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一种基于蝙蝠算法的多目标跟踪数据关联方法

A bat algorithm based data association method for multi-target tracking

  • 摘要: 针对多目标跟踪中的数据关联问题,提出了基于蝙蝠算法的数据关联方法。首先将多目标数据关联问题建模成组合优化问题,结合数据关联的特点,对蝙蝠算法的搜索更新规则进行改进,使其可以应用于多目标的数据关联问题,并给出了基于蝙蝠算法的多目标数据关联的详细流程。通过仿真实验和被动声呐实测数据测试表明,基于蝙蝠算法的多目标数据关联方法切实可行并且具有较好的效果。

     

    Abstract: A method based on Bat Algorithm to deal with the data association problem for multi-target tracking is proposed. First, the multi-target data association problem is transformed into a combinational optimization problem by modeling, and then the search and update rule of the bat algorithm is improved by combing the characteristics of multi-target data association. The new version of the bat algorithm can be applied to solving multi-target data asso-ciation problems. And in this paper, the detailed process of the bat algorithm based multi-target data association method is presented. Simulation results and test data of passive sonar show that this algorithm is feasible and effec-tive.

     

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