A Spatiotemporal Alignment Method for Localization with MIMO Antenna Arrays Integration

Accurate spatiotemporal alignment is crucial for multi-sensor fusion in Localization scenarios. Significant temporal discrepancies between sensors can affect alignment quality, particularly in systems employing Multiple-Input Multiple-Output (MIMO) antenna arrays. In this study, we propose a novel method based on information trajectory segments for real-time spatiotemporal alignment estimation. Experimental results demonstrate that our approach consistently enhances localization accuracy across various temporal offsets. This method proves robust against time discrepancies, improving the reliability of localization systems integrated with MIMO antenna arrays.

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Publication Details

Published
2024-09-22
DOI
https://doi.org/10.1109/apcap62011.2024.10881049
Primary Topic
Indoor and Outdoor Localization Technologies
Type
article
Field-Weighted Citation Impact
0.00

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article

A Spatiotemporal Alignment Method for Localization with MIMO Antenna Arrays Integration

Xiaolong Yang, Jinglong Cheng, Ming Gao, Bingrui Zhang et al.
Indoor and Outdoor Localization Technologies
article

A Spatiotemporal Alignment Method for Localization with MIMO Antenna Arrays Integration

Xiaolong Yang, Jinglong Cheng, Ming Gao, Bingrui Zhang, Mu Zhou
article en

Abstract

Accurate spatiotemporal alignment is crucial for multi-sensor fusion in Localization scenarios. Significant temporal discrepancies between sensors can affect alignment quality, particularly in systems employing Multiple-Input Multiple-Output (MIMO) antenna arrays. In this study, we propose a novel method based on information trajectory segments for real-time spatiotemporal alignment estimation. Experimental results demonstrate that our approach consistently enhances localization accuracy across various temporal offsets. This method proves robust against time discrepancies, improving the reliability of localization systems integrated with MIMO antenna arrays.

Chongqing University of Posts and Telecommunications (CN)
National Natural Science Foundation of China, Chongqing Graduate Student Research Innovation Project
Openalex Percentile: Top 75%
Indoor and Outdoor Localization Technologies
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