摘要
无迹卡尔曼粒子滤波算法作为典型的粒子滤波改进算法,有效提高了滤波精度.但旧的数据影响过大,导致滤波发散,借鉴衰减记忆无迹卡尔曼滤波算法的思想,通过引进衰减因子实现对当前测量数据利用的加强,减小历史数据对滤波结果的影响,提出了一种基于衰减记忆无迹卡尔曼滤波的粒子滤波算法.仿真实验表明,算法能够提供优于传统无迹卡尔曼滤波算法的跟踪精度.
Unscented Particle Filter as the typical improvement Particle Filter Algorithm effectively rises to the filter accuracy. But the old data once influences greatly lead to the filter＇s exhalement, this passage learn from Memory Attenuation UKF a thought of calculate way and pass to usher in a attenuation factor realization to current measurement data make use of strengthen, and let up a history data to filter result of influence, proposed a kind of particle filter algorithm based on Memory Attenuation UKF. The simulation experiment results show that the proposed algorithm can provide a better tack accuracy than tradition Unscented Particle Filter algorithm.
出处
《微电子学与计算机》
CSCD
北大核心
2012年第8期50-52,共3页
Microelectronics & Computer
