Multi-person Vital Signs Detection Based On Digital Beamforming

Non-contact vital sign detection technology can be used to detect human vital signs without contacting the human body,and has been applied to disaster rescue,daily health detection and other fields.The vital signs detection based on Doppler radar has the advantages of non-contact and penetrability.This technology can detect cardiopulmonary activity parameters and blood pressure of the living body,but there are still some difficulties that need to be overcome,such as high-precision heartbeat detection and body motion elimination,multi-person vital signs detection,and so on.Among them,multi-person vital signs detection is one of the hot spots in the field of non-contact vital signs detection.At present,the main technology is analog beamforming,but there are disadvantages such as poor anti-interference performance and low flexibility.In response to these problems,this paper uses digital beamforming technology to implement multi-person vital sign detection.The main work and research content are summarized as follows:(1)The principle of detecting vital sign signals by CW radar system is introduced.A narrowband signal model is established,the Capon beamforming algorithm is introduced,and two classic robust beamforming algorithms are discussed.The performances of the algorithm are analyzed through simulation results.(2)According to the application requirements of multi-person vital signs detection,the system structure is determined,multiple parameters of the radar transceiver link are studied,and a single input multiple output(SIMO)radar system is designed.The SIMO system includes many modules such as array antennas,orthogonal receivers,and baseband sampling,which can detect vital sign signals in the range of 1?4m.After testing,the single-channel receiver can accurately detect the human breathing signal,and the amplitude and phase correction algorithm can effectively correct each receiving channel.(3)For the multi-person vital signs detection scenario,this paper proposes two multi-person vital signs detection algorithms: a spatial integral-based echo signal steering vector estimation algorithm and an angular signal-constrained echo signal steering vector estimation algorithm.The steering vector estimation algorithm based on space integration first reconstructs the echo signal covariance matrix through space integration to obtain the preliminary estimate of the target signal steering vector,and then obtains the accurate target signal steering vector by solving the linear constraint quadratic programming problem.The steering vector estimation algorithm based on angular region constraints is to construct a quadratic constraint quadratic programming problem,and the solution of the convex optimization problem is an accurate estimate of the steering vector.Then the interference and noise covariance matrices are reconstructed according to the steering vector of each target signal,and the beam vector is used to obtain the weight vector.Simulation experiments show that under various error conditions,the proposed algorithm has a higher output signal-tointerference and noise ratio than traditional algorithms.(4)This article sets up an experimental platform for the SIMO radar system to detect the vital signs of multiple people,and conducts experimental verification for the detection of vital signs of two or three people.The experimental results show that the frequency of the respiratory signal measured by this system is basically the same as the reference signal when detecting the vital signs of multiple people,and the error is within 0.062.