Research On Vital Sign Signal Detection Method Based On FMCW Millimeter Wave Radar

In the field of non-contact vital sign signal detection,compared to ultra wideband radar,radar based on frequency modulated continuous wave(FMCW)system has a simpler structure and is easy to implement,while requiring low sampling rates.Combining the characteristics of millimeter wave radar such as high target detection accuracy,less environmental impact,and ability to work around the clock,this thesis uses TI’s AWR1642 millimeter wave radar platform to achieve a 77 GHz linear frequency modulated continuous wave system for human respiratory and heartbeat signal detection system and algorithm simulation modeling,and completes the hardware implementation of the algorithm under Xilinx Zynq FPGA platform.The main work includes:Firstly,starting with the radar baseband signal,the echo signal preprocessing process is completed using Moving Target Indication filter,range Fast Fourier Transform,frequency accumulation,and phase extraction methods to obtain a mixed respiratory and heartbeat signal.In order to separate and extract the respiratory and heartbeat signals,a correlation matrix based feature decomposition algorithm and empirical mode decomposition algorithm are used.Through matlab simulation modeling,two sets of bandpass filters are used to suppress out of band noise and separate the respiratory and heartbeat signals.Then,the respective frequencies of the two algorithms are extracted through MUSIC algorithm,sliding window MUSIC algorithm,Empirical Mode Decomposition,and Ensemble Empirical Mode Decomposition algorithm.In order to solve the problem of frequency band aliasing when the filter separates the breath and heartbeat,this thesis uses LMS(Least Mean Square)adaptive filtering method to replace the bandpass filter,and proposes a method for reconstructing the LMS filter reference signal: using Ensemble Empirical Mode Decomposition decomposition and wavelet soft threshold denoising,selecting appropriate submodal to form the reference heartbeat signal,and performing relevant simulation on the selection of the filter step factor,taking into account the convergence speed and accuracy.Simulation results and measured data show that the proposed method has a high accuracy in frequency estimation results,and can be applied to the extraction of respiratory and heartbeat signals in frequency band aliasing scenarios.Finally,the LFMCW millimeter wave radar vital sign signal detection system is built using the AWR1642 and Xilinx FPGA platforms.AWR1642 is responsible for processing the RF front-end to the radar baseband signal.The output data is collected to the FPGA through the DAC1000 EVM,and the code is written in Verilog.The EEMD+LMS breathing and heartbeat extraction algorithm is implemented in the FPGA.The feasibility of the system is verified through the output waveform.