基于S-D分配的集中式多传感器不敏滤波算法  

Centralized Multisensor Unscented Filter Algorithm Based on S-D Assignment

作　　者：管旭军[1,2] 芮国胜[1] 周旭[1] 张玉玲 

机构地区：[1]海军航空工程学院电子信息工程系,山东烟台264001 [2]海军湛江保障基地通信雷达声纳修理厂,广东湛江524009

出　　处：《电子科技大学学报》2010年第4期542-545,539,共5页Journal of University of Electronic Science and Technology of China

基　　金：国家自然科学基金(60572161)

摘　　要：研究了非线性环境中的集中式多传感器多目标跟踪问题,提出了一种基于S-D分配的集中式多传感器不敏滤波算法。算法通过广义S-D分配技术实现每个传感器中的量测与目标的数据关联,求得所有可能互联中的最佳划分,然后按照顺序多传感器联合概率数据互联算法,依次处理最佳划分中各传感器源于同一目标的量测,在此基础上通过不敏卡尔曼滤波(UKF)解决非线性系统中的目标跟踪问题。最后给出了该算法与MSJPDA/EKF算法的仿真比较,结果表明该算法具有更高的稳定性和跟踪精度。For the problem of multisensor-multitarget tracking in nonlinear system, a novel centralized multisensor unscented filter algorithm based on S-D assignment, SD-CMSUKF, is proposed. In the new algorithm, the association of measurements from each sensor to targets is first implemented according to the generalized S-D assignment technique and the optimal partition can be achieved. Then in the optimal partition, the measurements from the same target are dealt with sequentially in terms of the principle of sequential multisensor joint probabilistic data association algorithm （MSJPDA）. Based on these, UKF is used for the propagation of state distribution in nonlinear system and the SD-CMSUKF algorithm is derived. Compared with the MSJPDA/EKF, the accuracy and robustness of the proposed algorithm are improved. Simulation results show the superiority of the new algorithm.

关 键 词：多传感器多目标跟踪 非线性 S-D分配 不敏卡尔曼滤波 

分 类 号：TN95[电子电信—信号与信息处理]