Terminal attitude selection method of missile attack aircraft

Abstract

The appropriate terminal attitude of missile is important to improve the damage effectiveness of fragmentation warhead against aircraft targets. In this paper, three missile terminal attitude selection methods are proposed to solve the problem of terminal attitude selection in different situations according to their respective evaluation indexes. The MVE-based method uses the damage probability of each detonation point around the aircraft at a given attitude of missile to calculate the Mean Volume of Effectiveness (MVE) at the corresponding attitude, and then uses the MVE for different attitudes to select the terminal strike attitude. The detonation position-based method addresses the case where the missile detonation position can be assessed in advance. Given the effects of missile guidance errors and fuze activation position errors, Monte Carlo simulations are used to calculate the damage probability of aircraft with different strike attitudes, from which the terminal strike attitude is selected. The BP-ANN model-based method uses the constructed Back Propagation Artificial Neural Network (BP-ANN) model instead of simulation to calculate the evaluation indexes in the corresponding cases of MVE-based method and Detonation position-based method, which can improve the efficiency of attitude selection. Simulations are conducted for different scenarios to verify the feasibility and effectiveness of the proposed method.