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摘要:In high-resolution radar applications,the scatter distribution of target usually evolves non-linearly with the target movement,and thus it is difficult for a Bayesian filter to achieve an accurate estimation of the target extension state on its own.To solve this problem,we propose to use measurement features to help to propagate the posterior of the target extension in this paper,resulting in a feature-aided extended target probability hypothesis density(FA-ET-PHD)filter,where the features are applied to calculate the partition weights.Since the feature-based weights do not abide by the Bayesian inferring framework,the FA-ET-PHD filter can effectively avoid the deterioration of the performance in multi-target tracking caused by the nonlinear change of the distribution of scatters.Simulation results show that the proposed method can improve the accuracy of the multi-target state estimation as well as the robustness.
会议名称:

第33届中国控制与决策会议

会议时间:

2021-05-22

会议地点:

中国云南昆明

  • 专辑:

    信息科技

  • 专题:

    电信技术

  • DOI:

    10.26914/c.cnkihy.2021.023250

  • 分类号:

    TN958

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