An Enhanced Self-Motion Estimation Method based on mmWave Radar and IMU Data Fusion

An enhanced self-motion estimation method based on millimeter Wave (mmWave) radar and Inertial Measurement Unit (IMU) data fusion is proposed in this study, using a modified Extended Kalman Filter (EKF). Since the instrument error is inevitable in traditional Inertial Navigation Systems (INS), which is accumulated over time, significant errors are brought into the motion acquisition. However, mmWave radar has the abilities of high ranging accuracy and strong penetration, and can generate reliable point cloud information as LiDAR. Therefore, the fusion of mmWave radar and IMU makes the motion estimation more accurate. Experiments show that the proposed method can effectively improve the accuracy of self-motion estimation.