Multi-Sensor Consensus Estimation of State, Sensor Biases and Unknown Input
This paper addresses the problem of the joint estimation of system state and generalized sensor bias (GSB) under a common unknown input (UI) in the case of bias evolution in a heterogeneous sensor network. First, the equivalent UI-free GSB dynamic model is derived and the local optimal estimates of...
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MDPI AG
2016-09-01
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Online Access: | http://www.mdpi.com/1424-8220/16/9/1407 |
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author | Jie Zhou Yan Liang Feng Yang Linfeng Xu Quan Pan |
author_facet | Jie Zhou Yan Liang Feng Yang Linfeng Xu Quan Pan |
author_sort | Jie Zhou |
collection | DOAJ |
description | This paper addresses the problem of the joint estimation of system state and generalized sensor bias (GSB) under a common unknown input (UI) in the case of bias evolution in a heterogeneous sensor network. First, the equivalent UI-free GSB dynamic model is derived and the local optimal estimates of system state and sensor bias are obtained in each sensor node; Second, based on the state and bias estimates obtained by each node from its neighbors, the UI is estimated via the least-squares method, and then the state estimates are fused via consensus processing; Finally, the multi-sensor bias estimates are further refined based on the consensus estimate of the UI. A numerical example of distributed multi-sensor target tracking is presented to illustrate the proposed filter. |
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format | Article |
id | doaj.art-43467733e4eb4438af8562fb66802b69 |
institution | Directory Open Access Journal |
issn | 1424-8220 |
language | English |
last_indexed | 2024-04-11T11:01:47Z |
publishDate | 2016-09-01 |
publisher | MDPI AG |
record_format | Article |
series | Sensors |
spelling | doaj.art-43467733e4eb4438af8562fb66802b692022-12-22T04:28:30ZengMDPI AGSensors1424-82202016-09-01169140710.3390/s16091407s16091407Multi-Sensor Consensus Estimation of State, Sensor Biases and Unknown InputJie Zhou0Yan Liang1Feng Yang2Linfeng Xu3Quan Pan4Key Laboratory of Information Fusion Technology, Ministry of Education, School of Automation, Northwestern Polytechnical University, Xi’an 710129, ChinaKey Laboratory of Information Fusion Technology, Ministry of Education, School of Automation, Northwestern Polytechnical University, Xi’an 710129, ChinaKey Laboratory of Information Fusion Technology, Ministry of Education, School of Automation, Northwestern Polytechnical University, Xi’an 710129, ChinaKey Laboratory of Information Fusion Technology, Ministry of Education, School of Automation, Northwestern Polytechnical University, Xi’an 710129, ChinaKey Laboratory of Information Fusion Technology, Ministry of Education, School of Automation, Northwestern Polytechnical University, Xi’an 710129, ChinaThis paper addresses the problem of the joint estimation of system state and generalized sensor bias (GSB) under a common unknown input (UI) in the case of bias evolution in a heterogeneous sensor network. First, the equivalent UI-free GSB dynamic model is derived and the local optimal estimates of system state and sensor bias are obtained in each sensor node; Second, based on the state and bias estimates obtained by each node from its neighbors, the UI is estimated via the least-squares method, and then the state estimates are fused via consensus processing; Finally, the multi-sensor bias estimates are further refined based on the consensus estimate of the UI. A numerical example of distributed multi-sensor target tracking is presented to illustrate the proposed filter.http://www.mdpi.com/1424-8220/16/9/1407bias estimationstate estimationsensor registrationnetwork consensus |
spellingShingle | Jie Zhou Yan Liang Feng Yang Linfeng Xu Quan Pan Multi-Sensor Consensus Estimation of State, Sensor Biases and Unknown Input Sensors bias estimation state estimation sensor registration network consensus |
title | Multi-Sensor Consensus Estimation of State, Sensor Biases and Unknown Input |
title_full | Multi-Sensor Consensus Estimation of State, Sensor Biases and Unknown Input |
title_fullStr | Multi-Sensor Consensus Estimation of State, Sensor Biases and Unknown Input |
title_full_unstemmed | Multi-Sensor Consensus Estimation of State, Sensor Biases and Unknown Input |
title_short | Multi-Sensor Consensus Estimation of State, Sensor Biases and Unknown Input |
title_sort | multi sensor consensus estimation of state sensor biases and unknown input |
topic | bias estimation state estimation sensor registration network consensus |
url | http://www.mdpi.com/1424-8220/16/9/1407 |
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