Consensus Target Tracking in Switching Wireless Sensor Networks with Outliers
The problem of consensus-based distributed tracking in wireless sensor networks (WSNs) with switching network topologies and outlier-corrupted sensor observations is considered. First, to attack the outlier-corrupted measurements, a robust Kalman filtering (RKF) scheme with weighted matrices on inno...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-04-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2014/216063 |
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| _version_ | 1850166094151548928 |
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| author | Yan Zhou Dongli Wang Yonghong Lan Qingzhen Wen |
| author_facet | Yan Zhou Dongli Wang Yonghong Lan Qingzhen Wen |
| author_sort | Yan Zhou |
| collection | DOAJ |
| description | The problem of consensus-based distributed tracking in wireless sensor networks (WSNs) with switching network topologies and outlier-corrupted sensor observations is considered. First, to attack the outlier-corrupted measurements, a robust Kalman filtering (RKF) scheme with weighted matrices on innovation sequences is introduced. The proposed RKF possesses high robustness against outliers while having similar computational burden as traditional Kalman filter. Then, each node estimates the network-wide agreement on target state using only communications between one-hop neighbors. In order to improve the convergent speed of the consensus filter in case of switching topologies, an adaptive weight update strategy is proposed. Note that the proposed algorithm relaxes the requirement of Gaussian noise statistics in contrast to the decentralized/distributed Kalman filters. Besides, unlike the existing consensus-based filters, we do not need to perform consensus filtering on the covariance matrices, which will reduce the computational and communicational burden abundantly. Finally, simulation examples are included to demonstrate the robustness of the proposed RKF and effectiveness of adaptive consensus approach. |
| format | Article |
| id | doaj-art-e452ea19e8a44598abf290116d20bdfb |
| institution | OA Journals |
| issn | 1550-1477 |
| language | English |
| publishDate | 2014-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-e452ea19e8a44598abf290116d20bdfb2025-08-20T02:21:34ZengWileyInternational Journal of Distributed Sensor Networks1550-14772014-04-011010.1155/2014/216063216063Consensus Target Tracking in Switching Wireless Sensor Networks with OutliersYan Zhou0Dongli Wang1Yonghong Lan2Qingzhen Wen3 Key Laboratory of Intelligent Computing & Information Processing of MOE, Xiangtan 411105, China College of Information Engineering, Xiangtan University, Xiangtan 411105, China College of Information Engineering, Xiangtan University, Xiangtan 411105, China College of Information Engineering, Xiangtan University, Xiangtan 411105, ChinaThe problem of consensus-based distributed tracking in wireless sensor networks (WSNs) with switching network topologies and outlier-corrupted sensor observations is considered. First, to attack the outlier-corrupted measurements, a robust Kalman filtering (RKF) scheme with weighted matrices on innovation sequences is introduced. The proposed RKF possesses high robustness against outliers while having similar computational burden as traditional Kalman filter. Then, each node estimates the network-wide agreement on target state using only communications between one-hop neighbors. In order to improve the convergent speed of the consensus filter in case of switching topologies, an adaptive weight update strategy is proposed. Note that the proposed algorithm relaxes the requirement of Gaussian noise statistics in contrast to the decentralized/distributed Kalman filters. Besides, unlike the existing consensus-based filters, we do not need to perform consensus filtering on the covariance matrices, which will reduce the computational and communicational burden abundantly. Finally, simulation examples are included to demonstrate the robustness of the proposed RKF and effectiveness of adaptive consensus approach.https://doi.org/10.1155/2014/216063 |
| spellingShingle | Yan Zhou Dongli Wang Yonghong Lan Qingzhen Wen Consensus Target Tracking in Switching Wireless Sensor Networks with Outliers International Journal of Distributed Sensor Networks |
| title | Consensus Target Tracking in Switching Wireless Sensor Networks with Outliers |
| title_full | Consensus Target Tracking in Switching Wireless Sensor Networks with Outliers |
| title_fullStr | Consensus Target Tracking in Switching Wireless Sensor Networks with Outliers |
| title_full_unstemmed | Consensus Target Tracking in Switching Wireless Sensor Networks with Outliers |
| title_short | Consensus Target Tracking in Switching Wireless Sensor Networks with Outliers |
| title_sort | consensus target tracking in switching wireless sensor networks with outliers |
| url | https://doi.org/10.1155/2014/216063 |
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