A new particle filter algorithm based on new Clone particle swarm optimization（NCPSO-PF） is presented in this paper in order to solve the problem of low precision and complicated calculation of particle filter based on particle swarm optimization algorithm(PSO-PF). The algorithm enables the particles to fit the environment better and then reach the goal of global optimization through orthogonal initialization, clonal selection and local searching of self-learning. Finally different models are used for simulation experiment and the results indicate that this new algorithm improves the operation speed and precision of practical engineering application.
Bo, Yuming; Chen, Zhimin; Zhang, Jie; and Zhu, Jianliang
"New clone particle swarm optimization-based particle filter algorithm and its application,"
Applied Mathematics & Information Sciences: Vol. 07:
1, Article 21.
Available at: https://digitalcommons.aaru.edu.jo/amis/vol07/iss1/21