Cooperative Localization and Time Synchronization Based on M-VMP Method
Localization estimation and clock synchronization are important research directions in the application of wireless sensor networks. Aiming at the problems of low positioning accuracy and slow convergence speed in localization estimation methods based on message passing, this paper proposes a low-com...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-11-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/20/21/6315 |
| _version_ | 1797548781460258816 |
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| author | Zhongliang Deng Shihao Tang Buyun Jia Hanhua Wang Xiwen Deng Xinyu Zheng |
| author_facet | Zhongliang Deng Shihao Tang Buyun Jia Hanhua Wang Xiwen Deng Xinyu Zheng |
| author_sort | Zhongliang Deng |
| collection | DOAJ |
| description | Localization estimation and clock synchronization are important research directions in the application of wireless sensor networks. Aiming at the problems of low positioning accuracy and slow convergence speed in localization estimation methods based on message passing, this paper proposes a low-complexity distributed cooperative joint estimation method suitable for dynamic networks called multi-Gaussian variational message passing (M-VMP). The proposed method constrains the message to be a multi-Gaussian function superposition form to reduce the information loss in the variational message passing algorithm (VMP). Only the mean, covariance and weight of each message need to be transmitted in the network, which reduces the computational complexity while ensuring the information completeness. The simulation results show that the proposed method is superior to the VMP algorithm in terms of position accuracy and convergence speed and is close to the sum-product algorithm over a wireless network (SPAWN) based on non-parametric belief propagation, but the computational complexity and communication load are significantly reduced. |
| first_indexed | 2024-03-10T15:04:36Z |
| format | Article |
| id | doaj.art-eea258385b424bfa8d99b85b102fd533 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T15:04:36Z |
| publishDate | 2020-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-eea258385b424bfa8d99b85b102fd5332023-11-20T19:55:35ZengMDPI AGSensors1424-82202020-11-012021631510.3390/s20216315Cooperative Localization and Time Synchronization Based on M-VMP MethodZhongliang Deng0Shihao Tang1Buyun Jia2Hanhua Wang3Xiwen Deng4Xinyu Zheng5School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaSchool of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaSchool of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaSchool of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaSchool of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaSchool of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, ChinaLocalization estimation and clock synchronization are important research directions in the application of wireless sensor networks. Aiming at the problems of low positioning accuracy and slow convergence speed in localization estimation methods based on message passing, this paper proposes a low-complexity distributed cooperative joint estimation method suitable for dynamic networks called multi-Gaussian variational message passing (M-VMP). The proposed method constrains the message to be a multi-Gaussian function superposition form to reduce the information loss in the variational message passing algorithm (VMP). Only the mean, covariance and weight of each message need to be transmitted in the network, which reduces the computational complexity while ensuring the information completeness. The simulation results show that the proposed method is superior to the VMP algorithm in terms of position accuracy and convergence speed and is close to the sum-product algorithm over a wireless network (SPAWN) based on non-parametric belief propagation, but the computational complexity and communication load are significantly reduced.https://www.mdpi.com/1424-8220/20/21/6315multi-variational message passing (M-VMP)factor graph (FG)second-order Taylor expansioncooperative localizationjoint estimation of position and clock |
| spellingShingle | Zhongliang Deng Shihao Tang Buyun Jia Hanhua Wang Xiwen Deng Xinyu Zheng Cooperative Localization and Time Synchronization Based on M-VMP Method Sensors multi-variational message passing (M-VMP) factor graph (FG) second-order Taylor expansion cooperative localization joint estimation of position and clock |
| title | Cooperative Localization and Time Synchronization Based on M-VMP Method |
| title_full | Cooperative Localization and Time Synchronization Based on M-VMP Method |
| title_fullStr | Cooperative Localization and Time Synchronization Based on M-VMP Method |
| title_full_unstemmed | Cooperative Localization and Time Synchronization Based on M-VMP Method |
| title_short | Cooperative Localization and Time Synchronization Based on M-VMP Method |
| title_sort | cooperative localization and time synchronization based on m vmp method |
| topic | multi-variational message passing (M-VMP) factor graph (FG) second-order Taylor expansion cooperative localization joint estimation of position and clock |
| url | https://www.mdpi.com/1424-8220/20/21/6315 |
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