拟蒙特卡罗聚合重采样粒子滤波无源定位算法

doi:10.3969/j.issn.1001-2400.2012.05.026

Abstract

Abstract:

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.

Key words: passive location, quasi-monte-carlo, particle filter, particle merging, resampling, state estimate

CLC Number:

TN958.57

LIU Xue;JIAO Shuhong;LAN Xiaoyu. Quasi-monte-carlo merging resampling particle filter for passive location[J].J4, 2012, 39(5): 154-160.

References

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

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