摘要
雷达目标跟踪量测系统常受到闪烁噪声干扰,导致传统滤波算法的滤波性能急剧下降甚至发散。文中提出了改进粒子滤波算法,利用扩展卡尔曼滤波产生重要性概率密度函数。提出改进的重采样策略,提高采样粒子的有效性。将文中算法与PF及EKPF算法进行了仿真比较,结果表明该算法具有较优的跟踪性能。
Radar target tracking measurement systems is often disturbed by the glint noise, it leads to the performances of conventional filters degrade severely. This paper proposes an improved particle filter algorithm, the extended Kalman filtering is modified by providing the importance of probability density function. New resample strategy improves the effectiveness of particles. The proposed method is compared with the PF and the EKPF algorithm via the simulations. The results show that this algorithm has better tracking performance.
出处
《信息技术》
2013年第2期121-123,共3页
Information Technology
关键词
目标跟踪
粒子滤波
扩展卡尔曼滤波
人工免疫
target tracking
particle filter
extended Kalman filter
artificial immune
