Trajectory-oriented EKF-SLAM using the Fourier-Mellin Transform applied to Microwave Radar Images

This paper is concerned with the simultaneous localization and mapping (SLAM) application using data obtained from a microwave radar sensor. The radar scanner is based on the frequency modulated continuous wave (FMCW) technology. In order to overcome the complexity of radar image analysis, a trajectory-oriented EKF-SLAM technique using data from a 360° field of view radar sensor has been developed. This process makes no landmark assumptions and avoids the data association problem. The method of egomotion estimation makes use of the Fourier-Mellin transform for registering radar images in a sequence, from which the rotation and translation of the sensor motion can be estimated. In the context of the scan-matching SLAM, the use of the Fourier-Mellin transform is original and provides an accurate and efficient way of computing the rigid transformation between consecutive scans. Experimental results on real-world data are presented. Moreover a performance evaluation of the results is carried out. A comparative study between the output data of the proposed method and the data processed with smoothing approaches to SLAM is also achieved.