Modeling and game strategy analysis of suppressing IADS for multiple fighters’ cooperation

Abstract

This paper addresses the problem of suppression of the integrated air defense system (IADS) by multiple fighters' cooperation. Considering the dynamic changing of the number of the nodes in the operational process, a profit model for the influence of the mission's cost for the whole system is developed for both offense and defensive sides. The scenario analysis is given for the process of suppressing the IADS by multiple fighters. Based on this scenario analysis, the modeling method and the specific expression for the payoff function are proposed in four cases for each node. Moreover, a distributed virtual learning algorithm is designed for the n-person and n-strategy game, and the mixed strategy Nash equilibrium (MSNE) of this game can be solved from the n × m × 3-dimensional profit space. Finally, the simulation examples are provided to demonstrate the effectiveness of the proposed model and the game algorithm.

Study on Consulting Air Combat Simulation of Cluster UAV Based on Mixed Parallel Computing Framework of Graphics Processing Unit

“…This article is different from [19][20][21][22] using differential game as the decision core but combines the matrix game with the negotiation theory and uses the U-solution to study the theoretical framework of the cooperative air combat. The advantage of using matrix game is that when we calculate the best strategy, only Runge-Kutta method to integral the motion equations is necessary, avoiding the differential game demand solving the double side extreme value problem.…”

“…This is a dare to or impossible tactic during one-on-one air combat, which has increased the kill rate as a whole. The main attack and assist role are determined by λ pq k in (22), the biggest one is the main attack, and the rest are assists. The strategy of the assisting machine uses (25) to find the best decision; while the remaining one is the main attacker, at this time, look for the strategy to minimize the U value in (23).…”

“…This is a dare to or impossible tactic during one-on-one air combat, which has increased the kill rate as a whole. The main attack and assist role are determined by pq k λ in (22), the biggest one is the main attack, and the rest are assists.…”

“…Each strategy combination uses a GPU's thread to solve the motion equations of (13) to (21) in a time interval, and predicts the position, attitude, and velocity data of all the fighters of both fleets at the next time interval. This data is still calculated in the GPU's thread for all fighters' dominant values described in (22), and then all U values from (23) are calculated in parallel. Using the function written in CUDA to get the minimum or maximum value from the 7 k × 7 k array satisfied (25) to find the best strategy for both side's fighters.…”

“…Therefore, Ref. [22] introduces the fusion mechanism of differential game and negotiating theory. Ref.…”