基于邻域拓扑结构的目标协同跟踪算法

针对目标跟踪问题，提出一种新的节点协同跟踪方法，通过节点间邻域拓扑结构协同建立各节点的关联性，对目标进行协作监测与跟踪。算法根据节点信息共享时的传播差异，通过节点间的传播概率准确计算各节点捕捉增益，从而确定簇成员，增加了确定目标位置的精度。结合感知区域及最大移动定理界定目标最终移动区域，采用网格法算出区域质心。实验结果证明，与同类方法相比，该算法具有较高的跟踪精度，且跟踪稳定度较好。

Collaborative tracking algorithm based on target neighborhood topology

Aiming at the problem of target tracking, a new algorithm for cooperative target monitoring and tracking is proposed based on neighborhood topology of nodes. According to communication differences when nodes share information, the approach calculates the capture gain of each node based on communication probability, through which the cluster members are determined and the precision of targets position is improved. Finally, the final area of the target is defined by the intersection of the nodes sensing area and the maximum range of target movement. The area centroid is calculated using the grid method. The simulation results show that the proposed approach outperforms other similar methods in both tracking accuracy and stability.