For non-contact target sign detection by millimeter wave radar, a fast-moving multi-target scene was studied through simulation experiments. First, the measurement information of the target position and speed is obtained, and the corresponding relationship between each measurement distance and angle is obtained through an innovative algorithm, and then the joint probabilistic data association (JPDA) and nearest neighbor data association (NNDA) are used respectively. Multiple targets are tracked, and then their sign phase information is extracted, and the short-time Fourier transform algorithm is used to estimate the frequency of the processed sign signal. Through experiments, it can be seen that for moving targets with speeds up to 0.9 m/s, this detection method can obtain the target's breathing frequency with a small error; however, because the heartbeat signal is relatively weak, it can only be detected in a static state. Compared with other radar sign detection methods, this method can detect the breathing frequency of the speed of 0.9 m/s at a root mean square error detection rate of 0.035, and can detect multiple targets simultaneously without being easily confused.