kalman particle filter

基本解释

Kalman filter and particle filter is a typical representative of the probability tracking methods.
概率跟踪卡尔曼滤波和粒子滤波是这类方法的典型代表。
First, a new algorithm is proposed which combines the particle filter algorithm with extended Kalman filter algorithm and unscented Kalman filter algorithm.
首先，在粒子滤波的基础上融合进扩展卡尔曼滤波及无迹卡尔曼滤波；
Experimental results show that this approach can maintain the efficiency of kalman algorithm and the powerful ability of particle filter algorithm, so it is of advanced property.
实验结果表明这种跟踪算法即发挥了卡尔曼滤波的实时性又保持了粒子滤波的准确性，有较好跟踪性能。