Optimality analysis of one-step OOSM filtering algorithms in target tracking

查看全文 作　　者：ZHOU [1]WenHui;LI [2]Lin;CHEN [1]GuoHai;YU [3]AnXi

机构地区：[1]Nanjing Research Institute of Electronics Technology, Nanjing 210013, China;[2]Beijing Application and Development Center of Round-the-world Information, Beijing 100094, China;[3]College of Electronic Science and Engineering, NUDT, Changsha 410073, China

出　　处：《Science in China(Series F)》索引2007年第50卷第2期,共18页

基　　金：Supported by the National Natural Science Foundation of China (Grant No. 60402033) 摘　　要：In centralized multisensor tracking systems, there are out-of-sequence measurements (OOSMs) frequently arising due to different time delays in communication links and varying pre-processing times at the sensor. Such OOSM arrival can induce the “negative-time measurement update” problem, which is quite common in real multisensor tracking systems. The A1 optimal update algorithm with OOSM is presented by Bar-Shalom for one-step case. However, this paper proves that the optimality of A1 algorithm is lost in direct discrete-time model (DDM) of the process noise, it holds true only in discretized continuous-time model (DCM). One better OOSM filtering algorithm for DDM case is presented. Also, another new optimal OOSM filtering algorithm, which is independent of the discrete time model of the process noise, is presented here. The performance of the two new algorithms is compared with that of A1 algorithm by Monte Carlo simulations. The effectiveness and correctness of the two proposed algorithms are validated by analysis and simulation results. 关键词：目标跟踪一步OOSM滤波算法优化分析多传感器

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Optimality analysis of one-step OOSM filtering algorithms in target tracking

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