Distributed Multi-Antenna Positioning for Automatic-Guided Vehicle
Radio-based positioning systems are typically utilized to provide high-precision position information for automatic-guided vehicles (AGVs). However, the presence of obstacles in harsh environments, as well as carried cargoes on the AGV, will degrade the localization performance, since they block the...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-02-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/20/4/1155 |
| _version_ | 1828363806304108544 |
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| author | Xinyuan An Sihao Zhao Xiaowei Cui Qin Shi Mingquan Lu |
| author_facet | Xinyuan An Sihao Zhao Xiaowei Cui Qin Shi Mingquan Lu |
| author_sort | Xinyuan An |
| collection | DOAJ |
| description | Radio-based positioning systems are typically utilized to provide high-precision position information for automatic-guided vehicles (AGVs). However, the presence of obstacles in harsh environments, as well as carried cargoes on the AGV, will degrade the localization performance, since they block the propagation of radio signals. In this paper, a distributed multi-antenna positioning system is proposed, where multiple synchronous antennas are equipped on corners of an AGV to improve the availability and accuracy of positioning. An estimator based on the Levenberg−Marquardt algorithm is introduced to solve the nonlinear pseudo-range equations. To obtain the global optimal solutions, we propose a coarse estimator that utilizes the displacement knowledge of the antennas to provide a rough initial guess. Simulation results show a better availability of our system compared with the single antenna positioning system. Decimeter accuracy can be obtained under a Gaussian measurement noise with a standard deviation of 0.2 m. The results also demonstrate that the proposed algorithm can achieve positioning accuracy close to the theoretical Cramer−Rao lower bound. Furthermore, given prior information of the yaw angle, the same level of accuracy can be obtained by the proposed algorithm without the coarse estimation step. |
| first_indexed | 2024-04-14T05:06:02Z |
| format | Article |
| id | doaj.art-000fefa29eb6495794c1d1cd85b562aa |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T05:06:02Z |
| publishDate | 2020-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-000fefa29eb6495794c1d1cd85b562aa2022-12-22T02:10:41ZengMDPI AGSensors1424-82202020-02-01204115510.3390/s20041155s20041155Distributed Multi-Antenna Positioning for Automatic-Guided VehicleXinyuan An0Sihao Zhao1Xiaowei Cui2Qin Shi3Mingquan Lu4Department of Electronic Engineering, Tsinghua University, Beijing 100084, ChinaDepartment of Electronic Engineering, Tsinghua University, Beijing 100084, ChinaDepartment of Electronic Engineering, Tsinghua University, Beijing 100084, ChinaDepartment of Electronic Engineering, Tsinghua University, Beijing 100084, ChinaDepartment of Electronic Engineering, Tsinghua University, Beijing 100084, ChinaRadio-based positioning systems are typically utilized to provide high-precision position information for automatic-guided vehicles (AGVs). However, the presence of obstacles in harsh environments, as well as carried cargoes on the AGV, will degrade the localization performance, since they block the propagation of radio signals. In this paper, a distributed multi-antenna positioning system is proposed, where multiple synchronous antennas are equipped on corners of an AGV to improve the availability and accuracy of positioning. An estimator based on the Levenberg−Marquardt algorithm is introduced to solve the nonlinear pseudo-range equations. To obtain the global optimal solutions, we propose a coarse estimator that utilizes the displacement knowledge of the antennas to provide a rough initial guess. Simulation results show a better availability of our system compared with the single antenna positioning system. Decimeter accuracy can be obtained under a Gaussian measurement noise with a standard deviation of 0.2 m. The results also demonstrate that the proposed algorithm can achieve positioning accuracy close to the theoretical Cramer−Rao lower bound. Furthermore, given prior information of the yaw angle, the same level of accuracy can be obtained by the proposed algorithm without the coarse estimation step.https://www.mdpi.com/1424-8220/20/4/1155automatic-guided vehiclesdistributed multi-antenna positioninglevenberg–marquardt |
| spellingShingle | Xinyuan An Sihao Zhao Xiaowei Cui Qin Shi Mingquan Lu Distributed Multi-Antenna Positioning for Automatic-Guided Vehicle Sensors automatic-guided vehicles distributed multi-antenna positioning levenberg–marquardt |
| title | Distributed Multi-Antenna Positioning for Automatic-Guided Vehicle |
| title_full | Distributed Multi-Antenna Positioning for Automatic-Guided Vehicle |
| title_fullStr | Distributed Multi-Antenna Positioning for Automatic-Guided Vehicle |
| title_full_unstemmed | Distributed Multi-Antenna Positioning for Automatic-Guided Vehicle |
| title_short | Distributed Multi-Antenna Positioning for Automatic-Guided Vehicle |
| title_sort | distributed multi antenna positioning for automatic guided vehicle |
| topic | automatic-guided vehicles distributed multi-antenna positioning levenberg–marquardt |
| url | https://www.mdpi.com/1424-8220/20/4/1155 |
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