SLAM Using Cellular Multipath Component Delays and Angular Information with JPDA Approximation
(2023) 2023 8th International Conference on Signal and Image Processing p.973-978- Abstract
- Advanced cellular communication systems provide increased potential for opportunistic high-accuracy positioning. In this paper, long-term evolution (LTE) downlink signals from two commercial base stations (BS) are received by a massive antenna array mounted on a passenger vehicle. Multipath component (MPC) parameters, like delays and angle-of-arrival (AOA) are extracted from the received signals on a snapshot-by-snapshot basis, and then associated across snapshots with a low complexity joint probability data association approximation algorithm. The associated parameters are used to jointly estimate the positions of the vehicle, the transmitters, and the virtual transmitters (VT) with a simultaneous localization and mapping (SLAM)... (More)
- Advanced cellular communication systems provide increased potential for opportunistic high-accuracy positioning. In this paper, long-term evolution (LTE) downlink signals from two commercial base stations (BS) are received by a massive antenna array mounted on a passenger vehicle. Multipath component (MPC) parameters, like delays and angle-of-arrival (AOA) are extracted from the received signals on a snapshot-by-snapshot basis, and then associated across snapshots with a low complexity joint probability data association approximation algorithm. The associated parameters are used to jointly estimate the positions of the vehicle, the transmitters, and the virtual transmitters (VT) with a simultaneous localization and mapping (SLAM) algorithm. Both reflector and scatterer models are adopted, and clock and angular offsets are taken into account in the algorithm. The measurement results show the effectiveness of the data association algorithm and the accuracy of the SLAM algorithm. The vehicle’s horizontal position error of SLAM fused with proprioception is less than 5.5 meters after a traversed distance of 530 meters, compared to that of the un-aided proprioception which is 15 meters.
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Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/d43d9421-6c51-4f40-9d9e-3240bc3de91f
- author
- Chen, Junshi LU ; Whiton, Russ LU and Tufvesson, Fredrik LU
- organization
- publishing date
- 2023-10-09
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- 2023 8th International Conference on Signal and Image Processing (ICSIP)
- pages
- 6 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 2023 8th International Conference on Signal and Image Processing
- conference dates
- 2023-07-08 - 2023-07-10
- external identifiers
-
- scopus:85174692158
- ISBN
- 979-8-3503-9794-9
- 979-8-3503-9793-2
- 979-8-3503-9792-5
- DOI
- 10.1109/ICSIP57908.2023.10271016
- project
- MIMO-Sensor for Positioning and Autonomous Drive
- language
- English
- LU publication?
- yes
- id
- d43d9421-6c51-4f40-9d9e-3240bc3de91f
- date added to LUP
- 2023-10-10 09:39:19
- date last changed
- 2024-04-19 02:11:32
@inproceedings{d43d9421-6c51-4f40-9d9e-3240bc3de91f, abstract = {{Advanced cellular communication systems provide increased potential for opportunistic high-accuracy positioning. In this paper, long-term evolution (LTE) downlink signals from two commercial base stations (BS) are received by a massive antenna array mounted on a passenger vehicle. Multipath component (MPC) parameters, like delays and angle-of-arrival (AOA) are extracted from the received signals on a snapshot-by-snapshot basis, and then associated across snapshots with a low complexity joint probability data association approximation algorithm. The associated parameters are used to jointly estimate the positions of the vehicle, the transmitters, and the virtual transmitters (VT) with a simultaneous localization and mapping (SLAM) algorithm. Both reflector and scatterer models are adopted, and clock and angular offsets are taken into account in the algorithm. The measurement results show the effectiveness of the data association algorithm and the accuracy of the SLAM algorithm. The vehicle’s horizontal position error of SLAM fused with proprioception is less than 5.5 meters after a traversed distance of 530 meters, compared to that of the un-aided proprioception which is 15 meters.<br/>}}, author = {{Chen, Junshi and Whiton, Russ and Tufvesson, Fredrik}}, booktitle = {{2023 8th International Conference on Signal and Image Processing (ICSIP)}}, isbn = {{979-8-3503-9794-9}}, language = {{eng}}, month = {{10}}, pages = {{973--978}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{SLAM Using Cellular Multipath Component Delays and Angular Information with JPDA Approximation}}, url = {{https://lup.lub.lu.se/search/files/161189959/SLAM_Using_Cellular_Multipath_Component_Delays_and_Angular_Information_with_JPDA_Approximation.pdf}}, doi = {{10.1109/ICSIP57908.2023.10271016}}, year = {{2023}}, }