A Minimax Unbiased Estimation Fusion in Distributed Multisensor Localization and Tracking
A minimax estimation fusion in distributed multisensor systems is proposed, which aims to minimize the worst-case squared estimation error when the cross-covariances between local sensors are unknown and the normalized estimation errors of local sensors are norm bounded. The proposed estimation fusi...
Main Authors: | , |
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Format: | Article |
Language: | English |
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Hindawi - SAGE Publishing
2012-12-01
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Series: | International Journal of Distributed Sensor Networks |
Online Access: | https://doi.org/10.1155/2012/294578 |
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author | Xiaomei Qu Jie Zhou |
author_facet | Xiaomei Qu Jie Zhou |
author_sort | Xiaomei Qu |
collection | DOAJ |
description | A minimax estimation fusion in distributed multisensor systems is proposed, which aims to minimize the worst-case squared estimation error when the cross-covariances between local sensors are unknown and the normalized estimation errors of local sensors are norm bounded. The proposed estimation fusion is called as the Chebyshev fusion estimation (CFE) because its geometrical interpretation is in coincidence with the Chebyshev center, which is a nonlinear combination of local estimates. Theoretically, the CFE is better than any local estimator in the sense of the worst-case squared estimation error and is robust to the choice of the supporting bound. The simulation results illustrate that the proposed CFE is a robust fusion in localization and tracking and more accurate than the previous covariance intersection (CI) method. |
first_indexed | 2024-03-12T20:25:52Z |
format | Article |
id | doaj.art-eaedbc51051a4c82922bac6030c6f3ed |
institution | Directory Open Access Journal |
issn | 1550-1477 |
language | English |
last_indexed | 2024-03-12T20:25:52Z |
publishDate | 2012-12-01 |
publisher | Hindawi - SAGE Publishing |
record_format | Article |
series | International Journal of Distributed Sensor Networks |
spelling | doaj.art-eaedbc51051a4c82922bac6030c6f3ed2023-08-02T00:33:29ZengHindawi - SAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772012-12-01810.1155/2012/294578A Minimax Unbiased Estimation Fusion in Distributed Multisensor Localization and TrackingXiaomei Qu0Jie Zhou1 College of Computer Science and Technology, Southwest University for Nationalities, Chengdu, Sichuan 610041, China College of Mathematics, Sichuan University, Chengdu, Sichuan 610064, ChinaA minimax estimation fusion in distributed multisensor systems is proposed, which aims to minimize the worst-case squared estimation error when the cross-covariances between local sensors are unknown and the normalized estimation errors of local sensors are norm bounded. The proposed estimation fusion is called as the Chebyshev fusion estimation (CFE) because its geometrical interpretation is in coincidence with the Chebyshev center, which is a nonlinear combination of local estimates. Theoretically, the CFE is better than any local estimator in the sense of the worst-case squared estimation error and is robust to the choice of the supporting bound. The simulation results illustrate that the proposed CFE is a robust fusion in localization and tracking and more accurate than the previous covariance intersection (CI) method.https://doi.org/10.1155/2012/294578 |
spellingShingle | Xiaomei Qu Jie Zhou A Minimax Unbiased Estimation Fusion in Distributed Multisensor Localization and Tracking International Journal of Distributed Sensor Networks |
title | A Minimax Unbiased Estimation Fusion in Distributed Multisensor Localization and Tracking |
title_full | A Minimax Unbiased Estimation Fusion in Distributed Multisensor Localization and Tracking |
title_fullStr | A Minimax Unbiased Estimation Fusion in Distributed Multisensor Localization and Tracking |
title_full_unstemmed | A Minimax Unbiased Estimation Fusion in Distributed Multisensor Localization and Tracking |
title_short | A Minimax Unbiased Estimation Fusion in Distributed Multisensor Localization and Tracking |
title_sort | minimax unbiased estimation fusion in distributed multisensor localization and tracking |
url | https://doi.org/10.1155/2012/294578 |
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