1. A new technique to address CID and IFF studies David Dean, Kathryn Hynd, Beejal Mistry, Alasdair Vincent and Paul Syms Dstl IMD and LSD 22 ISMOR, September 2005 Dstl/CP16723

2. © Dstl 2005 Dstl is part of the Ministry of Defence UK UNCLASSIFIED 2 2 September 2005 Contents Introduction and definitions –CID project background –the technical problem Outline of the INCIDER model –decision engines –validation Initial successes? Questions

3. © Dstl 2005 Dstl is part of the Ministry of Defence UK UNCLASSIFIED 3 2 September 2005 Introduction: What is amicide? Definition of amicide (fratricide, friendly fire …): –“An attack by one or more initiators acting as a group on one or more friendly targets that are under friendly control” Includes attacks that result in no casualties or damage –these are excluded in the US definition A ‘near-miss’ is when firers nearly attack friends –but the error is realised before a shot is fired

4. © Dstl 2005 Dstl is part of the Ministry of Defence UK UNCLASSIFIED 4 2 September 2005 Causes of amicides Causes of 1167 20th. century events analysed by Dstl:

5. © Dstl 2005 Dstl is part of the Ministry of Defence UK UNCLASSIFIED 5 2 September 2005 Consequences of amicide Casualties to Blue forces –estimated at 10–20% of all casualties in WW1 and WW2 –greater in proportion if enemy less effective Reduces tempo –including effects of lost opportunities to engage Impact on morale Political implications –nationally and within coalitions –used to undermine confidence in military

6. © Dstl 2005 Dstl is part of the Ministry of Defence UK UNCLASSIFIED 6 2 September 2005 Introduction: What is CID? UK definition of combat identification (CID): –“The process of combining situational awareness, target identification, specific tactics, techniques and procedures to increase operational effectiveness of weapon systems and reduce the incidence of casualties caused by friendly fire” Thus there are 3 methods of improving CID: –situational awareness (SA) –physical target identification (TID) –tactics, techniques and procedures (TTPs)

7. © Dstl 2005 Dstl is part of the Ministry of Defence UK UNCLASSIFIED 7 2 September 2005 The CID OA problem MoD requires advice on CID cost-effective CID solutions –BoI across SA, TID and TTPs –across all environments – sea, land, air … joint and combined –spans the physical, information and cognitive domains Cost-effectiveness implies quantitative modelling –cognitive domain usually addressed using ‘soft OA’ methods No quantitative ‘off-the-shelf’ assessment tools available Dstl understood all domains to a sufficient extent … –and was aware sufficient data existed to support modelling …

8. The INCIDER model

9. © Dstl 2005 Dstl is part of the Ministry of Defence UK UNCLASSIFIED 9 2 September 2005 What is INCIDER? The Integrative Combat Identification Entity Relationship Model Integrates human, physical and operational domains A repository of parameters that will impact upon CID, and the relationships between them –a generic representation of combat entities observing and identifying prior to engagement –can be tailored to represent all potential encounters where CID is a contributory factor

10. © Dstl 2005 Dstl is part of the Ministry of Defence UK UNCLASSIFIED 10 2 September 2005 INCIDER output: P(correct ID) and time to ID INCIDER conceptual overview Operational domain Scenario complexity Context and RoEs Possible target options Physical domain Organic sensor characteristics Target characteristics Environment – e.g. terrain, weather Human domain Pre-set characteristics Variables, e.g. from training Expectation, e.g. from briefings Motivation Physiology – e.g. stress and fatigue

11. © Dstl 2005 Dstl is part of the Ministry of Defence UK UNCLASSIFIED 11 2 September 2005 CID decision-making scope Decision process Projection Battlespace Entity Organic and 3rd. party information “Picture” Compiled view Absolute truth about identity Maximum information available to sensors Maximum information available to observer Aggregated information available to observer Fusion process Decision output categories Recognition Is it a tank? Action Should I kill it, report it, hide from it or ignore it? Identification What sort of tank is it? Detection Is it a military object? Total information available for decision Retrieved information, reports Memory Decision Comprehension Perception

12. © Dstl 2005 Dstl is part of the Ministry of Defence UK UNCLASSIFIED 12 2 September 2005 Pre-conceptions –from plans, briefings and attitudes Initial contact –target might be Red, Blue, White or a non-target Build up confidence –by seeking additional information Classify and decide –take action (outside current model) Stages in a typical encounter

