Improving Land Vehicle Navigation: A Study on RIDR and Kalman Filters

Paulo Ricardo Marques de Araujo, Eslam Mounier, Mohamed Elhabiby, Sidney Givigi, Aboelmagd Noureldin

Peer Reviewed

Abstract:	This paper investigates RIDR (Radar Inertial Dead Reckoning), a novel positioning system using gyroscopes and radar-based forward speed estimation. It presents a formulation for vector space Kalman filters and compares RIDR with INS and RISS. An error state Kalman filter is proposed for precise position and attitude corrections. Experimental validation in diverse urban environments demonstrates the promising performance of RIDR, reinforcing its viability as a robust alternative to IMU-based algorithms. This research highlights challenges and opportunities for future advancements in the field, paving the way for improved autonomous vehicle navigation and control systems.
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:	1656 - 1668
Cite this article:	de Araujo, Paulo Ricardo Marques, Mounier, Eslam, Elhabiby, Mohamed, Givigi, Sidney, Noureldin, Aboelmagd, "Improving Land Vehicle Navigation: A Study on RIDR and Kalman Filters," Proceedings of the 36th International Technical Meeting of the Satellite Division of the Institute of Navigation (ION GNSS+ 2023), Denver, Colorado, September 2023, pp. 1656-1668. https://doi.org/10.33012/2023.19212
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