使用遗传算法的自适应Kalman滤波器

Adaptive Kalman filter with genetic algorithm

基于Magill的Kalman滤波器池结构 ,设计了使用遗传算法的自适应Kalman滤波器 ,给出了离线和在线两种实现方案 .离线方案以辨识滤波参数为主要目的 ,进而可以对状态进行较准确的事后估计 ;在线方案以实时地对状态进行估计为目的 .对滤波参数寻优使用具有良好性能的浮点数编码遗传算法 ,该算法与二进制编码遗传算法相比收敛速度更快、搜索全局最优的能力更强 .

Adaptive Kalman filter with genetic algorithm was designed on the configuration of Magill's Kalman filter bank with. Two realization schemes including off-line and on-line given. The off-line scheme aims primarily at identifying filtering parameters, and the postmortem estimation of states can be obtained more accurately while. The on-line scheme aims at real-time estimation of the states. A well-performed float-coded genetic algorithm was used to optimize the filtering parameters. In comparison with the binary-coded genetic algorithm, this algorithom has higher convergence speed and greater ability of finding global optimum. The efficiency of the proposed adaptive Kalman filter has been verified through simulation.