Enhanced Vehicular Localization under Non-Line-of-Sight Multipath Propagation

Sung Il Choi; Hong Ki Kim; Sang Hyun Lee

doi:10.1109/ICTC52510.2021.9620752

Enhanced Vehicular Localization under Non-Line-of-Sight Multipath Propagation

Sung Il Choi, Hong Ki Kim, Sang Hyun Lee

School of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

This paper develops localization strategies of non-line-of-sight (NLoS) hidden vehicles using Bayesian inference techniques and study an enhanced convergence property via statistical physics based analysis methods. NLoS vehicular localization is achieved with the measurement of multi-path channel propagation information, such as angle-of-arrival (AoA), angle-of-departure (AoD) and time-of-arrival (ToA) by characterizing their geometric relationship in a probabilistic inference task. An efficient solution is derived using generalized approximate message passing (GAMP), while convergence dynamics of GAMP has been reported as a critical issue with this approach. This paper develops a novel approach called generalized message passing (GMP) that revolves the convergence problem via compensation based on Onsager terms of the interaction model. Numerical results verify that the developed algorithm stabilizes the localization performance.

Original language	English
Title of host publication	ICTC 2021 - 12th International Conference on ICT Convergence
Subtitle of host publication	Beyond the Pandemic Era with ICT Convergence Innovation
Publisher	IEEE Computer Society
Pages	318-322
Number of pages	5
ISBN (Electronic)	9781665423830
DOIs	https://doi.org/10.1109/ICTC52510.2021.9620752
Publication status	Published - 2021
Event	12th International Conference on Information and Communication Technology Convergence, ICTC 2021 - Jeju Island, Korea, Republic of Duration: 2021 Oct 20 → 2021 Oct 22

Publication series

Name	International Conference on ICT Convergence
Volume	2021-October
ISSN (Print)	2162-1233
ISSN (Electronic)	2162-1241

Conference

Conference	12th International Conference on Information and Communication Technology Convergence, ICTC 2021
Country/Territory	Korea, Republic of
City	Jeju Island
Period	21/10/20 → 21/10/22

Bibliographical note

Funding Information:
ACKNOWLEDGEMENT This work was supported by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT). (No. 2021-0-00467, Intelligent 6G Wireless Access System, and No. 2016-0-00208, High Accurate Positioning Enabled MIMO Transmission and Network Technologies for Next 5G-V2X (vehicle-to-everything) Services.)

Publisher Copyright:
© 2021 IEEE.

ASJC Scopus subject areas

Information Systems
Computer Networks and Communications

Access to Document

10.1109/ICTC52510.2021.9620752

Cite this

Choi, S. I., Kim, H. K., & Lee, S. H. (2021). Enhanced Vehicular Localization under Non-Line-of-Sight Multipath Propagation. In ICTC 2021 - 12th International Conference on ICT Convergence: Beyond the Pandemic Era with ICT Convergence Innovation (pp. 318-322). (International Conference on ICT Convergence; Vol. 2021-October). IEEE Computer Society. https://doi.org/10.1109/ICTC52510.2021.9620752

Enhanced Vehicular Localization under Non-Line-of-Sight Multipath Propagation. / Choi, Sung Il; Kim, Hong Ki; Lee, Sang Hyun.
ICTC 2021 - 12th International Conference on ICT Convergence: Beyond the Pandemic Era with ICT Convergence Innovation. IEEE Computer Society, 2021. p. 318-322 (International Conference on ICT Convergence; Vol. 2021-October).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Choi, SI, Kim, HK & Lee, SH 2021, Enhanced Vehicular Localization under Non-Line-of-Sight Multipath Propagation. in ICTC 2021 - 12th International Conference on ICT Convergence: Beyond the Pandemic Era with ICT Convergence Innovation. International Conference on ICT Convergence, vol. 2021-October, IEEE Computer Society, pp. 318-322, 12th International Conference on Information and Communication Technology Convergence, ICTC 2021, Jeju Island, Korea, Republic of, 21/10/20. https://doi.org/10.1109/ICTC52510.2021.9620752

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title = "Enhanced Vehicular Localization under Non-Line-of-Sight Multipath Propagation",

abstract = "This paper develops localization strategies of non-line-of-sight (NLoS) hidden vehicles using Bayesian inference techniques and study an enhanced convergence property via statistical physics based analysis methods. NLoS vehicular localization is achieved with the measurement of multi-path channel propagation information, such as angle-of-arrival (AoA), angle-of-departure (AoD) and time-of-arrival (ToA) by characterizing their geometric relationship in a probabilistic inference task. An efficient solution is derived using generalized approximate message passing (GAMP), while convergence dynamics of GAMP has been reported as a critical issue with this approach. This paper develops a novel approach called generalized message passing (GMP) that revolves the convergence problem via compensation based on Onsager terms of the interaction model. Numerical results verify that the developed algorithm stabilizes the localization performance. ",

author = "Choi, {Sung Il} and Kim, {Hong Ki} and Lee, {Sang Hyun}",

note = "Funding Information: ACKNOWLEDGEMENT This work was supported by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT). (No. 2021-0-00467, Intelligent 6G Wireless Access System, and No. 2016-0-00208, High Accurate Positioning Enabled MIMO Transmission and Network Technologies for Next 5G-V2X (vehicle-to-everything) Services.) Publisher Copyright: {\textcopyright} 2021 IEEE.; 12th International Conference on Information and Communication Technology Convergence, ICTC 2021 ; Conference date: 20-10-2021 Through 22-10-2021",

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AB - This paper develops localization strategies of non-line-of-sight (NLoS) hidden vehicles using Bayesian inference techniques and study an enhanced convergence property via statistical physics based analysis methods. NLoS vehicular localization is achieved with the measurement of multi-path channel propagation information, such as angle-of-arrival (AoA), angle-of-departure (AoD) and time-of-arrival (ToA) by characterizing their geometric relationship in a probabilistic inference task. An efficient solution is derived using generalized approximate message passing (GAMP), while convergence dynamics of GAMP has been reported as a critical issue with this approach. This paper develops a novel approach called generalized message passing (GMP) that revolves the convergence problem via compensation based on Onsager terms of the interaction model. Numerical results verify that the developed algorithm stabilizes the localization performance.

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Enhanced Vehicular Localization under Non-Line-of-Sight Multipath Propagation

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