Pixel-Level GPS Localization and Denoising using Computer Vision and 6G Communication Beams

Fuente: arXiv
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Main Authors: Charan, Gouranga, Osman, Tawfik, Alkhateeb, Ahmed
Format: Preprint
Published: 2024
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author Charan, Gouranga
Osman, Tawfik
Alkhateeb, Ahmed
author_facet Charan, Gouranga
Osman, Tawfik
Alkhateeb, Ahmed
contents Accurate localization is crucial for various applications, including autonomous vehicles and next-generation wireless networks. However, the reliability and precision of Global Navigation Satellite Systems (GNSS), such as the Global Positioning System (GPS), are compromised by multi-path errors and non-line-of-sight scenarios. This paper presents a novel approach to enhance GPS accuracy by combining visual data from RGB cameras with wireless signals captured at millimeter-wave (mmWave) and sub-terahertz (sub-THz) basestations. We propose a sensing-aided framework for (i) site-specific GPS data characterization and (ii) GPS position de-noising that utilizes multi-modal visual and wireless information. Our approach is validated in a realistic Vehicle-to-Infrastructure (V2I) scenario using a comprehensive real-world dataset, demonstrating a substantial reduction in localization error to sub-meter levels. This method represents a significant advancement in achieving precise localization, particularly beneficial for high-mobility applications in 5G and beyond networks.
format Preprint
id arxiv_https___arxiv_org_abs_2407_19541
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Pixel-Level GPS Localization and Denoising using Computer Vision and 6G Communication Beams
Charan, Gouranga
Osman, Tawfik
Alkhateeb, Ahmed
Signal Processing
Accurate localization is crucial for various applications, including autonomous vehicles and next-generation wireless networks. However, the reliability and precision of Global Navigation Satellite Systems (GNSS), such as the Global Positioning System (GPS), are compromised by multi-path errors and non-line-of-sight scenarios. This paper presents a novel approach to enhance GPS accuracy by combining visual data from RGB cameras with wireless signals captured at millimeter-wave (mmWave) and sub-terahertz (sub-THz) basestations. We propose a sensing-aided framework for (i) site-specific GPS data characterization and (ii) GPS position de-noising that utilizes multi-modal visual and wireless information. Our approach is validated in a realistic Vehicle-to-Infrastructure (V2I) scenario using a comprehensive real-world dataset, demonstrating a substantial reduction in localization error to sub-meter levels. This method represents a significant advancement in achieving precise localization, particularly beneficial for high-mobility applications in 5G and beyond networks.
title Pixel-Level GPS Localization and Denoising using Computer Vision and 6G Communication Beams
topic Signal Processing
url https://arxiv.org/abs/2407.19541