Vehicular Wireless Positioning -- A Survey

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Authors: Sharief Saleh, Satyam Dwivedi, Russ Whiton, Peter Hammarberg, Musa Furkan Keskin, Julia Equi, Hui Chen, Florent Munier, Olof Eriksson, Fredrik Gunnarsson, Fredrik Tufvesson, Henk Wymeersch
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Abstract

The rapid advancement of connected and autonomous vehicles has driven a growing demand for precise and reliable positioning systems capable of operating in complex environments. Meeting these demands requires an integrated approach that combines multiple positioning technologies, including wireless-based systems, perception-based technologies, and motion-based sensors. This paper presents a comprehensive survey of wireless-based positioning for vehicular applications, with a focus on satellite-based positioning (such as global navigation satellite systems (GNSS) and low-Earth-orbit (LEO) satellites), cellular-based positioning (5G and beyond), and IEEE-based technologies (including Wi-Fi, ultrawideband (UWB), Bluetooth, and vehicle-to-vehicle (V2V) communications). First, the survey reviews a wide range of vehicular positioning use cases, outlining their specific performance requirements. Next, it explores the historical development, standardization, and evolution of each wireless positioning technology, providing an in-depth categorization of existing positioning solutions and algorithms, and identifying open challenges and contemporary trends. Finally, the paper examines sensor fusion techniques that integrate these wireless systems with onboard perception and motion sensors to enhance positioning accuracy and resilience in real-world conditions. This survey thus offers a holistic perspective on the historical foundations, current advancements, and future directions of wireless-based positioning for vehicular applications, addressing a critical gap in the literature.

Fields of Study & Subjects

Indoor and Outdoor Localization Technologies GNSS positioning and interference Vehicular Ad Hoc Networks (VANETs)

Publication details

Journal / source
arXiv (Cornell University)
Publication date
28 January 2026
Document type
Preprint