Ultra-wideband radar has the advantages of high resolution, strong penetration ability, low power consumption, etc. The human body does not need to contact any electrodes or sensors when the ultra-wideband radar is in operation, and it can penetrate through non-metallic media such as clothes and ruins, and detect the information of human vital signs at a long distance. It has an important application value in non-contact vital signs detection. Since the human heartbeat signal is easily interfered by respiratory harmonics and other noises, in order to accurately extract the human vital signs, vital signs signal denoising method based on the combination of improved adaptive noise ensemble empirical modal decomposition (ICEEMDAN) and wavelet packet decomposition (WPD) is proposed. Firstly, we measure the vital signs of the person to be measured by ultra-wideband radar, obtain the spatial location of the human body to extract the micro-motion signals from the body surface, and perform compensation and under-sampling processing for the vibration signals of the body surface; we use the threshold denoising method of ICEEMDAN-WPD to carry out modal decomposition of the micromotion signals, select appropriate modal components for denoising and reconstruction, and obtain the time-frequency characteristics of the micro-motion signals of the human heartbeat. The experimental results show that the algorithm improves the correlation coefficient to 0.9405 and the signal-to-noise ratio to 9.0938 dB compared with the traditional denoising algorithm, which retains more vital signs information and has higher signal-to-noise ratio, and it can be effectively used in the field of vital signs detection.