Research On The Measurement Method Of Human Micro-motion Characteristics Based On Picosecond Pulse

As the most typical micro-motion feature of the human body,respiratory signal detection can not only provide technical support for emergency events such as post-disaster rescue and military operations,help staff quickly obtain status information of life bodies in the area,but also assist medical staff in medical monitoring.The patient’s health status is evaluated.Therefore,it is of great significance to study the measurement method of respiratory signal.Because the range of changes in the human thoracic cavity caused by breathing is only 1-3cm,and the environment has a great influence on the detection,traditional detection methods based on acoustic,optical and infrared principles are difficult to make effective reception judgments on human breathing signals in complex environments,And timedomain ultra-wideband radar measurement technology has a strong ability to perceive subtle changes,and can use "time windows" to suppress clutter interference and reduce environmental impact.This paper studies the micro-motion target detection method based on the non-carrier picosecond pulse.The main research contents of the paper are as follows:(1)The characteristics of human micro-motion signals are systematically discussed,and the selection of test hardware is discussed.The models of single life body breathing,target detection behind obstacles,and double life body breathing detection are studied respectively,and the electromagnetic wave propagation model in each scene is established,which provides a mathematical and physical knowledge framework for the subsequent experimental plan design.(2)The micro-motion signal detection and analysis based on picosecond pulses were carried out.Discuss the detection principle of single life body breathing signal from four aspects of clutter suppression,signal extraction,time-frequency transformation and target positioning;in view of the multipath effect caused by the complex environment in the detection of through-wall breathing,the digital low is used before the breathing signal extraction.Pass filter suppresses high-frequency clutter,and uses wavelet packet denoising method to filter out clutter signals close to the respiratory frequency;in the detection of dual life body respiratory signals,it searches for the two peaks with the largest Doppler spectrum frequency components The targets are separated and the targets on the two channels are matched according to the breathing rate.(3)Research on human respiratory signal measurement and error analysis.A single life body breath measurement experiment was used to compare the efficiency of different signal extraction methods.According to the breath measurement results of different postures of the human body,the human breath model in the time-domain ultra-wideband radar detection was corrected;low-pass filtering and wavelet packet removal were verified.The effect of noise on the stability and accuracy of the breathing detection results of the target through the wall;in the detection of the breathing signal of the dual life body,the breathing signals of the two living bodies can be clearly separated to obtain the breathing frequency and twodimensional position information of the target;Three aspects of source,transceiver antenna and sampling discussed the error items generated during measurement,and the best measurement plan was determined through comparative experiments.