Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/92735
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Aeronautical and Aviation Engineering | en_US |
dc.creator | Zhang, G | en_US |
dc.creator | Ng, HF | en_US |
dc.creator | Wen, W | en_US |
dc.creator | Hsu, LT | en_US |
dc.date.accessioned | 2022-05-16T09:07:28Z | - |
dc.date.available | 2022-05-16T09:07:28Z | - |
dc.identifier.issn | 1524-9050 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/92735 | - |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers | en_US |
dc.rights | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | en_US |
dc.rights | The following publication Zhang, G., Ng, H. F., Wen, W., & Hsu, L. T. (2020). 3D mapping database aided GNSS based collaborative positioning using factor graph optimization. IEEE Transactions on Intelligent Transportation Systems, 22(10), 6175-6187 is available at https://doi.org/10.1109/TITS.2020.2988531 | en_US |
dc.subject | 3D building model | en_US |
dc.subject | Collaborative positioning | en_US |
dc.subject | GNSS | en_US |
dc.subject | NLOS | en_US |
dc.subject | Ray-tracing | en_US |
dc.subject | Urban canyon | en_US |
dc.subject | V2X | en_US |
dc.title | 3D mapping database aided GNSS based collaborative positioning using factor graph optimization | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 6175 | en_US |
dc.identifier.epage | 6187 | en_US |
dc.identifier.volume | 22 | en_US |
dc.identifier.issue | 10 | en_US |
dc.identifier.doi | 10.1109/TITS.2020.2988531 | en_US |
dcterms.abstract | The recent development in vehicle-to-everything (V2X) communication opens a new opportunity to improve the positioning performance of the road users. We explore the benefit of connecting the raw data of the global navigation satellite system (GNSS) from the agents. In urban areas, GNSS positioning is highly degraded due to signal blockage and reflection. 3D building model can play a major role in mitigating the GNSS multipath and non-line-of-sight (NLOS) effects. To combine the benefits of 3D models and V2X, we propose a novel 3D mapping aided (3DMA) GNSS-based collaborative positioning method that makes use of the available surrounding GNSS receivers' measurements. By complementarily integrating the ray-tracing based 3DMA GNSS and the double difference technique, the random errors (such as multipath and NLOS) are mitigated while eliminating the systematic errors (such as atmospheric delay and satellite clock/orbit biases) between road user. To improve the accuracy and robustness of the collaborative algorithm, factor graph optimization (FGO) is employed to optimize the positioning solutions among agents. Multiple low-cost GNSS receivers are used to collect both static and dynamic data in Hong Kong and to evaluate the proposed algorithm by post-processing. We reduce the GNSS positioning error from over 30 meters to less than 10 meters for road users in a deep urban canyon. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | IEEE transactions on intelligent transportation systems, Oct. 2021, v. 22, no. 10, p. 6175-6187 | en_US |
dcterms.isPartOf | IEEE transactions on intelligent transportation systems | en_US |
dcterms.issued | 2021-10 | - |
dc.identifier.scopus | 2-s2.0-85116858865 | - |
dc.identifier.eissn | 1558-0016 | en_US |
dc.description.validate | 202205 bckw | en_US |
dc.description.oa | Accepted Manuscript | en_US |
dc.identifier.FolderNumber | AAE-0017 | - |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | The Hong Kong Polytechnic University | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 58700280 | - |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
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Zhang_3D_Mapping_Database.pdf | Pre-Published version | 2.59 MB | Adobe PDF | View/Open |
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