关键词: 运动目标, 粒子滤波, 分层采样, 聚类方法, 追踪精度

Abstract: To solve the poor robustness due to the changing moving target or the inaccurate tracking, a stratified sampling particle filter algorithm based on clustering method was proposed. The sampling space was divided into several parts by group sampling to make sampling points focused on the big probability density value part, thus the sampling error was reduced half of the original; the clustering algorithm could group the particles reasonably by weight, the diversity of particles was kept, thus the tracking precision was improved. The experimental results show that the tracking error of proposed method is less than half of the original one, and the stability has strengthened in each simulation time, as well as the tracking precision.

Key words: moving target, particle filter, stratified sampling, clustering method, tracking precision