In this paper, a data association problem is investigated in which a multi-platform detecting multi-target scenario is considered. A PointNet-based data association algorithm for matching measurements and targets is proposed which can deal with the measurement noises, false alarms, missed detections due to environmental interference and limitations on sensor resolution, as well as unknown target motions. The constantly changing number of targets and measurements are also taken into account. First, the data preprocessing method is provided. Then, a PointNet-based data association algorithm is designed by which the data association probabilities between the real targets and the measurements are given. Then, the effectiveness and the accuracy of the proposed algorithm are proved by the test experiments.


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    Title :

    A PointNet-Based Multi-platform Multi-target Data Association Algorithm


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Yan, Liang (editor) / Duan, Haibin (editor) / Yu, Xiang (editor) / Chu, Xuan (author) / Zheng, Tianyu (author) / Zhang, Xinran (author) / He, Fenghua (author)


    Publication date :

    2021-10-30


    Size :

    10 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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