Angle Residual Based NLOS Suppression and Localization Method in Wireless Sensor Networks
With the rapid development of Internet of Things (IOT) applications, the performance of existing wireless localization methods under non-line-of-sight (NLOS) transmission environments is seriously challenged. Therefore, this paper proposes a new definition of residual, i.e., the angle residual. The...
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| Veröffentlicht in: | IEEE sensors journal 2023-07, Vol.23 (13), p.1-1 |
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| creator | Wang, Jiale Wen, Jiangang Hua, Jingyu Feng, Xiaofei Xu, Zhijiang Ni, Zhengwei |
| description | With the rapid development of Internet of Things (IOT) applications, the performance of existing wireless localization methods under non-line-of-sight (NLOS) transmission environments is seriously challenged. Therefore, this paper proposes a new definition of residual, i.e., the angle residual. The key target of angle residual is to detect line-of-sight (LOS) links from measured and calculated angle parameters. The target position is then estimated by two-step weighted least squares (TS-WLS) algorithm, where only positioning parameters of LOS link are included. Simulation shows that the proposed algorithm performs better than traditional algorithms, especially when the mobile node (MN) position and the NLOS link distribution are randomly generated. Therefore, the proposed method effectively improves the positioning performance and enhances the localization stability in real NLOS transmission environments. |
| doi_str_mv | 10.1109/JSEN.2023.3275627 |
| format | Article |
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Therefore, this paper proposes a new definition of residual, i.e., the angle residual. The key target of angle residual is to detect line-of-sight (LOS) links from measured and calculated angle parameters. The target position is then estimated by two-step weighted least squares (TS-WLS) algorithm, where only positioning parameters of LOS link are included. Simulation shows that the proposed algorithm performs better than traditional algorithms, especially when the mobile node (MN) position and the NLOS link distribution are randomly generated. 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Therefore, this paper proposes a new definition of residual, i.e., the angle residual. The key target of angle residual is to detect line-of-sight (LOS) links from measured and calculated angle parameters. The target position is then estimated by two-step weighted least squares (TS-WLS) algorithm, where only positioning parameters of LOS link are included. Simulation shows that the proposed algorithm performs better than traditional algorithms, especially when the mobile node (MN) position and the NLOS link distribution are randomly generated. 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| subjects | Algorithms Angle residual Internet of Things Line of sight Localization method Location awareness Manganese Measurement uncertainty Noise measurement Non-line of sight error Parameters Position measurement Topology Wireless communication Wireless localization Wireless Network Wireless Sensor Network Wireless sensor networks |
| title | Angle Residual Based NLOS Suppression and Localization Method in Wireless Sensor Networks |
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