Optimal Centralized Update With Multiple Local Out-of-Sequence Measurements
Optimal Centralized Update With Multiple Local Out-of-Sequence Measurements
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DOI：
10.1109/tsp.2009.2012885
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发表时间：
2009-04
影响因子：
5.4
通讯作者：
Xiaojing Shen;Yunmin Zhu;Enbin Song;Yingting Luo
中科院分区：
文献类型：
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作者：
Xiaojing Shen;Yunmin Zhu;Enbin Song;Yingting Luo
在多传感器目标跟踪系统中，传感器产生的观测结果通常不按顺序到达中央处理器。已经有一些用于单次失序测量（OOSM）的更新算法。在本文中，我们考虑具有多个异步（不同滞后时间）OOSM 的最佳集中式更新算法。首先，我们将最优更新算法推广到[Y. Bar-Shalom，“跟踪中的失序测量更新：精确解决方案”，IEEE 航空航天和电子系统学报，卷。 38，第 769-778 页，2002 年 7 月]具有多个一步滞后 OOSM 的最优集中更新算法。然后，基于最佳线性无偏估计，我们提出了一种具有多个任意步长滞后 OOSM 的最优集中更新算法。最后，提出了两种次优集中更新算法来降低计算复杂度。数值例子表明，两种次优集中式算法的性能接近最优集中式更新算法。
In a multisensor target tracking system, observations produced by sensors typically arrive at a central processor out of sequence. There have been some update algorithms for single out-of-sequence measurement (OOSM). In this paper, we consider optimal centralized update algorithms with multiple asynchronous (different lag time) OOSMs. First, we generalize the optimal update algorithm with single one-step-lag OOSM in [Y. Bar-Shalom, ldquoUpdate With Out-of-Sequence Measurements in Tracking: Exact Solution,rdquo IEEE Transactions on Aerospace and Electronic Systems, vol. 38, pp. 769-778, July 2002] to optimal centralized update algorithm with multiple one-step-lag OOSMs. Then, based on best linear unbiased estimation, we present an optimal centralized update algorithm with multiple arbitrary-step-lag OOSMs. Finally, two suboptimal centralized update algorithms are proposed to reduce the computational complexity. A numerical example shows that performances of two suboptimal centralized algorithms are close to that of the optimal centralized update algorithm.