Effective Sweep Width, Effort, and Area. Report Results and Describe Future Work required to generalize their application.

29. Potomac Management Group, Inc.29 Concept of Operations (Preparation) Select a typical area and typical search object types (no more than 3 types) Select track(s) for searchers to follow (for at least 1 hour—longer is better) Choose date, select participants, make logistic arrangements, set up schedule Obtain/construct search objects (≥ 10 of each)

30. Potomac Management Group, Inc.30 Concept of Operations (Execution) Place objects at random locations along the track and random distances on either side Send searcher/data recorder pairs along the track at timed intervals (to ensure separation) Searchers move at normal search speed and report all sightings of search objects Data recorders record searcher sighting reports and other pertinent data Collect and analyze the recorded data

31. Potomac Management Group, Inc.31 Chief Logan State Park Experiment Area

32. Potomac Management Group, Inc.32 Select Search Track End I End II a 240 m 220 m c 180 m 220 m e 230 m f 280 m g 340 m h 290 m 80 m b d Waypoints a to h were marked with flags. Approximate distances between waypoints are in meters.

33. Potomac Management Group, Inc.33 Search Objects Orange Glove Garbage Bag

34. Potomac Management Group, Inc.34 Determining Object Locations Useful range of distances off track Too close => Insufficient data for longer ranges Too far => Wasted detection opportunities Useful range of distances along track Too close => Frequent reinforcement => alertness Too far => Track too long for reasonable time Use Average Maximum Detection Range

35. Potomac Management Group, Inc.35 Average Maximum Detection Range

36. Potomac Management Group, Inc.36 Select Object Placement Randomize Distances along the track Distances off track Right or Left of track Object types Determine locations based on largest AMDR Average separation along track of 3  AMDR Off track up to 1.5  AMDR

37. Potomac Management Group, Inc.37 Example of Object Locations (AMDR = 100 m) Search Object Locations Track Interval Along Track Location Cross Track Location Search Object Type Location #1100 to 300241 m122 m rightB Location #2400 to 600442 m47 m leftA Location #3700 to 900886 m69 m rightA Location #41000 to 12001033 m22 m leftB Location #51300 to 15001420 m45 m leftA More locationsTo end of trackNext location Next search object type

38. Potomac Management Group, Inc.38 Search Object Location Zones 2 x AMDR 3 x AMDR 1.5 x AMDR Lateral Range

39. Potomac Management Group, Inc.39 What is a Detection Opportunity? For the purposes of a detection experiment, a detection opportunity is defined as one complete pass by the search object. If there are 15 identical search objects of a given type and 30 searchers in an experiment, then there are a total of 15 x 30 = 450 detection opportunities for that type. Each detection opportunity has one of two results: Detection or Non-detection.

40. Potomac Management Group, Inc.40 Important Notes When performing a detection experiment, it is important to understand that: The relationship between the searcher (sensor) and the search object during the window of detection opportunity must be captured, and Knowing when non-detection occurs is just as important as knowing when detection occurs.

41. Potomac Management Group, Inc.41 Important Notes The experiment is NOT a competitive event The experiment does NOT measure individual searcher proficiency Do NOT tell searchers how many objects are present, how far off track, or give any other hints DO Collect additional data (e.g., weather, time of day, terrain and vegetation descriptions, searcher training/experience data, etc.) for later analysis

42. Potomac Management Group, Inc.42 Perform Experiment Secretly Place Objects at Selected Locations Send Searcher/Data Recorder Pairs along the Selected Track at Timed Intervals Collect Completed Detection Data Forms Remove Objects at Experiment’s Conclusion (Discard data for objects not found.) Compile, Sort and Analyze the Detection Data

43. Potomac Management Group, Inc.43 Detection Log

44. Potomac Management Group, Inc.44 Calculate Sweep Width Use the following property of sweep width: The number of detections outside a swath one sweep width wide centered on the searcher’s track equals the number of missed detections inside that swath. Equivalently, the number of detections at lateral ranges greater than one-half the sweep width value are equal to the number of missed detections at lateral ranges less than one-half the sweep width value.

45. Potomac Management Group, Inc.45 Logan Demonstration Statistics 32 Searchers Participated 12 Orange Gloves were placed Glove AMDR = 19 meters 32 x 12 = 384 Detection Opportunities 9 Black Garbage Bags were placed Bag AMDR = 25 meters (1.5 x 25 = 37.5 meters) 32 x 9 = 288 Detection Opportunities

46. Potomac Management Group, Inc.46 Consolidated Detection Data

47. Potomac Management Group, Inc.47 Orange Glove Sweep Width Orange Glove Detection Data— W = 36 meters. (Crossing point equals one-half effective sweep width value.) (AMDR = 25 m) (12 Gloves, 32 Searchers)

48. Potomac Management Group, Inc.48 Orange Glove Half Lateral Range Curve Orange Glove Half Lateral Range Curve— W = 40 meters (Areas under this portion equal one-half effective sweep width value.)

49. Potomac Management Group, Inc.49 Orange Glove Modified Sweep Width Modified Orange Glove Detection Data— W = 33 meters. (Crossing point equals one-half effective sweep width value.)

50. Potomac Management Group, Inc.50 Orange Glove Modified Half LRC Modified Orange Glove Half Lateral Range Curve— W = 33 meters. (Areas under this portion equal one-half effective sweep width value.)

51. Potomac Management Group, Inc.51 Black Bag Sweep Width Black Garbage Bag Detection Data— W = 58 meters. (Crossing point is equal to half sweep width value.) (AMDR = 25 m) (9 Bags, 32 Searchers)

52. Potomac Management Group, Inc.52 Black Bag Lateral Range Curve Black Garbage Bag Half Lateral Range Curve— W = 53 meters. (Area under this portion equals one-half effective sweep width value.)

53. Potomac Management Group, Inc.53 Lessons Learned AMDR did not work well Poor choice of location? Poor technique by investigators? Should have been repeated several times in different locations May need to use maximum, rather than average maximum detection range Need steady flow of searcher/data recorder pairs

54. Potomac Management Group, Inc.54 Future Work Validate and refine detection experiment procedures in 3 different venues with different SAR groups and personnel during the next year. Publish the refined procedures and make them available upon request. Extend techniques to include aerial search over land (CAP, CASARA, etc). Develop more advanced search planning methods appropriate for the land SAR community.

55. Potomac Management Group, Inc.55 Future Work (continued) Develop functional requirements for software tools to support land SAR search planning. Survey existing software packages for synergistic opportunities. Develop software (modules) to support land SAR search planning functions.

56. Potomac Management Group, Inc.56 Conclusions A practical detection experiment procedure is feasible. Effective sweep width results make scientifically proven search planning methods available for use in land SAR. Objective, accurate, reliable POD estimation is possible More nearly optimal resource allocation can be done Increase probability of success (POS) at maximum rate. Minimize mean time to find survivors. Save more lives. Minimize risks to searchers through reduced exposure times. Minimize costs through shorter searches on average.

57. Potomac Management Group, Inc.57 Conclusions (continued) Effort needed is comparable to a SAREX. No special skills, tools or equipment required (although some items would be helpful). Data should be archived at a central site. Additional data gathered will support later analyses for important secondary effects For example, correction factors to extend usability of effective sweep width data to situations other than those of the experiments.

58. Potomac Management Group, Inc.58 Potomac Management Group, Inc. 510 King Street, Suite 200 Alexandria, VA 22314 Attn: J. R. Frost 703-836-1037 or 202-267-6702 (USCG) E-mail: jfrost@potomacmgmt.com orjfrost@potomacmgmt.com jfrost@comdt.uscg.mil THANK YOU!