NLOS Identification and Positioning Algorithm Based on Localization Residual in Wireless Sensor Networks
The problem of target localization in WSN (wireless sensor network) has received much attention in recent years. However, the performance of traditional localization algorithms will drastically degrade in the non-line of sight (NLOS) environment. Moreover, variable methods have been presented to add...
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| Format: | Article |
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MDPI AG
2018-09-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/18/9/2991 |
| _version_ | 1817992565640658944 |
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| author | Jingyu Hua Yejia Yin Weidang Lu Yu Zhang Feng Li |
| author_facet | Jingyu Hua Yejia Yin Weidang Lu Yu Zhang Feng Li |
| author_sort | Jingyu Hua |
| collection | DOAJ |
| description | The problem of target localization in WSN (wireless sensor network) has received much attention in recent years. However, the performance of traditional localization algorithms will drastically degrade in the non-line of sight (NLOS) environment. Moreover, variable methods have been presented to address this issue, such as the optimization-based method and the NLOS modeling method. The former produces a higher complexity and the latter is sensitive to the propagating environment. Therefore, this paper puts forward a simple NLOS identification and localization algorithm based on the residual analysis, where at least two line-of-sight (LOS) propagating anchor nodes (AN) are required. First, all ANs are grouped into several subgroups, and each subgroup can get intermediate position estimates of target node through traditional localization algorithms. Then, the AN with an NLOS propagation, namely NLOS-AN, can be identified by the threshold based hypothesis test, where the test variable, i.e., the localization residual, is computed according to the intermediate position estimations. Finally, the position of target node can be estimated by only using ANs under line of sight (LOS) propagations. Simulation results show that the proposed algorithm can successfully identify the NLOS-AN, by which the following localization produces high accuracy so long as there are no less than two LOS-ANs. |
| first_indexed | 2024-04-14T01:28:26Z |
| format | Article |
| id | doaj.art-ac8febc9ee8d4a3292c7e75a17ccea94 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T01:28:26Z |
| publishDate | 2018-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-ac8febc9ee8d4a3292c7e75a17ccea942022-12-22T02:20:19ZengMDPI AGSensors1424-82202018-09-01189299110.3390/s18092991s18092991NLOS Identification and Positioning Algorithm Based on Localization Residual in Wireless Sensor NetworksJingyu Hua0Yejia Yin1Weidang Lu2Yu Zhang3Feng Li4Department of Electronic Engineering, Zhejiang Gongshang University, Hangzhou 310018, ChinaDepartment of Communication Engineering, Zhejiang University of Technology, Hangzhou 310023, ChinaDepartment of Communication Engineering, Zhejiang University of Technology, Hangzhou 310023, ChinaDepartment of Communication Engineering, Zhejiang University of Technology, Hangzhou 310023, ChinaDepartment of Communication Engineering, Zhejiang University of Technology, Hangzhou 310023, ChinaThe problem of target localization in WSN (wireless sensor network) has received much attention in recent years. However, the performance of traditional localization algorithms will drastically degrade in the non-line of sight (NLOS) environment. Moreover, variable methods have been presented to address this issue, such as the optimization-based method and the NLOS modeling method. The former produces a higher complexity and the latter is sensitive to the propagating environment. Therefore, this paper puts forward a simple NLOS identification and localization algorithm based on the residual analysis, where at least two line-of-sight (LOS) propagating anchor nodes (AN) are required. First, all ANs are grouped into several subgroups, and each subgroup can get intermediate position estimates of target node through traditional localization algorithms. Then, the AN with an NLOS propagation, namely NLOS-AN, can be identified by the threshold based hypothesis test, where the test variable, i.e., the localization residual, is computed according to the intermediate position estimations. Finally, the position of target node can be estimated by only using ANs under line of sight (LOS) propagations. Simulation results show that the proposed algorithm can successfully identify the NLOS-AN, by which the following localization produces high accuracy so long as there are no less than two LOS-ANs.http://www.mdpi.com/1424-8220/18/9/2991wireless localizationnon-line-of-sight errorlocalization residualwireless sensor network |
| spellingShingle | Jingyu Hua Yejia Yin Weidang Lu Yu Zhang Feng Li NLOS Identification and Positioning Algorithm Based on Localization Residual in Wireless Sensor Networks Sensors wireless localization non-line-of-sight error localization residual wireless sensor network |
| title | NLOS Identification and Positioning Algorithm Based on Localization Residual in Wireless Sensor Networks |
| title_full | NLOS Identification and Positioning Algorithm Based on Localization Residual in Wireless Sensor Networks |
| title_fullStr | NLOS Identification and Positioning Algorithm Based on Localization Residual in Wireless Sensor Networks |
| title_full_unstemmed | NLOS Identification and Positioning Algorithm Based on Localization Residual in Wireless Sensor Networks |
| title_short | NLOS Identification and Positioning Algorithm Based on Localization Residual in Wireless Sensor Networks |
| title_sort | nlos identification and positioning algorithm based on localization residual in wireless sensor networks |
| topic | wireless localization non-line-of-sight error localization residual wireless sensor network |
| url | http://www.mdpi.com/1424-8220/18/9/2991 |
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