1. Research Potential in Data from Instrumented Training CPT John J. Horton DISE Operations Officer 7 th Army Expeditionary Training Center (7ETC) US Army Europe

2. Purpose Provide an overview of Instrumentation Systems (IS) Explore potential analytical applications of the data generated by IS with respect to casualties

3. Agenda Instrumentation Systems Data Collection Research Potential of IS Data Limitations of IS Data Two Sample Applications Recommendations

4. Essential Components of an IS Instrumentation -GPS -Radio transmitter -Recording device -AAR/Playback Instrumentation System (IS) += Tactical Engagement Simulation System Field Instrumentation: an internal or external recording, monitoring and relaying device employed by live instrumented entities. These devices provide an independent source of data to assess the performance of operational systems involved in the exercise – Defense Modeling and Simulation Office Glossary e.g MILES

5. Instrumentation Systems Most are vehicle-based (i.e. MILES II / SAWE) All the CTCs have some form of instrumentation Soldier-worn instrumentation appeared late ’90s (still not widespread) Many systems now under development

6. Instrumentation at the 7 th ETC CMTC (Hohenfels) –Vehicle-based and tied to permanent antennas –Developing a dismounted & expeditionary capability Directorate of Training (Grafenwoehr) –Deployable Instrumentation Systems Europe (DISE) –Bought OTS in 2002 from Saab Training Systems –Approx. 800 personnel / 200 vehicles –Intended for home-station and deployed locations Both systems can link to constructive and virtual domains using DIS / HLA / DBST wrap-around

7. Instrumented Players Dismounted SoldiersArmored Vehicles TargetsWheeled Vehicles IED’s

8. Laser detectors GPS Antenna Battery Pack Computer FM Antenna Key Components: Personal Detection Device (PDD)

9. Key Components: Small Arms Transmitter (SAT) Unique SATs for: -M16/M4 -M249 -M240/M60 -M2 -AK-47 / 74 SAT Laser - Range and “effects” similar to associated weapon Small-Arms Alignment Device (SAAD) -Aligns SAT to Soldier’s real zero

10. CCC Global Positioning Satellite Antenna How it works Computer Control Console (CCC) Time & Position Signal Only PDD Sends: - Location - Status - Weapon events PDD Receives: - Area Weapons (AW) effects data - Other Instructions from CCC CCC: -Records data -Displays players -Sends AW data -Controls targetry Instrumented Player (can also be a vehicle)

11. DISE System Capabilities ~8 KM Range 8 KM Coverage Range can be extended with additional towers One antenna & CCC can handle 300+ Players, Including dismounted infantry tanks, IFVs, HMMWVs etc. 9M & 21M Mast Antennas HMMWV-based Can be erected < 1 hr

12. Representation of an Engagement

13. Data Collection DISE collects: –Locations ~ 1 meter resolution –Weapons-events –Player-to-player weapons pairing –Player health 5 second “heartbeat” Data recorded in XML XML file is input for AAR play- back program

14. Casualties in DISE Players are wounded or killed by: –Direct & Indirect fire –NBC effects –Minefields / IEDs Wound type / severity probabilistically determined (i.e. P(k) set my manufacturer) Speaker in PDD alerts Soldier to status All data (positions, time, weapons etc.) stored in XML-AAR file

15. Live training is the closest approximation to actual combat Quantitative data never-before available is now routinely collected Instrumented training will become the de- facto standard for all Force-on-Force training Data being generated by this training could be used by the Analytic community The Point

16. Research Domains & Data Initial Injury First Treatment CASEVAC Level II / III Quantitative Data -Direction of attack -Engagement dist. -Weapon type -Orientation of wound on body Categorical Data -Casualty MOS -Rank -Duty Position Quantitative Data -CLS locations -Medics locations -Elapsed Time Categorical Data -First responder (i.e. buddy, CLS, medic, PA) Quantitative Data -CCP location -Ambulance loc. -CASEVAC time Categorical Data -Type of CASEVAC used Quantitative Data -Distributions -Utilization of assets Categorical Data - Aggregate data on casualties General Qualitative – Tactical scenario, Force Compositions & Terrain

17. Potential Research Questions Initial Injury Where should BA be thickest? Should there be MOS-specific BA? Are there statistically significant survivability factors (age, duty position, physical fitness etc.)? First Treatment How many medics/CLS ? Where should they be? Do leaders lose SA of casualties? Would an individual tracking system help?

18. Potential Research Questions CASEVAC Optimal location of CASEVAC assets? What are trade-offs of standard vs. non- standard CASEVAC? How effective is our CASEVAC training (MOP)? Level II / III Care How much capacity is needed? What battlefield geometry of assets is optimal? At what echelons of care should scarce resources be stocked?

19. Casualty Data for Analysis Real Pro: Medical data From a real war Categorical data Con: Tactical quantitative Small, fixed sample size Instrumented Pro: Tactical quantitative Hypothesis testing Con: Not from a real war Limited “medical” data Live domain is problematic

20. Analytic Data Issues and Limitations Initial Injury –Wounds stochastically determined –Inherent limitations of a TESS First Treatment –Treatment requires OC assistance (control gun) CASEVAC –Loss of GPS coverage inside vehicles / buildings Level II/III –Not often part of training exercise General –Units respond to casualties differently in “real life” Technological Cultural / Training Priorities Both

21. Sample Application: Direction of Attack and Distance Engagement distance and orientation can be calculated directly Assuming Soldier is oriented in his or her direction of travel, orientation of wound on the body can be calculated

22. Sample Application: Fitting Casualty Data to a Distribution Using data to estimate distribution parameters Map scenario space to distribution parameters Explore relationships and refine models

23. Recommendations Analytic community explores partnerships with CTCs to gain access (or shape collection of) instrumented casualty data Requirements of analytic community expressed in specifications for future Instrumentation Systems Modeling and Simulation community look at ways live data can validate and improve current combat casualty models