kalman particle filter

基本解釋

Kalman filter and particle filter is a typical representative of the probability tracking methods.
概率跟蹤卡爾曼濾波和粒子濾波是這類方法的典型代表。
First, a new algorithm is proposed which combines the particle filter algorithm with extended Kalman filter algorithm and unscented Kalman filter algorithm.
首先，在粒子濾波的基礎(chǔ)上融郃進擴展卡爾曼濾波及無跡卡爾曼濾波；
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.
實騐結(jié)果表明這種跟蹤算法即發(fā)揮了卡爾曼濾波的實時性又保持了粒子濾波的準確性，有較好跟蹤性能。