Transcript VIATO - Visual Interactive Aircraft Trajectory Optimization
Team Optimal Signaling Strategies in Air Combat
Kai Virtanen, Raimo P. Hämäläinen and Ville Mattila
Systems Analysis Laboratory Helsinki University of Technology
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Analysis Laboratory Helsinki University of Technology
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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
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Analysis Laboratory Helsinki University of Technology
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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 •
D
ata
L
ink
E
lectronic counter-countermeasure
C
omputer (DLEC) • developed by Finnish Air Force and Finnish industry team • for transmitting messages under jamming • for encoding and decoding signals
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ystems
Analysis Laboratory Helsinki University of Technology
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Signaling in the team
- Opponent’s state - Commands - Own state -
Opponent’s state - Own state
- Battle manager - Overall situation assessment
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- Ground measurements 4
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
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 •
Messages ranked based on the positions, velocities and accelerations of planes S
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Prioritization environment
Decision at t+
D
t Decision at t
Alternative messages: - Opponent 1 - Opponent 2 - Own state Information: - Radar observations at t - Transmitted messages at t D t, t-2 D t, ...
Opponent 1 Alternative messages: - Opponent 1 - Opponent 2 - Opponent 3 Opponent 2 - Own state Opponent 3 Information: - Radar observations at t+ D t - Transmitted messages at t, t D t, ...
Decision at t+2
D
t
Alternatives: - Own state data Information: - Transmitted messages at t+ D t, t, ...
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Terminology
•
Importance
: Importance of an individual opponent with respect to an individual member of own team Own team Importances Opponents Own team Importance indices Opponents : : : : •
Importance index
: Importance of the individual opponent with respect to own team • Selection of the message based on the importance index
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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: n k 1 k ( x k ) • v k and w k depend on the preferences and goals of a pilot • Index: – Weighted sum of importances – Maximum importance
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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 k n 1 k ( x k )
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Analysis Laboratory Helsinki University of Technology
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Own plane information
A
assumes that
B
is an opponent => a message is needed
A B
Team members must be aware of each others constantly
A
should send its own state information since
B
must know who
A
is • Importance index: – Moving average of the importance indices of previous transmissions • Time factor as before
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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
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{ •
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: Own team Importance intervals Opponents : :
The final selection based on interval importance indices S
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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
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Settings:
- number of aircraft - simulation time - transmission time - radar’s scanning angle and range - etc.
Case: 4 vs. 4 combat
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team members
Initial combat state
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opponents 15
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Analysis Laboratory Helsinki University of Technology
Simulated solution
signaling team member opponent whose info is relayed 16
Results
• Evolution of importance indices in time • Measures for quality of relayed information • Cumulative attack time of opponents • Performance index of team members
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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
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