论文部分内容阅读
为解决集中式多传感器系统中多目标跟踪问题,提出了一种基于S-D分配的集中式多传感器联合概率数据互联算法。算法首先应用广义S-D分配的规则对每个传感器送来的观测数据进行排列组合,然后对每个组合中各量测点进行概率加权以获得一个等效量测点,最后根据每个等效量测点的联合似然函数计算其联合互联概率并获得融合中心的状态估计。该文最后给出了该算法与已有集中式多传感器联合概率数据互联算法的仿真比较,仿真结果表明该文算法的跟踪性能更优越。
In order to solve the multi-target tracking problem in a centralized multi-sensor system, a centralized multi-sensor joint probability data interconnection algorithm based on S-D assignment is proposed. Firstly, the algorithm applies the generalized SD distribution rule to arrange and combine the observed data from each sensor. Then, the weight of each measurement point in each combination is weighted to obtain an equivalent measurement point. Finally, according to each equivalent The joint likelihood function of measurement points calculates the probability of joint interconnection and obtains the state estimate of the fusion center. Finally, the simulation results of the proposed algorithm and the existing centralized multi-sensor joint probabilistic data interconnection algorithm are given. The simulation results show that the algorithm has better tracking performance.