A new immune particle filter algorithm for tracking a moving target

In this paper, we first analyze the performance of standard particle filter algorithm, which mainly focuses on the sample impoverishment brought by re-sampling to resolve degeneracy phenomenon. In order to increase the diversity of particles and the number of meaningful particles, we consider the basic immune clonal selection algorithm and memory mechanism. We introduce artificial immune algorithm into particle re-sampling process, and propose a new particle filter algorithm based on immune re-sampling which is called immune particle filter. The proposed algorithm is better than the standard particle filter in particle diversity and efficiency. Finally, we show the effectiveness and robustness of the proposed immune particle filter by simulation.