Real-Time Large-Scale Motion Cancellation Method for FMCW Radar Vital Sign Detection

When radar detects the vital signs of moving humans, the range bin where the target is located is in a state of continuous change. The traditional method extracts peak phases based on the range profile matrix (RPM) for compensation. However, limited by range resolution and affected by environmental noise, it is prone to target range localization inaccuracies, which further prevents accurate compensation of motion phases and ultimately leads to phase ambiguity. To solve this problem, this paper proposes a vital sign extraction method integrating the extended Differentiate and Cross Multiply (DACM) algorithm and robust Kalman filtering. This method utilizes the high sensitivity of the angular frequency to target displacement, eliminates largescale motion interference through robust Kalman filtering, and finally restores the target phase information by accumulating the filtered angular frequency. Without the need for accurate fitting of the motion path, this method effectively improves the real-time performance and detection accuracy of the system.