一种基于局部搜索采样的粒子滤波检测前跟踪算法

A particle filter track-before-detect algorithm based on local search sampling

针对一类状态部分可测系统粒子滤波检测前跟踪算法中高维采样效率低的问题,提出一种基于局部搜索采样的粒子滤波器检测前跟踪算法.该算法在后验状态更新之后,在可测分量估计值的附近,对不可测分量引入先验分布信息,用少量粒子进行局部搜索采样,提高了粒子采样效率.仿真结果表明,所提出算法获得了更好的检测和跟踪性能.

A particle filter track-before-detect based on local search sampling is proposed to deal with the low sampling efficiency in high-dimension state space for the particle filter track-before-detect in a class of state partially observable system.After the update of the posterior state,by using the prior distribution information of the unobservable components,a kind of local search sampling strategy is executed around the estimate of observable components by a small amount of particles,which improves the efficiency of state sampling for particles.Simulation results show that the new algorithm obtains better detection and tracking performance.