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Electrical Engineering and Systems Science > Systems and Control

arXiv:2101.10689 (eess)
[Submitted on 26 Jan 2021 (v1), last revised 21 Apr 2022 (this version, v4)]

Title:A Distributed Implementation of Steady-State Kalman Filter

Authors:Jiaqi Yan, Xu Yang, Yilin Mo, Keyou You
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Abstract:This paper studies the distributed state estimation in sensor network, where $m$ sensors are deployed to infer the $n$-dimensional state of a linear time-invariant (LTI) Gaussian system. By a lossless decomposition of optimal steady-state Kalman filter, we show that the problem of distributed estimation can be reformulated as synchronization of homogeneous linear systems. Based on such decomposition, a distributed estimator is proposed, where each sensor node runs a local filter using only its own measurement and fuses the local estimate of each node with a consensus algorithm. We show that the average of the estimate from all sensors coincides with the optimal Kalman estimate. Numerical examples are provided in the end to illustrate the performance of the proposed scheme.
Subjects: Systems and Control (eess.SY)
Cite as: arXiv:2101.10689 [eess.SY]
  (or arXiv:2101.10689v4 [eess.SY] for this version)
  https://doi.org/10.48550/arXiv.2101.10689

Submission history

From: Xu Yang [view email]
[v1] Tue, 26 Jan 2021 10:31:59 UTC (18 KB)
[v2] Wed, 17 Mar 2021 05:53:32 UTC (86 KB)
[v3] Wed, 19 Jan 2022 03:44:23 UTC (349 KB)
[v4] Thu, 21 Apr 2022 13:15:55 UTC (383 KB)
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