Augmented Filtering Based on Information Weighted Consensus Fusion for Simultaneous Localization and Tracking via Wireless Sensor Networks
This paper develops a novel augmented filtering framework based on information weighted consensus fusion, to achieve the simultaneous localization and tracking (SLAT) via wireless sensor networks (WSNs). By integrating augmented transition and observation models, we formulate a dynamical system that...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi - SAGE Publishing
2015-09-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2015/391757 |
| _version_ | 1797728785823432704 |
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| author | Xiangyuan Jiang Baozhou Lu Peng Ren Chunbo Luo Xinheng Wang |
| author_facet | Xiangyuan Jiang Baozhou Lu Peng Ren Chunbo Luo Xinheng Wang |
| author_sort | Xiangyuan Jiang |
| collection | DOAJ |
| description | This paper develops a novel augmented filtering framework based on information weighted consensus fusion, to achieve the simultaneous localization and tracking (SLAT) via wireless sensor networks (WSNs). By integrating augmented transition and observation models, we formulate a dynamical system that encodes both the target moving manners and coarse sensor locations in an augmented state. We then conduct augmented filtering based on augmented extended Kalman filters to estimate the augmented state. We further refine our target estimate according to information weighted consensus filtering which fuses the target information obtained from neighboring sensors. The fused information is fed back as the target estimate to the augmented filter. Our framework is computationally efficient because it only requires neighboring sensor communications. Experiments on SLAT problem validate the effectiveness of the proposed algorithm in terms of tracking accuracy and localization precision in limited ranging conditions. |
| first_indexed | 2024-03-12T11:19:08Z |
| format | Article |
| id | doaj.art-ca2626ab38f24f63bd4463dd15369acc |
| institution | Directory Open Access Journal |
| issn | 1550-1477 |
| language | English |
| last_indexed | 2024-03-12T11:19:08Z |
| publishDate | 2015-09-01 |
| publisher | Hindawi - SAGE Publishing |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj.art-ca2626ab38f24f63bd4463dd15369acc2023-09-02T01:24:38ZengHindawi - SAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772015-09-011110.1155/2015/391757391757Augmented Filtering Based on Information Weighted Consensus Fusion for Simultaneous Localization and Tracking via Wireless Sensor NetworksXiangyuan Jiang0Baozhou Lu1Peng Ren2Chunbo Luo3Xinheng Wang4 China University of Petroleum (East China), Qingdao 266580, China China University of Petroleum (East China), Qingdao 266580, China China University of Petroleum (East China), Qingdao 266580, China University of the West of Scotland, Paisley PA1 2BE, UK University of the West of Scotland, Paisley PA1 2BE, UKThis paper develops a novel augmented filtering framework based on information weighted consensus fusion, to achieve the simultaneous localization and tracking (SLAT) via wireless sensor networks (WSNs). By integrating augmented transition and observation models, we formulate a dynamical system that encodes both the target moving manners and coarse sensor locations in an augmented state. We then conduct augmented filtering based on augmented extended Kalman filters to estimate the augmented state. We further refine our target estimate according to information weighted consensus filtering which fuses the target information obtained from neighboring sensors. The fused information is fed back as the target estimate to the augmented filter. Our framework is computationally efficient because it only requires neighboring sensor communications. Experiments on SLAT problem validate the effectiveness of the proposed algorithm in terms of tracking accuracy and localization precision in limited ranging conditions.https://doi.org/10.1155/2015/391757 |
| spellingShingle | Xiangyuan Jiang Baozhou Lu Peng Ren Chunbo Luo Xinheng Wang Augmented Filtering Based on Information Weighted Consensus Fusion for Simultaneous Localization and Tracking via Wireless Sensor Networks International Journal of Distributed Sensor Networks |
| title | Augmented Filtering Based on Information Weighted Consensus Fusion for Simultaneous Localization and Tracking via Wireless Sensor Networks |
| title_full | Augmented Filtering Based on Information Weighted Consensus Fusion for Simultaneous Localization and Tracking via Wireless Sensor Networks |
| title_fullStr | Augmented Filtering Based on Information Weighted Consensus Fusion for Simultaneous Localization and Tracking via Wireless Sensor Networks |
| title_full_unstemmed | Augmented Filtering Based on Information Weighted Consensus Fusion for Simultaneous Localization and Tracking via Wireless Sensor Networks |
| title_short | Augmented Filtering Based on Information Weighted Consensus Fusion for Simultaneous Localization and Tracking via Wireless Sensor Networks |
| title_sort | augmented filtering based on information weighted consensus fusion for simultaneous localization and tracking via wireless sensor networks |
| url | https://doi.org/10.1155/2015/391757 |
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