Multi-person Heartbeat Detection And Positioning Based On SIMO Rada

In the field of human vital signs signal detection,non-contact vital signs radar has attracted more attention than video and infrared detection technology due to its advantages in long-term and stable detection.Therefore,it is more and more widely used in medical treatment,emergency rescue,indoor inspection and so on.In the above-mentioned detection scenarios,there are actually many targets.Therefore,multi-person vital sign signal detection based on vital signs radar is one of the current research hotspots.Based on a single-input multiple-output(SIMO)frequency modulated continuous wave(FMCW)radar system,this paper proposes a multi-person heartbeat signal detection algorithm.Through the sparse reconstruction imaging algorithm based on two-dimensional Doppler information,complete the two-dimensional space imaging and positioning of the human target,Then,according to the target position,the ZASLMS algorithm and the tensor decomposition algorithm are used to decompose the heartbeat signals of the human body from the vital signs of the human body.The work and research done in this paper are mainly as follows:(1)The basic principles of FMCW radar’s target detection and the hardware platform of the SIMO radar system in this paper are introduced,and the synchronization signal sampling is improved.Then it introduces the traditional vital sign signal processing method and the system flow of multi-person positioning and heartbeat detection used in this article.Finally,the SIMO radar array signal processing combined with the principle of DBF is introduced.(2)The traditional target imaging algorithm steps are introduced,and the shortcomings of the method are explained;a sparse reconstruction imaging algorithm based on two-dimensional range Doppler information is proposed.The algorithm performs sparse reconstruction based on the distance of the target and two-dimensional Doppler information,which can achieve the suppression of interfering moving targets and the two-dimensional imaging positioning of human targets.The measured data shows that the algorithm in this paper has better antiinterference and imaging effect than the traditional one-dimensional sparse reconstruction algorithm.(3)A multi-person heartbeat extraction algorithm is proposed,which is based on principal component analysis(PCA)for phase extraction,and the ZASLMS algorithm is used to accurately obtain the target heart rate of the human body;Then based on the tensor decomposition algorithm,the trajectory matrix is established based on the echo signals within the angle range of the thoracic cavity,and the vital sign signal is decomposed,and the human heartbeat signal is obtained according to the heart rate obtained by the ZASLMS algorithm.The actual test shows that,compared with the VMD signal decomposition algorithm,this algorithm can avoid modal aliasing and realize the effective acquisition of the time-domain waveform signal of the human target heartbeat.(4)An experimental platform for the SIMO radar system was built to conduct multi-person heartbeat detection experiments,which were verified by the experiments of two people at the same distance gate,two people at different distance gates,and three target detection experiments.The measured data shows that when two people are at the same distance door,the maximum root mean square relative error(RMSRE)of the heartbeat signal is 0.06,and the maximum average relative error(MRE)is 0.05.When two people are at different distance doors,the maximum RMSRE is 0.052,and the maximum MRE is 0.041.In the three-person experiment,the maximum RMSRE was 0.073,and the maximum MRE was 0.051.The human body test verifies the effectiveness of the system and algorithm in this paper.