13. © Dstl 2005 Dstl is part of the Ministry of Defence UK UNCLASSIFIED 13 2 September 2005 90% Friend 5% Neutral 5% Enemy 90% Enemy 10% Neutral 60% Enemy 20% Neutral 20% Friend 100% Friend 50% Neutral 40% Enemy 100% Neutral 10% Friend 75% Enemy 20% Neutral 5% Friend 75 %Enemy 20% Neutral 5% Friend 90 % Classification Range 90 % Detection Range Preconceptions Zone of Certainty

14. © Dstl 2005 Dstl is part of the Ministry of Defence UK UNCLASSIFIED 14 2 September 2005 Stale Friendly Position Report Something there, I think it’s hostile Maximum Range of Movement Combined SA and positional Errors 100% Neutral Initial Contact

15. © Dstl 2005 Dstl is part of the Ministry of Defence UK UNCLASSIFIED 15 2 September 2005 Build up confidence Send in a scout Seek information from SA, EO, BTID etc. Contact HQ Check location Check SA Pause Advance

16. © Dstl 2005 Dstl is part of the Ministry of Defence UK UNCLASSIFIED 16 2 September 2005 Cognitive engines Fusion engine tracks likely target identity –uses the Dempster-Shafer method –similar to Bayesian inference, but using ‘confidence masses’ –starts with target ID pre-conceptions –updated as new information received Decision engine has two functions: –decides on further action before CID decision reached –decides on target identity when confidence threshold reached INCIDER iterates loop until a CID decision is made

17. © Dstl 2005 Dstl is part of the Ministry of Defence UK UNCLASSIFIED 17 2 September 2005 Output: ID: X at time t Expectation/ history Task selection Iteration during run Classification outcome Decision outcome Decision engine Confidence in target identity Battlespace target object Sensor model Situation awareness model Dempster- Shafer ‘fusion engine’ Pre-set human parameters of decision maker Variable human parameters of decision maker INCIDER decision model overview

18. © Dstl 2005 Dstl is part of the Ministry of Defence UK UNCLASSIFIED 18 2 September 2005 Way ahead for INCIDER Validation using synthetic environment –with psychometric testing of participants –collaborating with QinetiQ CHS and Land Division Better modelling of possible errors –in physical, informational and cognitive domains Aim to embed INCIDER in combat simulation –possibly Dstl’s Close Action Environment (CAEn) –will improve context, but may encounter interface problems

19. © Dstl 2005 Dstl is part of the Ministry of Defence UK UNCLASSIFIED 19 2 September 2005 Constructive simulation Behaviour INCIDER model Vignettes Validates Calibrate, modify Validation: ‘model–test–model’ Human factors data Generate s SE modelling Questions? Generates Live exercises Validate

20. Initial impressions and summary

21. © Dstl 2005 Dstl is part of the Ministry of Defence UK UNCLASSIFIED 21 2 September 2005 Initial results Results were intuitively ‘sensible’ –sensitive to different scenario vignettes –sensitive to physical, informational and cognitive factors –sensitive to interventions in SA, TID and TTPs Different CID interventions helped in different vignettes –sometimes ‘binary’, other times more subtle influences Interactions between some CID interventions seen –e.g. training and provision of specific TID equipments –statistically significant using ANOVAR

22. © Dstl 2005 Dstl is part of the Ministry of Defence UK UNCLASSIFIED 22 2 September 2005 Initial successes Quantitative assessment across three domains –enabling equitable comparison of different LoDs –contributes to understanding human factors in warfare High levels of cross-disciplinary collaboration –technologists and engineers –military SMEs –psychologists –mathematicians … and to include cost forecasters –brought together by operational analysts

23. © Dstl 2005 Dstl is part of the Ministry of Defence UK UNCLASSIFIED 23 2 September 2005 Summary Dstl required to assess CID interventions quantitatively –sensitive to parameters in SA, TID and TTPs –sensitive to physical, informational and cognitive factors Built the INCIDER model –and managed to provide acceptable ‘first cut’ data set Substantial success from first results –sensitive to changes in scenarios and CID parameters Contributes to understanding human factors in warfare –potential for application to other ‘fusion’ problems

24. © Dstl 2005 Dstl is part of the Ministry of Defence UK UNCLASSIFIED 24 2 September 2005 Questions? Always keen to hear of amicide events for catalogue – compilation of V2.0 is ongoing – please e-mail me on prsyms@dstl.gov.uk