Abstract

Resampling in the particle filter algorithm can solve the algorithm's degeneracy problem. In order to decrease the execution time of the particle filter, the parallel resampling particle filter algorithm is proposed. In the algorithm, firstly all weights of the particles are sorted according to the ascending order. Secondly the particles space is classified into two independent sets. Finally the particles that will be resampled from two sets respectively are found parallelly according to the random search method. According to the theoretical analysis and the experiment results, the algorithm can reduce the search space for resampling and can shorten the search time, so it has high efficiency in the implementation. What is more, the algorithm can overcome the blindness of resampling, and can better embody the basic idea of resampling which is a good weight particle to be reproduced more, so it has better filter and estimation performance.

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