1. 1 S ystems Analysis Laboratory Helsinki University of Technology Kai Virtanen, Raimo P. Hämäläinen and Ville Mattila Systems Analysis Laboratory Helsinki University of Technology Team Optimal Signaling Strategies in Air Combat

2. 2 S ystems Analysis Laboratory Helsinki University of Technology Outline Signaling game: –The signaling system –Signaling in the team The message prioritization problem Importance index: –Age of information –Own plane information –Uncertainty in signaling Simulation environment Conclusions

3. 3 S ystems Analysis Laboratory Helsinki University of Technology Signaling game M-on-N air combat Pilot’s decision making based on information received from –visual detection, radio communication, radar measurements –a signaling system Data Link Electronic counter-countermeasure Computer (DLEC) developed by Finnish Air Force and Finnish industry team for transmitting messages under jamming for encoding and decoding signals

4. 4 S ystems Analysis Laboratory Helsinki University of Technology J A M M I N G Signaling in the team - Opponent’s state - Own state - Opponent’s state - Commands - Own state - Battle manager - Overall situation assessment - Ground measurements

5. 5 S ystems Analysis Laboratory Helsinki University of Technology Message prioritization problem The signaling system aims at helping in the situation assessment: –Fixed transmission capacity => The most important information must be transmitted => A decision problem Messages ranked based on the positions, velocities and accelerations of planes Select the most important message with respect to the overall goals of the team! Alternative messages: - States of the opponents observed by radar - Own state

6. 6 S ystems Analysis Laboratory Helsinki University of Technology Opponent 1 Alternative messages: - Opponent 1 - Opponent 2 - Own state Information: - Radar observations at t - Transmitted messages at t-  t, t-2  t,... Alternative messages: - Opponent 1 - Opponent 2 - Opponent 3 - Own state Information: - Radar observations at t+  t - Transmitted messages at t, t-  t,... Alternatives: - Own state data Prioritization environment Opponent 2 Opponent 3 Information: - Transmitted messages at t+  t, t,... Decision at t Decision at t+  t Decision at t+2  t

7. 7 S ystems Analysis Laboratory Helsinki University of Technology Terminology Importance: Importance of an individual opponent with respect to an individual member of own team Importance index: Importance of the individual opponent with respect to own team Selection of the message based on the importance index Own team Opponents : : Own team Opponents : : Importances Importance indices

8. 8 S ystems Analysis Laboratory Helsinki University of Technology Index of importance A decision analytic value function model Attributes based on information available in the signaling system Distance x 1 Angle x 2  Velocity x n “Importance of distance” v 1 (x 1 ) “Importance of angle” v 2 (x 2 )  “Importance of velocity” v n (x n ) Importance: v k and w k depend on the preferences and goals of a pilot Index: –Weighted sum of importances –Maximum importance

9. 9 S ystems Analysis Laboratory Helsinki University of Technology Age of information Quality of relayed information decreases in time No confirmation mechanism Important messages must be retransmitted frequently –Quality of information ensured –Success of transmissions ensured Time elapsed since the previous transmission related to a given plane (age of previous message) Elapsed time used as a multiplicative attribute –Importance } 

10. 10 S ystems Analysis Laboratory Helsinki University of Technology Own plane information Importance index: –Moving average of the importance indices of previous transmissions Time factor as before A B A assumes that B is an opponent => a message is needed A should send its own state information since B must know who A is  Team members must be aware of each others constantly

11. 11 S ystems Analysis Laboratory Helsinki University of Technology Uncertainty in prioritization Uncertainty in the attributes: –Inaccurate state variables due to radar errors –Age of information in the signaling system Uncertainty about the weights: –Incomplete preference statements –Different preferences within a group Interval analysis a new method to incorporate uncertainty

12. 12 S ystems Analysis Laboratory Helsinki University of Technology Interval importance index Signals’ error indices are intervals => Interval attributes Group or incomplete preference assessment => Interval weights The value function is minimized and maximized s.t. the attribute and weight intervals => Importance intervals Interval importance index based on aggregation criteria: Importance intervals Own team Opponents : : { Importance index The final selection based on interval importance indices Importance intervals

13. 13 S ystems Analysis Laboratory Helsinki University of Technology Information Prioritization in Air Combat (IPAC) Matlab-based simulation tool M-on-N air combat simulation: –Planes fly given trajectories or follow a feedback guidance law –Radar field assumed to be a cone –The signaling system model transmits messages Prioritization methods: –Importance index, interval importance index, range rate/range, –Construction of the value function Visualization of signaling and trajectories

14. 14 S ystems Analysis Laboratory Helsinki University of Technology Case: 4 vs. 4 combat Settings: - number of aircraft - simulation time - transmission time - radar’s scanning angle and range - etc.

15. 15 S ystems Analysis Laboratory Helsinki University of Technology Initial combat state team members opponents

16. 16 S ystems Analysis Laboratory Helsinki University of Technology Simulated solution signaling team member opponent whose info is relayed

17. 17 S ystems Analysis Laboratory Helsinki University of Technology Results Evolution of importance indices in time Measures for quality of relayed information Cumulative attack time of opponents Performance index of team members

18. 18 S ystems Analysis Laboratory Helsinki University of Technology Conclusions The decision analytical prioritization model: –The value function captures preferences of pilots –Uncertainties treated by interval techniques Practical use: –True implementation of the signaling system –Decision making module of air combat simulators Evaluation by pilots => “ This new model improves our situation assessment capability” Future research: –Signaling model incorporated into an air combat game => Impact of information structure on the outcome of the game