To overcome the high computational complexity of the existing joint tracking and classification (JTC) algorithm, particle filter (PF) is introduced to replace numerical integration in solving JTC, and hence computational load is considerably reduced. Our particle filter based JTC (PF-JTC) algorithm makes use of the target kinematic information provided by the low-resolution radar (LLR) and the target electromagnetic equipment information provided by the electronic support measure (ESM) to improve the performance of tracking and classification simultaneously. Simulation results verify the effectiveness of the proposed PF-JTC algorithm.


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    Title :

    Particle filter based joint tracking and classification


    Contributors:
    Zhan, Kun (author) / Xu, Long (author) / Jiang, Hong (author) / Bai, Liang (author) / Wu, Mengjie (author)


    Publication date :

    2014-08-01


    Size :

    241539 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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