The Design of a Modified PSO Guidance Law Using Predictor and LOS Rate Evaluation

Abstract

Abstract. This paper proposes a modified particle swarm optimization guidance (MPSOG) for the pursuit-evasion optimization problem. If the line-of-sight (LOS) rate equals zero, the curvature of the missile's trajectory would be smaller and the probability of intercept greater. Thus, we propose using a MPSOG to improve the guidance performance. The MPSOG uses a Kalman filter to predict a target's dynamic. The lateral acceleration commands of the y-and z-axis are optimized by the particle swarm optimization (PSO) algorithm, respectively. Numerical simulation results show that the MPSOG have better guidance performance than proportional navigation guidance and particle swarm optimization guidance in miss distance, time-to-go, and final lateral acceleration commands.