基于粒子筛选处理的粒子滤波改进算法

Improved Particle Filter Based on New Particle Selection and Process Strategy

针对粒子滤波中的粒子贫化问题,分析了目前用于增加粒子多样性方法存在的不足,提出了一种新的粒子筛选与处理方法。通过设置筛选区间,保留该区间内的粒子,对区间外的粒子进行移动处理,从而改善粒子分布。仿真结果表明,该方法能够有效缓解粒子贫化问题,提高滤波精度。同时由于有效样本数增加,降低了重采样次数,总体上减少了算法运行时间。

To solve the particle impoverishment problem in particle filter （PF）, an improved al- gorithm is proposed based on a new particle selection and process strategy. By choseing filte- ring interval, the predicted particles falling into the desired interval are accepted, and the oth- ers outside the interval are corrected by concentrating them from remote areas to high likeli- hood areas of probability density function. Experimental results show that the new algorithm increases the filtering accuracy, compared with standard PF. Meanwhile, as the number of ef- fective particle increases, the requirement of resampling operation is decreased, thus reducing the computational time.