Research On Feature Extraction And Separation Technology Of Chest Wall Micro-Motion Millimeter Wave Radar Signal

Millimeter-wave radar can realize non-contact vital sign monitoring,and has broad application prospects in the fields of home-based elderly health monitoring,medical monitoring and disaster rescue.Vital sign activities such as breathing and heartbeat can cause millimeter-level micro-motion of the chest wall,so the frequency modulated continuous millimeter wave(FMCMW)radar with strong anti-interference and high sensitivity is used to complete the measurement.During vital sign monitoring,static object interference,random body movement(RBM),etc.will affect the extraction of vital sign signals,resulting in failure to correctly decompose breathing and heartbeat signals.The main work of this paper is as follows:Ⅰ.This paper proposes a method for decomposing vital signs signals based on variational modal decomposition.First,Fourier transform is performed on the intermediate frequency signal of the millimeter-wave radar to determine the distance unit where the chest wall is located;then,the phase in this distance unit is extracted and unwound,and the phase is converted into a distance variable to obtain a respiration and heartbeat information.Vital sign signal;finally,the variational modal decomposition algorithm is used to decompose the breathing and heartbeat signals from the vital sign signal,and the frequency feature is estimated based on Fourier transform.The vital sign signal waveform was successfully extracted through the experiment,and the frequency error of the separated breathing and heartbeat signals was within 8%,which proved the feasibility of the proposed technical route.Ⅱ.This paper establishes a static interference mathematical model and proposes a static interference removal method.Firstly,the radar echo signal model of static interference is established,and the specific expression of static object interference is obtained.Then,the causes and influence methods of static interference of different strengths on vital sign signals are simulated and analyzed.Finally,a dynamic circle center estimation method is proposed to remove the static interference.The effectiveness of the dynamic circle center estimation method for static interference removal is verified by experiments.Ⅲ.This paper proposes a body motion trajectory estimation method based on polynomial fitting to eliminate the influence of body motion dynamic interference on the estimation accuracy of vital sign parameters.First,the mathematical model of random body motion and the radar echo signal model under dynamic interference are established;then,the manifestations of the influence of dynamic interference on vital sign signals are simulated and analyzed;finally,polynomial fitting is used to estimate the trajectory of random body motion,reducing the Dynamic disturbances in vital sign signals.The experimental results show that the proposed method can effectively remove the RBM in vital sign signals and improve the accuracy of parameter estimation.