TDOA-Based Source Collaborative Localization via Semidefinite Relaxation in Sensor Networks
The time delay of arrival- (TDOA-) based source localization using a wireless sensor network has been considered in this paper. The maximum likelihood estimate (MLE) is formulated by taking the correlated TDOA noise into account, which is caused by the difference with the TOA of the reference sensor...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2015-09-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2015/248970 |
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| _version_ | 1850166074803224576 |
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| author | Yongsheng Yan Haiyan Wang Xiaohong Shen Ke He Xionghu Zhong |
| author_facet | Yongsheng Yan Haiyan Wang Xiaohong Shen Ke He Xionghu Zhong |
| author_sort | Yongsheng Yan |
| collection | DOAJ |
| description | The time delay of arrival- (TDOA-) based source localization using a wireless sensor network has been considered in this paper. The maximum likelihood estimate (MLE) is formulated by taking the correlated TDOA noise into account, which is caused by the difference with the TOA of the reference sensor. The global optimal solution is difficult to obtain due to the nonconvex nature of the ML function. We propose an alternative semidefinite programming method, which transforms the original ML problem into a convex one by relaxing nonconvex equalities into convex matrix inequalities. In addition, the source localization algorithm in the presence of sensor location errors and non-line-of-sight (NLOS) observations is developed. Our simulation results demonstrate the potential advantages of the proposed method. Furthermore, the proposed source localization algorithm by taking the NLOS TOA measurements as the constraints of the convex problem can provide a good estimate. |
| format | Article |
| id | doaj-art-e41dd7b68e304d2fb58458ca9f227f32 |
| institution | OA Journals |
| issn | 1550-1477 |
| language | English |
| publishDate | 2015-09-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-e41dd7b68e304d2fb58458ca9f227f322025-08-20T02:21:34ZengWileyInternational Journal of Distributed Sensor Networks1550-14772015-09-011110.1155/2015/248970248970TDOA-Based Source Collaborative Localization via Semidefinite Relaxation in Sensor NetworksYongsheng Yan0Haiyan Wang1Xiaohong Shen2Ke He3Xionghu Zhong4 School of Marine Science and Technology, Northwestern Polytechnical University, 127 Youyi West Road, Xi'an, Shaanxi 710072, China School of Marine Science and Technology, Northwestern Polytechnical University, 127 Youyi West Road, Xi'an, Shaanxi 710072, China School of Marine Science and Technology, Northwestern Polytechnical University, 127 Youyi West Road, Xi'an, Shaanxi 710072, China School of Marine Science and Technology, Northwestern Polytechnical University, 127 Youyi West Road, Xi'an, Shaanxi 710072, China School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798The time delay of arrival- (TDOA-) based source localization using a wireless sensor network has been considered in this paper. The maximum likelihood estimate (MLE) is formulated by taking the correlated TDOA noise into account, which is caused by the difference with the TOA of the reference sensor. The global optimal solution is difficult to obtain due to the nonconvex nature of the ML function. We propose an alternative semidefinite programming method, which transforms the original ML problem into a convex one by relaxing nonconvex equalities into convex matrix inequalities. In addition, the source localization algorithm in the presence of sensor location errors and non-line-of-sight (NLOS) observations is developed. Our simulation results demonstrate the potential advantages of the proposed method. Furthermore, the proposed source localization algorithm by taking the NLOS TOA measurements as the constraints of the convex problem can provide a good estimate.https://doi.org/10.1155/2015/248970 |
| spellingShingle | Yongsheng Yan Haiyan Wang Xiaohong Shen Ke He Xionghu Zhong TDOA-Based Source Collaborative Localization via Semidefinite Relaxation in Sensor Networks International Journal of Distributed Sensor Networks |
| title | TDOA-Based Source Collaborative Localization via Semidefinite Relaxation in Sensor Networks |
| title_full | TDOA-Based Source Collaborative Localization via Semidefinite Relaxation in Sensor Networks |
| title_fullStr | TDOA-Based Source Collaborative Localization via Semidefinite Relaxation in Sensor Networks |
| title_full_unstemmed | TDOA-Based Source Collaborative Localization via Semidefinite Relaxation in Sensor Networks |
| title_short | TDOA-Based Source Collaborative Localization via Semidefinite Relaxation in Sensor Networks |
| title_sort | tdoa based source collaborative localization via semidefinite relaxation in sensor networks |
| url | https://doi.org/10.1155/2015/248970 |
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