Indoor Mobile Localization in Wireless Sensor Network under Unknown NLOS Errors
Localization is one of the key techniques in wireless sensor network. One of the main problems in indoor mobile localization is non-line-of-sight (NLOS) propagation. And the NLOS effects will lead to a large localization error. So the NLOS problem is the biggest challenge for accurate mobile locatio...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi - SAGE Publishing
2013-02-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2013/208904 |
| _version_ | 1797719539736117248 |
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| author | Long Cheng Hao Wu Chengdong Wu Yunzhou Zhang |
| author_facet | Long Cheng Hao Wu Chengdong Wu Yunzhou Zhang |
| author_sort | Long Cheng |
| collection | DOAJ |
| description | Localization is one of the key techniques in wireless sensor network. One of the main problems in indoor mobile localization is non-line-of-sight (NLOS) propagation. And the NLOS effects will lead to a large localization error. So the NLOS problem is the biggest challenge for accurate mobile location estimation in WSN. In this paper, we propose a likelihood matrix correction based mixed Kalman and H -infinity filter (LC-MKHF) method. A likelihood matrix based correction method is firstly proposed to correct the LOS and NLOS measurements. This method does not need the prior information about the statistical properties of the NLOS errors. So it is independent of the physical measurement ways. And then a mixed Kalman and H -infinity filter method is proposed to improve the range measurement. Simulation results show that the LC-MKHF algorithm has higher estimate accuracy in comparison with no-filter, Kalman filter, and H -infinity filter methods. And it is robust to the NLOS errors. |
| first_indexed | 2024-03-12T09:06:17Z |
| format | Article |
| id | doaj.art-f9edfa2e6a2949d19e5d2dd0dfaca8b3 |
| institution | Directory Open Access Journal |
| issn | 1550-1477 |
| language | English |
| last_indexed | 2024-03-12T09:06:17Z |
| publishDate | 2013-02-01 |
| publisher | Hindawi - SAGE Publishing |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj.art-f9edfa2e6a2949d19e5d2dd0dfaca8b32023-09-02T15:18:12ZengHindawi - SAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772013-02-01910.1155/2013/208904Indoor Mobile Localization in Wireless Sensor Network under Unknown NLOS ErrorsLong Cheng0Hao Wu1Chengdong Wu2Yunzhou Zhang3 College of Information Science and Engineering, Northeastern University, Shenyang 110819, China Faculty of Engineering & Information Technologies, University of Sydney, NSW 2006, Australia College of Information Science and Engineering, Northeastern University, Shenyang 110819, China College of Information Science and Engineering, Northeastern University, Shenyang 110819, ChinaLocalization is one of the key techniques in wireless sensor network. One of the main problems in indoor mobile localization is non-line-of-sight (NLOS) propagation. And the NLOS effects will lead to a large localization error. So the NLOS problem is the biggest challenge for accurate mobile location estimation in WSN. In this paper, we propose a likelihood matrix correction based mixed Kalman and H -infinity filter (LC-MKHF) method. A likelihood matrix based correction method is firstly proposed to correct the LOS and NLOS measurements. This method does not need the prior information about the statistical properties of the NLOS errors. So it is independent of the physical measurement ways. And then a mixed Kalman and H -infinity filter method is proposed to improve the range measurement. Simulation results show that the LC-MKHF algorithm has higher estimate accuracy in comparison with no-filter, Kalman filter, and H -infinity filter methods. And it is robust to the NLOS errors.https://doi.org/10.1155/2013/208904 |
| spellingShingle | Long Cheng Hao Wu Chengdong Wu Yunzhou Zhang Indoor Mobile Localization in Wireless Sensor Network under Unknown NLOS Errors International Journal of Distributed Sensor Networks |
| title | Indoor Mobile Localization in Wireless Sensor Network under Unknown NLOS Errors |
| title_full | Indoor Mobile Localization in Wireless Sensor Network under Unknown NLOS Errors |
| title_fullStr | Indoor Mobile Localization in Wireless Sensor Network under Unknown NLOS Errors |
| title_full_unstemmed | Indoor Mobile Localization in Wireless Sensor Network under Unknown NLOS Errors |
| title_short | Indoor Mobile Localization in Wireless Sensor Network under Unknown NLOS Errors |
| title_sort | indoor mobile localization in wireless sensor network under unknown nlos errors |
| url | https://doi.org/10.1155/2013/208904 |
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