拟蒙特卡罗聚合重采样粒子滤波无源定位算法

提出一种基于拟蒙特卡罗聚合重采样粒子滤波的机载无源定位算法．首先利用基于离散状态空间的粒子聚合技术对空间相近粒子进行加权聚合，在保证粒子空间分布合理性的同时有效抑制了粒子的退化;然后采用拟蒙特卡罗技术将重采样后的粒子向高似然区移动，优化了粒子在状态空间中的分布特性，提高了滤波精度．仿真结果表明: 新算法对比拟蒙特卡罗高斯粒子滤波算法，在保证滤波精度的同时，提高了运行效率．

Quasi-monte-carlo merging resampling particle filter for passive location

To meet the requirements of high location speed and accuracy in the air-borne passive location,a quasi-monte-carlo merging resampling particle filter is proposed.Firstly,the particle merging technique based on particles’ spatial similarity is used to keep rational distribution and restrain the weight degeneracy problem of the particles.Secondly,the deterministic samples are chosen according to the quasi-monte-carlo integration technique to push the particles into the high likelihood area and explore the state space more efficiently,so that the integration error is reduced and the precision of the filter is improved.Finally,simulation results show that the efficiency of the filter is improved while the precision is quaranteed compared with the quasi-monte-carlo gaussian particle filter.