Optimal unbiased linear sensor fusion over multiple lossy channels with collective observability

In this paper, we consider optimal linear sensor fusion for obtaining a remote state estimate of a linear process based on the sensor data transmitted over lossy channels. There is no local observability guarantee for any of the sensors. It is assumed that the state of the linear process is collecti...

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Main Authors: Wu, Yuchi, Ding, Kemi, Li, Yuzhe, Shi, Ling
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2022
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Online Access:https://hdl.handle.net/10356/159376
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1593762022-06-16T05:31:00Z Optimal unbiased linear sensor fusion over multiple lossy channels with collective observability Wu, Yuchi Ding, Kemi Li, Yuzhe Shi, Ling School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering State Estimation Kalman Filter In this paper, we consider optimal linear sensor fusion for obtaining a remote state estimate of a linear process based on the sensor data transmitted over lossy channels. There is no local observability guarantee for any of the sensors. It is assumed that the state of the linear process is collectively observable. We transform the problem of finding the optimal linear sensor fusion coefficients as a convex optimization problem which can be efficiently solved. Moreover, the closed-form expression is also derived for the optimal coefficients. Simulation results are presented to illustrate the performance of the developed algorithm. The work by Y. Wu and L. Shi is supported by a Hong Kong RGC General Research Fund, Hong Kong Special Administrative Region 16204218. The work of Y. Li was supported by National Natural Science Foundation of China, China (61890924, 61991404), and Liao Ning Revitalization Talents Program (XLYC1907087). 2022-06-16T05:31:00Z 2022-06-16T05:31:00Z 2021 Journal Article Wu, Y., Ding, K., Li, Y. & Shi, L. (2021). Optimal unbiased linear sensor fusion over multiple lossy channels with collective observability. Automatica, 128, 109568-. https://dx.doi.org/10.1016/j.automatica.2021.109568 0005-1098 https://hdl.handle.net/10356/159376 10.1016/j.automatica.2021.109568 2-s2.0-85103288333 128 109568 en Automatica © 2021 Elsevier Ltd. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
State Estimation
Kalman Filter
spellingShingle Engineering::Electrical and electronic engineering
State Estimation
Kalman Filter
Wu, Yuchi
Ding, Kemi
Li, Yuzhe
Shi, Ling
Optimal unbiased linear sensor fusion over multiple lossy channels with collective observability
description In this paper, we consider optimal linear sensor fusion for obtaining a remote state estimate of a linear process based on the sensor data transmitted over lossy channels. There is no local observability guarantee for any of the sensors. It is assumed that the state of the linear process is collectively observable. We transform the problem of finding the optimal linear sensor fusion coefficients as a convex optimization problem which can be efficiently solved. Moreover, the closed-form expression is also derived for the optimal coefficients. Simulation results are presented to illustrate the performance of the developed algorithm.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Wu, Yuchi
Ding, Kemi
Li, Yuzhe
Shi, Ling
format Article
author Wu, Yuchi
Ding, Kemi
Li, Yuzhe
Shi, Ling
author_sort Wu, Yuchi
title Optimal unbiased linear sensor fusion over multiple lossy channels with collective observability
title_short Optimal unbiased linear sensor fusion over multiple lossy channels with collective observability
title_full Optimal unbiased linear sensor fusion over multiple lossy channels with collective observability
title_fullStr Optimal unbiased linear sensor fusion over multiple lossy channels with collective observability
title_full_unstemmed Optimal unbiased linear sensor fusion over multiple lossy channels with collective observability
title_sort optimal unbiased linear sensor fusion over multiple lossy channels with collective observability
publishDate 2022
url https://hdl.handle.net/10356/159376
_version_ 1736856365380403200