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Optimal Centralized Update With Multiple Local Out-of-Sequence Measurements

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4 Author(s)
Xiaojing Shen ; Dept. of Math., Sichuan Univ., Chengdu ; Yunmin Zhu ; Enbin Song ; Yingting Luo

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.

Published in:

Signal Processing, IEEE Transactions on  (Volume:57 ,  Issue: 4 )

Date of Publication:

April 2009

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