Integrated Remote Sensing and Map Registration System for High-Precision Positioning in Covered Parking Garages

Emma Dawson

Peer Reviewed

Abstract:	Accurate, uninterrupted and high-precision positioning is a requirement for autonomous vehicles (AVs) of the future. Global Navigation Satellite Systems (GNSS) are ubiquitous for navigation today, but access to satellites is not always possible in urban and indoor environments. A suite of other sensors is necessary to satisfy the positioning requirements of AVs. Electronic scanning radars (ESR) are now a low-cost sensor found in most recent vehicles. They are of increasing interest for positioning and navigation applications for their ability to operate in all weather and lighting conditions. This paper presents a positioning method for use in GNSS-denied environments which registers radar point clouds generated from four ESRs mounted on a vehicle to a pre-existing map of the environment. Radar odometry is performed to obtain a forward velocity estimate at a high data rate, as an alternate source of velocity to the commonly used odometer. A dead-reckoning solution involving inertial sensors and radar odometry is used to pre-transform and aggregate the ESR scans into a point cloud in the navigation frame of the map. An iterative closest point (ICP) algorithm is used to register the radar point cloud to the map, providing a transformation which serves as a correction to the dead-reckoning solution. A real road test scenario was performed inside a covered parking garage to examine the performance of the proposed method. The proposed method was able to sustain sub-meter level accuracy 95% of the time at a data rate of 20Hz.
Published in:	Proceedings of the 36th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2023) September 11 - 15, 2023 Hyatt Regency Denver Denver, Colorado
Pages:	1633 - 1643
Cite this article:	Dawson, Emma, "Integrated Remote Sensing and Map Registration System for High-Precision Positioning in Covered Parking Garages," Proceedings of the 36th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2023), Denver, Colorado, September 2023, pp. 1633-1643. https://doi.org/10.33012/2023.19210
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