The Sequential Monte Carlo Probability Hypothesis Density (SMC-PHD) filter with the idea of track- before-detect (TBD) is a kind of effective means to deal with multitarget detection and tracking under complex electromagnetic condition with low Signal- to-Noise Ratio (SNR). However, it suffers from inaccurate estimation number of targets and large computational complexity due to the improper assumption when the TBD is incorporated into the SMC-PHD filter. To combat this problem, we propose an improved SMC-PHD filter method for multitarget TBD in this paper, where a new measurement model and a novel method to determine the clutter density are designed. Simulation results demonstrate that the proposed method outperforms the traditional method in terms of tracking accuracy and computational complexity.


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    Title :

    Improved SMC-PHD Filter for Multi-Target Track-Before-Detect


    Contributors:
    Luo, Xin (author) / Yang, Chaoqun (author) / Chen, Ruiyong (author) / Shi, Zhiguo (author)


    Publication date :

    2016-09-01


    Size :

    1133981 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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