Research On The Detection Of Vital Sign Based On UWB Radar

The rapid development of urbanization process has brought about some problems such as medical treatment,social security and so on,and how to solve these problems has become a hot topic for many scholars discuss and research.As a kind of important method,non-contact vital signal detection provides a research direction for solving this kind of problem.Because of its strong penetrating ability,anti-jamming and high resolution,UWB radar plays an important role in the field of non-contact vital signal detection.Therefore,it is of great significance to study the vital signal detection based on Ultra Wide-band radar in the field of non-contact vital signal detection.This paper from the signal processing,the pattern classification as the guiding ideology,according to the characteristics of signal patterns of each component of the signal,the signal detection of the direct wave,the identification of multiple targets,the separation and reorganization of the target signal are studied.The general technical route of this paper is provided by analyzing the main technical route and typical algorithm on vital signal detection.The main contents of this paper mainly involve the following aspects.Firstly,this paper reviews several typical non-contact detection methods and detection algorithms based on radar,and compares their advantages and disadvantages,and analyzes the characteristics of UWB radar in the vital signal detection based on the analysis of UWB radar system,as well as establishes the vital signal model.At the same time,two algorithms for the quality evaluation criteria are summarized and the quality of the algorithm is evaluated from the perspective of the whole and the local point of view.Secondly,the direct wave is analyzed and the mathematical model of direct wave is established,and the direct wave suppression algorithm based on Karhunen-Loeve(K-LT)transform with FastICA(Fast Independent Component Analysis)is proposed.The effectiveness of the proposed method in direct wave suppression is verified by the experimental study on the single stationary target and single moving target.The superiority of the algorithm in the iterative speed and computational complexity is proved by comparing the objective performance between ICA with K-L,such as the iteration times,the running time,the C/I,the S/N and so on.Thirdly,a signal extraction algorithm based on Ensemble EMD(EEMD)and BP optimization algorithm is proposed according to the analysis of traditional signal extraction methods for the respiratory and heartbeat of the vital sign,aiming at the poor quality of the traditional EEMD reconstruction signal and the shortcomings of the traditional EMD method,such as the endpoint leap,as well as the extraction of one man's vital signal was studied.Experimental results show that the proposed algorithm not only can overcome the endpoint extension problem of EMD,but also improves the signal to noise ratio of the reconstructed signal.And,it is proved that the algorithm is suitable for the extraction of the signal components in the signal.Finally,the theoretical derivation of Multiple Signal Classification(MUSIC)is made by analyzing the characteristics of multi target human signals and constructing a double signal model.On this basis,this paper proposed a theoretical model and algorithm implementation steps of MUSIC.In this paper,experimental on the single and double stationary human target signals are made.The experimental results show that the proposed method can effectively identify the number of human target signals,especially in the aspect of multiple human target signal recognition,and it has the advantages of high resolution and strong anti-interference ability.