1 / 13

Game Optimal Support Time of a Medium Range Air-to-Air Missile

Game Optimal Support Time of a Medium Range Air-to-Air Missile. Janne Karelahti, Kai Virtanen, and Tuomas Raivio Systems Analysis Laboratory Helsinki University of Technology. Contents. Problem setup Support time game Modeling the probabilities related to the payoffs Numerical example

kiefer
Download Presentation

Game Optimal Support Time of a Medium Range Air-to-Air Missile

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Game Optimal Support Time of a Medium Range Air-to-Air Missile Janne Karelahti, Kai Virtanen, and Tuomas Raivio Systems Analysis Laboratory Helsinki University of Technology

  2. Contents • Problem setup • Support time game • Modeling the probabilities related to the payoffs • Numerical example • Real time solution of the support time game • Conclusions

  3. Problem setup • One-on-one air combat with missiles • Phases of a medium range air-to-air missile: • Target position downloaded from the launching a/c • In blind mode target position is extrapolated • Target position acquired with the missile’s own radar • In phase 1 (support phase), the launching a/c must keep the target within its radar’s gimbal limit • Prolonging the support phase • Shortens phase 2, which increases the probability of hit • Degrades the possibilities to evade the missile possibly fired by the target

  4. Problem setup Phase 3: locked Phase 2: extrapolation Phase 1: support The problem: optimal support times tB, tR?

  5. Modeling aspects • Aircraft & Missiles • 3DOF point-mass models • Parameters describe identical generic fighter aircraft and missiles • Missile guided by Proportional Navigation • Assumptions • Simultaneous launch of the missiles • Constant lock-on range • Target extrapolation is linear • Missile detected only when it locks on to the target • State measurements are accurate • Predefined support maneuver of the launcher keeps the target within the gimbal limit

  6. Support time game • Gives game optimal support times tB and tRas its solution • The payoff of the game  probabilities of survival and hit • The probabilities are combined as a single payoff with weights • The weights , i=B,R reflect the players’ risk attitudes Blue’s probability of survival Blue missile’s probability of hit Blue: Red: Blue missile’s probability of guidance Blue missile’s probability of reach Blue missile’s prob. of hit = ´

  7. Modeling the probabilities pr and pg • Probability of reach pr: • Depends strongly on the closing velocity of the missile • The worst closing velocity corresponding to different support times  a set of optimal control problems for both players • Probability of guidance pg: • Depends, i.a., on the launch range, radar cross section of the target, closing velocity, and tracking error

  8. pr and pg in this study Probability of reach closing velocity at distance df optimize: minimize closing velocity extrapolate predetermined support maneuver Probability of guidance tracking error at

  9. Minimum closing velocities • For each (tB,tR), the minimum closing velocity of the missile against the a/c at a given final distance df (here for Blue aircraft): • u = Blue a/c’s controls, x = states of Blue a/c and Red missile, f = state equations, g = constraints • Initial state = vehicles’ states at the end of Blue’s support phase • Direct multiple shooting solution method => time discretization and nonlinear programming

  10. Solution of the support time game • Reaction curve: • Player’s optimal reactions to the adversary’s support times • Solution = Nash equilibrium • Best response iteration • Red player: • Blue player: Support time of Red wB=0 Support time of Blue

  11. support phase altitude, km extrapolation phase locked phase x range, km Example trajectories Red (left), wR=0.5, supports 12.4 seconds Blue (right), wB=1.0, supports 5.0 seconds y range, km

  12. Real time solution • Off-line: • Solve the closing velocities and tracking errors for a grid of initial states • In real time: • Interpolate CV’s and TE’s for a given intermediate initial state • Apply best response iteration • Red: • Blue: optimized interpolated Support time of Red Support time of Blue

  13. Conclusions • The support time game formulation • Seemingly among the first attempts to determine optimal support times • AI and differential game solutions: the best support times based on predefined decision heuristics • Discrete-time air combat simulation models: predefined support times • Pure differential game formulations are practically intractable • Utilization aspects • Real time solution scheme could be utilized in, e.g., • Guidance model of an air combat simulator • Pilot advisory system • Unmanned aerial vehicles

More Related