Non-contact life sign monitoring signal processing system

Abstract

The invention provides a non-contact life sign monitoring signal processing system, comprising an I/Q channel signal processing module, a respiration frequency estimation module, a modulation component removing module and a heartbeat frequency estimation module, wherein the I/Q channel signal processing module is used for combining I/Q channel signals I(t) and Q(t) into a complex signal S(t); the respiration frequency estimation module is used for defining a frequency rotation operator according to the baseband signal mathematic model characteristic, multiplying S(t) by, performing Fourier transformation, performing optimizing estimation on a parameter P by the spectrum concentrated index, and estimating firstly to obtain respiration frequency fr; the modulation component removing module is used for multiplying S(t) by the frequency rotation operator estimated in the step 2 and removing the modulation component caused by respiration in S(t); and the heartbeat frequency estimation module is used for estimating the heartbeat frequency fh. According to the non-contact life sign monitoring signal processing system provided by the invention, the matched frequency rotation operators are constructed based on a radar baseband signal model to perform parameterization optimizing estimation, and high-precision fr and fh estimation values can be obtained by short sampling length data, so the test sensitivity and the noise resistance are high.

Description

technical field [0001] The invention relates to the technical field of radar signal processing, in particular to a signal processing system for non-contact vital sign monitoring based on the micro-Doppler effect. Background technique [0002] The microwave radar is used to emit radio frequency waves of a certain frequency, directly irradiating the human body, and the breathing and heartbeat of the human body will cause the chest to rise and fall regularly. This micro-motion will perform micro-Doppler modulation and reflection on the radar radio frequency waves. By demodulating the phase of the radar echo signal, the frequency information of respiration and heartbeat can be obtained, and the long-term non-contact monitoring of vital signs can be realized. Non-contact vital sign monitoring based on the micro-Doppler effect solves the inconvenience of additional contact equipment for contact monitoring, and has important application potential in the fields of health and medical...

AI Technical Summary

Problems solved by technology

When extracting information from the baseband signal, the use of complex signal demodulation can effectively eliminate the problem of detecting zero points, but the multiplier harmonic components caused by respiration often cover up the spectrum peaks caused by heartbeat motion modulation, which cannot be effectively monitored simultaneously. breathing and heart rate

By performing arctangent demodulation on the dual-channel baseband signal, the modulation phase information can be directly extracted, but accurate DC offset compensation is required, and the anti-noise performance is poor

The baseband signal is a nonlinear frequency modulation signal, and its time-frequency expression is the superposition of two oscillating time-frequency components. Since the amplitude of the Doppler frequency shift caused by breathing and heartbeat is small, it is difficult to achieve the required frequency through time-frequency transformation. time and frequency resolution, resulting in poor estimation accuracy

[0004] The above signal demodulation algorithms all use FFT (Fast Fourier Transform) to obtain the peak frequency of the spectrum to directly estimate the breathing and heartbeat frequency, but on the one hand, because the normal human breathing frequency is generally between 0.3-0.6Hz, ordinary FFT Fourier transform) requires a long sampling time to obtain high frequency resolution to accurately estimate breathing and heartbeat frequencies

On the other hand, longer sample data length reduces time resolution, resulting in poor sensitivity of monitoring

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