Abstract: Considering the degeneracy of particle weight and the large amount of calculation existing in the standard particle filtering algorithm,a particle swarm optimization particle filtering method based on the criteria of MKLD is brought forward in this paper.This method embeds the particle swarm optimization algorithm into the important sampling process of the particle filtering method,to optimize the sampling process and improve the fine collection of particles while maintaining the state estimation performance of the particle filtering method.At the same time,in order to reduce the computational complexity,the new algorithm adaptively selects the optimized particles and the implementation moment of the particle swarm optimization based on the criteria of MKLD.The results of a large amount of computational experiments and the GPS/DR integrated navigation simulation experiment show the effectiveness of the novel method proposed in this paper.