摘要
退化现象是应用粒子滤波算法的一个主要障碍,常规的再采样方法虽然可解决退化问题,但容易产生粒子耗尽现象.针对上述问题,将人工免疫算法引入粒子滤波,提出了人工免疫粒子滤波算法.通过人工免疫算法寻找较好的粒子用于估计,以增加粒子集的多样性,从而缓解了粒子滤波的退化现象并解决了粒子耗尽问题.仿真结果表明该算法是可行的.
Degeneracy phenomenon is a main disadvantage to particle filter application. Common re-sampling method can resolve degeneracy phenomenon, but the sample impoverishment is a secondary result. Therefore, artificial immune particle filter is proposed, in which artificial immune algorithm is introduced. Better particles for estimalcion are selected with artificial immune algorithm, as a result, the diversity of samples is enhanced. The degeneracy phenomenon is ameliorated and the problem of sample impoverishment is also resolved by using the proposed particle filter. Simulation results show the feasibility of the proposed immune particle filter algorithm.
出处
《控制与决策》
EI
CSCD
北大核心
2008年第3期293-296,301,共5页
Control and Decision
关键词
粒子滤波
退化问题
粒子耗尽
人工免疫算法
Particle filter
Degeneracy phenomenon
Sample impoverishment
Artificial immune algorithm
