Non-Line-of-Sight Path-Assisted Localization Based on Joint Spatio-Temporal Information

Chengsong Fu; Wenquan Feng; Hongbo Zhao; Jianer Zhou; Chen Zhuang

doi:10.1109/LCOMM.2025.3634799

Non-Line-of-Sight Path-Assisted Localization Based on Joint Spatio-Temporal Information

Chengsong Fu
, Wenquan Feng
, Hongbo Zhao
, Jianer Zhou^*
, Chen Zhuang^*

^*Corresponding author for this work

School of Electronic and Information Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

In complex environments, traditional line-of-sight (LOS)-based localization methods suffer from limited performance due to frequent interruption of LOS paths. This letter proposes a spatio-temporal joint localization (STJL) mechanism, a novel non-line-of-sight (NLOS) path-assisted localization method that exploits both spatial and temporal characteristics of channel parameters. The STJL first introduces an error-minimization-based path matching algorithm to associate multipath components across time, improving path consistency and parameter stability. Then the STJL integrates temporal continuity and spatial geometry of paths through Kalman filtering to improve localization accuracy. The proposed mechanism enables robust estimation of virtual LOS paths even under obstruction. Simulation results demonstrate that the STJL significantly improves accuracy and stability of the localization, achieving over 50% improvement in localization accuracy compared to the geometry-based NLOS localization.

Original language	English
Pages (from-to)	307-311
Number of pages	5
Journal	IEEE Communications Letters
Volume	30
DOIs	https://doi.org/10.1109/LCOMM.2025.3634799
State	Published - 2026

Keywords

Kalman filtering
Non-line-of-sight
multipath-assisted positioning
path matching

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10.1109/LCOMM.2025.3634799

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@article{20fa23b315ab4bc9b8ac45952a61a359,

title = "Non-Line-of-Sight Path-Assisted Localization Based on Joint Spatio-Temporal Information",

abstract = "In complex environments, traditional line-of-sight (LOS)-based localization methods suffer from limited performance due to frequent interruption of LOS paths. This letter proposes a spatio-temporal joint localization (STJL) mechanism, a novel non-line-of-sight (NLOS) path-assisted localization method that exploits both spatial and temporal characteristics of channel parameters. The STJL first introduces an error-minimization-based path matching algorithm to associate multipath components across time, improving path consistency and parameter stability. Then the STJL integrates temporal continuity and spatial geometry of paths through Kalman filtering to improve localization accuracy. The proposed mechanism enables robust estimation of virtual LOS paths even under obstruction. Simulation results demonstrate that the STJL significantly improves accuracy and stability of the localization, achieving over 50\% improvement in localization accuracy compared to the geometry-based NLOS localization.",

keywords = "Kalman filtering, Non-line-of-sight, multipath-assisted positioning, path matching",

author = "Chengsong Fu and Wenquan Feng and Hongbo Zhao and Jianer Zhou and Chen Zhuang",

note = "Publisher Copyright: {\textcopyright} 1997-2012 IEEE.",

year = "2026",

doi = "10.1109/LCOMM.2025.3634799",

language = "英语",

volume = "30",

pages = "307--311",

journal = "IEEE Communications Letters",

issn = "1089-7798",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - JOUR

T1 - Non-Line-of-Sight Path-Assisted Localization Based on Joint Spatio-Temporal Information

AU - Fu, Chengsong

AU - Feng, Wenquan

AU - Zhao, Hongbo

AU - Zhou, Jianer

AU - Zhuang, Chen

PY - 2026

Y1 - 2026

N2 - In complex environments, traditional line-of-sight (LOS)-based localization methods suffer from limited performance due to frequent interruption of LOS paths. This letter proposes a spatio-temporal joint localization (STJL) mechanism, a novel non-line-of-sight (NLOS) path-assisted localization method that exploits both spatial and temporal characteristics of channel parameters. The STJL first introduces an error-minimization-based path matching algorithm to associate multipath components across time, improving path consistency and parameter stability. Then the STJL integrates temporal continuity and spatial geometry of paths through Kalman filtering to improve localization accuracy. The proposed mechanism enables robust estimation of virtual LOS paths even under obstruction. Simulation results demonstrate that the STJL significantly improves accuracy and stability of the localization, achieving over 50% improvement in localization accuracy compared to the geometry-based NLOS localization.

AB - In complex environments, traditional line-of-sight (LOS)-based localization methods suffer from limited performance due to frequent interruption of LOS paths. This letter proposes a spatio-temporal joint localization (STJL) mechanism, a novel non-line-of-sight (NLOS) path-assisted localization method that exploits both spatial and temporal characteristics of channel parameters. The STJL first introduces an error-minimization-based path matching algorithm to associate multipath components across time, improving path consistency and parameter stability. Then the STJL integrates temporal continuity and spatial geometry of paths through Kalman filtering to improve localization accuracy. The proposed mechanism enables robust estimation of virtual LOS paths even under obstruction. Simulation results demonstrate that the STJL significantly improves accuracy and stability of the localization, achieving over 50% improvement in localization accuracy compared to the geometry-based NLOS localization.

KW - Kalman filtering

KW - Non-line-of-sight

KW - multipath-assisted positioning

KW - path matching

UR - https://www.scopus.com/pages/publications/105022249252

U2 - 10.1109/LCOMM.2025.3634799

DO - 10.1109/LCOMM.2025.3634799

M3 - 文章

AN - SCOPUS:105022249252

SN - 1089-7798

VL - 30

SP - 307

EP - 311

JO - IEEE Communications Letters

JF - IEEE Communications Letters

ER -

Non-Line-of-Sight Path-Assisted Localization Based on Joint Spatio-Temporal Information

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Keywords

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