Radar/IMU Integration Using Visual Feature Matching

Mohamed Elkholy, Mohamed Elsheikh, Naser El-Sheimy

Abstract:	In this paper, a 360^o Frequency Modulated Continuous Wave (FMCW) Radar was integrated with IMU, nonholonomic constraints (NHC), and an odometer through a closed-loop extended Kalman filter (EKF) to compensate for the Global Navigation Satellite System (GNSS) signal outages, overcome INS drift and errors, and smooth the navigation solution. The Oriented Fast and Rotated Brief (ORB) algorithm was adopted for Radar ego-motion estimation. An open access dataset was used in the experimental work. The data was collected in a GNSS challenging environment containing trees and high buildings around the Daejeon Convention Center (DCC) in South Korea. To access the performance of the proposed methodology, simulated GNSS outages were introduced for two trajectories at three different starting outage points. The horizontal position and 3D position percentage errors range between 1.07% and 2.79% of the traveled distance during two minutes of GNSS signal outage, where the traveled distance was around 1.1 km.
Published in:	Proceedings of the 35th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2022) September 19 - 23, 2022 Hyatt Regency Denver Denver, Colorado
Pages:	1999 - 2010
Cite this article:	Elkholy, Mohamed, Elsheikh, Mohamed, El-Sheimy, Naser, "Radar/IMU Integration Using Visual Feature Matching," Proceedings of the 35th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2022), Denver, Colorado, September 2022, pp. 1999-2010. https://doi.org/10.33012/2022.18549
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