关键词: 微分进化, 粒子滤波, 重采样, 粒子退化

Abstract: Aiming at solving the sample impoverishment phenomenon caused by the re-sample scheme of conventional particle filter, an evolutionary particle filter is proposed, in which differential evolutionary programming is introduced. The improved approach relieves the effect caused by samples impoverishment through ameliorating the diversity of samples set and improves the ability of tracking the target via using the crossover and mutation operators. Simulation results demonstrate that compared with the traditional particle filter, this improved method can evaluate the state and track target more accurately, and the precision of this algorithm increases more than 100 percent than standard particle filter. It needs fewer particles to achieve tracking problems.

Key words: differential evolution, particle filter, resample, samples impoverishment