联合Metropolis算法和MDL准则的密集多目标分辨算法

doi:10.3969/j.issn.1001-2400.2014.03.026

Abstract

Abstract:

When multiple targets' echoes fall into the same resolution cell of monopulse radar, the echoes are distinguished at a slow rate of convergence using the available processing algorithm. Aiming at this problem, a new processing algorithm is presented, which combines the Metropolis algorithm with minimum description length (MDL) criteria. Constructing the update function and the rule of iteration can improve the convergence of the different markov chains of parameters estimation. Then, by using the fusion decision rule, valid samples are selected to calculate the parameters. Lastly, the numbers of multiple unresolved targets are calculated by using minimum description length criteria. The proposed algorithm has not only a higher rate of convergence, but also a better resolution capability under multiple targets with a more accurate parametric estimation. The efficacy and feasibility of the method are verified by simulation.

Key words: multiple unresolved targets, distinguish algorithm, metropolis algorithm, minimum description length criteria, markov chain

LI Zhenxing;LIU Jinmang;ZHOU Zheng;GUO Xiangke;LI Yanlei. Multiple unresolved targets distinguish algorithm by combination of the Metropolis algorithm with MDL criteria[J].J4, 2014, 41(3): 174-180.

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Multiple unresolved targets distinguish algorithm by combination of the Metropolis algorithm with MDL criteria

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