Research On Vital Signs Detection Algorithm Based On Ultra-wideband Radar

With the rapid development of radio technology,ultra-wideband radar has gradually become an important research area for vital signs detection.UWB radar plays an increasingly important role in vital signs detection due to its advantages of high range resolution,strong penetration ability and anti-interference.Among them,the vital signs detection system based on ultra-wideband radar has a wide range of applications,especially in the fields of medical health,disaster relief,and military warfare.This paper studies the vital signs detection algorithm based on ultra-wideband radar.The main contents are summarized as follows:(1)For the presence of strong clutter and noise in the received signal,this paper first uses the average cancellation method to filter the static clutter,and then uses the frequency domain low-pass filtering and signal autocorrelation processing to reduce the noise of the signal to improve The signal-to-noise ratio of the signal,and then use the range gate selection algorithm to extract the vibration signal of the body surface.(2)Research the single-target vital sign detection algorithm.Aiming at the possible slight movement of the measured target(without excessive jitter),a trajectory capture algorithm is proposed,which predicts the target's movement trajectory through the peak position of the received pulse,and then corrects each received pulse according to the movement trajectory to obtain the target's static state Under the received signal.In order to solve the problem that the weak heartbeat signal is easily covered by respiratory harmonics and other clutters,an N-iteration peak capture algorithm is proposed,which first extracts the respiratory frequency and suppresses its higher harmonics,and then captures M peak frequencies in the heartbeat band,Then iterate N times to count the peak frequency of the heartbeat frequency band as the heartbeat frequency.Through MATLAB algorithm simulation,the results show that the algorithm can accurately extract the vital signs of stationary and micro-moving targets.Compared with the traditional peak capture algorithm and Discrete Fourier Transform(DFT)algorithm,it has higher measurement accuracy and more accuracy.Good stability.(3)Study the multi-target vital signs detection algorithm.This paper proposes two multi-target sign detection algorithms,one-dimensional distance clustering-based multi-target sign detection algorithm and distance-frequency clustering-based multi-target sign detection algorithm.The former algorithm first calculates the distance gate energy,then performs one-dimensional distance clustering to obtain the target distance gate coordinates,and then performs a single target sign detection in sections to obtain the respiratory heartbeat frequency.The latter algorithm first expands the echo signal in the frequency domain,and then performs noise reduction and binarization processing on the respiration and heartbeat frequency bands respectively,and then performs two-dimensional distance frequency clustering to obtain the respiratory heartbeat frequency of the measured target.Through MATLAB algorithm simulation,the results show that,compared with other algorithms,the sign detection algorithm based on one-dimensional distance clustering has higher measurement accuracy,but can only detect multiple targets at different locations;while distance-frequency clustering The sign detection algorithm can quickly and accurately detect multiple targets at the same location.