Research On Life Parameter Detection Technology Based On Millimeter Wave Sensor

Millimeter wave is a new type of non-contact physiological signal detection method,which can detect the relevant life parameter signals generated by the human body due to cardiopulmonary activity.Compared with traditional ECG and pulse detectors,it is not only non-contact,but also has a certain penetrating ability,which can be detected through obstacles such as clothing and quilts.Compared with non-contact detectors such as infrared ray and laser,millimeter wave is less affected by the external weather environment and has the ability to work around the clock.The millimeter wave sensor has a small antenna size due to its high frequency,and can be used to construct a compact and cost-effective detection system.These advantages make the millimeter wave technology have application potential in the fields of medical diagnosis,health monitoring,disaster rescue,etc.,and therefore millimeter wave technology has important research value and significance.The detection and separation methods of human respiratory and heartbeat signals under FMCW system are studied in this thesis.The software and hardware design of the millimeter-wave sensor system is completed.Micro-displacement detection and target distance tracking are performed based on phase information.FIR digital filters and wavelet transform methods are used to separate breathing and heartbeat signals.Aiming at the interference of respiratory harmonics in the heartbeat signal,an adaptive filter-based respiratory harmonics suppression method is proposed.The main content of the full text is arranged as follows:Firstly,the domestic and foreign development status of non-contact life signal detection technology is investigated,and the advantages and disadvantages of existing methods and technologies are analyzed.Then,a physiological model for the detection of human life signals is established,which lays the foundation for detecting the life signals by using a small displacement of the human chest wall.The theory of FMCW radar detection is introduced in detail,and the method of detecting small displacement using phase change is deduced.In addition,based on the non-stationary and time-varying characteristics of respiratory and heartbeat signals,related weak signal detection algorithms are also introduced.Secondly,a highly integrated transceiver chip solution is adopted,and a 77 GHz millimeter wave sensor hardware system is designed with the transceiver antenna and peripheral circuits.The software configuration framework is designed according to the communication protocol of the chip.The influence of the related parameters of the transmission waveform on the detection effect is analyzed,then the configuration of the sawtooth waveform is completed by selecting the appropriate parameters.Before detecting the respiratory and heartbeat signals,a series of preprocessing work is performed on the IF signal,which includes tracking the target distance,extracting the phase information of the distance unit where the target is located,and writing an algorithm to phase expand the original signal to obtain the chest wall displacement information.On this basis,the FIR digital filter is used to initially separate the respiratory signal.Finally,the Coiflet wavelet basis function is selected and the wavelet transform is used to separate the heartbeat signal.The influence of breathing harmonics on the heartbeat signal is further discussed.A harmonic filtering algorithm based on the RLS adaptive filter is proposed.Simulation verification and detection of the actual heartbeat signal are performed.In addition,experiments are designed to compare the performance between this system and ordinary contact detection systems.Experimental results show that the life parameter detection system based on millimeter wave sensors in this thesis has strong real-time performance and accuracy.