리플렉터 맵핑 분포 최소화를 통한 4D 이미징 레이더-IMU 외부 파라미터 캘리브레이션

Abstract

Precise extrinsic calibration of 4D imaging radar and IMU(Inertial Measurement Unit) is essential for accurate perception and stable control in autonomous systems. This study introduces a novel, reflector-based calibration method that minimizes spatial distribution discrepancies among radar-detected reflector points, achieving accurate alignment of extrinsic parameters. By extracting high-RCS reflectors from radar data, the proposed method isolates reliable features while reducing noise. Calibration of ZRP (height, roll, pitch) parameters using a fitted plane model further enhances accuracy, reducing the dimensionality of the final optimization. Through minimizing reflector point dispersion in the global frame, our approach achieves robust x, y, and yaw calibration, improving the system’s resilience in complex environments. Experimental evaluations confirm the effectiveness of this method across various scenarios, highlighting its potential for enhancing the fidelity of radar-IMU calibration.