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针对杂波和漏检环境下多个群目标跟踪中形状估计精度低的问题,提出一种具有形状信息的多个群目标跟踪算法。该算法首先进行量测集划分进而起始航迹,随后对传统的群目标Bayesian递推算法进行改进,并融合群航迹关联等算法,利用改进的算法对多个群目标的运动状态和形状信息同时进行估计,大大提高了形状的估计精度。仿真结果表明,该算法不仅可以对多个群目标的运动状态同时进行跟踪,并且可以有效估计每个群目标的形状信息,大大提高了形状估计精度。
Aiming at the low accuracy of shape estimation in multiple target tracking in clutter and missed detection environment, a multi-target tracking algorithm with shape information is proposed. The algorithm first divides the measurement set and then starts the track, then improves the traditional Bayesian recursive algorithm and combines the algorithm of group track association, and improves the motion state and shape of multiple group targets by using the improved algorithm. The information is estimated at the same time, greatly improving the shape estimation accuracy. Simulation results show that this algorithm not only can track the motion of multiple targets at the same time, but also can effectively estimate the shape information of each target and greatly improve the accuracy of shape estimation.