Research on over-the-horizon air combat guidance method based on dynamic RCS

基于动态RCS的超视距空战导引方法研究

¹ CASIC Research Institute of Intelligent Decision Engineering, Wuhan 430040, China
² School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710129, China
³ Luoyang Institute of Electro-Optical Equipment, AVIC, Luoyang 471009, China

Received: 1 February 2024

Abstract

In order to solve the problem of target loss caused by too small target RCS in the process of long-range enemy contact, the relationship between target RCS and radar detection probability is analyzed, and a guidance method based on Particle Swarm Optimization (PSO) is proposed. Firstly, the influence of dynamic RCS is considered to obtain the optimal attack situation, and then the situation evaluation function considering dynamic RCS constraints is established. Then, to maximize the situation assessment value as the goal, particle swarm optimization algorithm is used to find the most appropriate overload at every moment, so as to guide our aircraft into the attack zone to constitute the launch conditions. The simulation results show that considering the RCS constraint, the particle swarm overload optimization method can reduce the fluctuation degree of target RCS and effectively reduce the probability of target loss during long-range enemy guidance.

摘要

针对远距接敌过程中目标雷达散射截面(radar cross section, RCS)过小引起的目标丢失问题, 分析了目标RCS与雷达探测概率的关系, 提出了一种基于粒子群过载寻优(particle swarm optimization, PSO)的导引方法。考虑动态RCS的影响得出最佳攻击态势, 在此基础上建立考虑动态RCS约束的态势评估函数; 以态势评估值最大化为目标, 利用粒子群算法寻找每一时刻最合适的过载, 从而导引我方战机进入攻击区构成发射条件。在不同场景下开展了相关仿真, 结果表明考虑RCS约束, 基于粒子群过载寻优的方法在导引战机达成最佳攻击态势的过程中, 能减小目标RCS的起伏程度, 有效地降低了远距离接敌导引过程中目标丢失概率。