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Centralized Fuzzy Data Association Algorithm of Three-sensor Multi-target Tracking System

机译:三传感器多目标跟踪系统的集中模糊数据关联算法

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摘要

For improving the effect of multi-target tracking in dense target and clutter scenario, a centralized fuzzy optimal assignment algorithm (CMS-FOA) of three-sensor multi-target system is proposed. And on the base of this, a generalized probabilistic data association algorithm (CMS-FOAGPDA) based on CMS-FOA algorithm is presented. The fusion algorithm gets effective 3-tuple of measurement set by using components of several satisfactory solutions of the fuzzy optimal assignment problem and then uses generalized probabilistic data association algorithm to calculate the update states of targets. Simulation results show that, in the aspect of multi-target tracking accuracy, CMS-FOA algorithm is superior to the optimal assignment (CMS-OA) algorithm based on state estimate and CMS-FOAGPDA algorithm is better than CMS-FOA algorithm. But considering the time spent, CMS-FOA algorithm spends a minimum of time and CMS-FOAGPDA algorithm is exactly on the contrary. Therefore, compared with CMS-OA algorithm, the two algorithms presented in the study each has its advantages and should be chosen according to the needs of the actual application when in use.
机译:为了提高在密集目标和杂乱场景下多目标跟踪的效果,提出了一种三传感器多目标系统的集中式模糊最优分配算法(CMS-FOA)。在此基础上,提出了一种基于CMS-FOA算法的广义概率数据关联算法(CMS-FOAGPDA)。该融合算法通过使用模糊最优分配问题的几个满意解的分量来获得有效的三元组测量值,然后使用广义概率数据关联算法来计算目标的更新状态。仿真结果表明,在多目标跟踪精度方面,CMS-FOA算法优于基于状态估计的最优分配(CMS-OA)算法,CMS-FOAGPDA算法优于CMS-FOA算法。但是考虑到所花费的时间,CMS-FOA算法花费的时间最少,而CMS-FOAGPDA算法恰恰相反。因此,与CMS-OA算法相比,本研究提出的两种算法各有优点,应在使用时根据实际应用的需要进行选择。

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