The physical health status of civil aviation personnel is an important factor affecting aviation safety， among which respiration and heart rate are extremely important indicators of health. To address the limitations and interference of contact or wearable measurement systems on personnel during working， linear frequency-modulated continuous wave （FMCW） radar can be used to achieve non-contact measurement. Since vital sign signals have the characteristics of time-varying and non-stationary， to solve the problem of mode aliasing in empirical mode decomposition （EMD） in signal decomposition， the time-varying filtering based on EMD （TVF-EMD） can adaptively adjust the local cutoff frequency of the signal， effectively improving the signal separation performance and solving the mode aliasing problem. By using the intrinsic mode functions （IMF） components decomposed by TVF-EMD to reconstruct the time-domain signal corresponding to the heartbeat， the frequency and inter-beat interval （IBI） of the heartbeat signal can be estimated， and further the relevant indicators of heart rate variability （HRV） can be estimated. Simulation experiments and actual measured data processing results show that TVF-EMD can effectively separate respiration and heartbeat signals from millimeter wave radar measurement signals. At the same time， a simulation analysis of the decomposition effects of TVF-EMD and EMD methods from the aspects of mode aliasing degree and signal separation performance has been conducted， and the results show that TVF-EMD can effectively solve the mode aliasing problem. Therefore， the TVF-EMD method can accurately and effectively extract vital sign information from millimeter wave radar measurement signals， provide accurate time-domain information for IBI estimation and HRV analysis， and has a broad application prospect.