Radar Target Tracking Based on Firefly Intelligent Optimization Particle Filter Algorithm

Abstract

Aiming at the problem of poor tracking accuracy in radar target tracking derived from particle filter (PF) under unknown measurement noise environment.. In this research, the basic particle filter algorithm is improved, and the Firefly Algorithm (FA) is brought in the particle filter in order to displace the original resampling process, so that the particles move on to the high-likelihood area, avoiding the screening of particles, thereby overcoming particle poverty. It also improves the particle quality.In the modeling process, the measurement noise variance is estimated in real time using moving window technology to further ameliorate the correctness of radar target tracking. Finally, by simulating radar target tracking, the availability of the algorithm is proved.