关键词: 无迹粒子滤波, 自适应免疫优化, Metropolis准则, 阈值因子, 粒子退化, 粒子枯竭

Abstract: Aiming at the problem of Unscented Particle Filter（UPF） such as particles degeneracy and particles impoverishment at the partial observation, this paper proposes an Adaptive Immune Optimization Unscented Particle Filter（AIO-UPF） algorithm. The algorithm uses the global optimization ability and diversity of features of the immune algorithm in the affinity and concentration and the Metropolis criteria with the adaptive threshold factor δ makes the particle set move towards higher likelihood area. In this way, the diversity and effectiveness of particle have improved and the problem of particle degradation and depletion have alleviated. Simulation results indicate that the new particle filter outperforms obviously superior to PF and traditional Unscented Particle Filter, and in the state estimation accuracy increases by about 27%.

Key words: unscented particle filter, adaptive immune optimization, Metropolis criteria, threshold factor, particles degeneracy, particles impoverishment