一种新的基于模糊聚类的多目标跟踪算法

提出了一种新的基于模糊聚类的多目标跟踪算法,该算法通过模糊聚类得到测量点迹与目标预测位置之间的隶属度,并将其作为权值系数对有效回波的信息量进行加权,来实现目标的状态估计的更新。仿真结果表明,传统算法在多目标密集时易产生关联错误而导致跟踪发散,新算法通过加权过程保证了对多目标的高精度跟踪。

Novel multiple targets tracking algorithm based on fuzzy clustering

A novel multiple targets tracking algorithm based on fuzzy clustering is proposed. It uses the degrees of membership between the measurements and the predicted locations of the targets which are obtained through fuzzy clustering as weight numbers of innovations to realize the update of targets' states.The simulation results demonstrate that the conventional algorithm is easily to make a wrong association when targets are near to each other which may lead to the emanative tracking.However,the new algorithm makes use of the weighted sum of innovations to guarantee high quality of tracking.