Multi-body vital signs synchronous monitoring system and method based on millimeter wave sensing

Abstract

A system and method for synchronously monitoring vital signs of multiple human bodies based on millimeter wave sensing, comprising: a millimeter wave radar front-end module, a microcontroller, a processor, and a display and recording module, wherein: the millimeter wave radar front-end module is used to transmit linear frequency modulated continuous wave microwave or millimeter wave signals, and receive reflected echo signals to generate multi-channel intermediate frequency baseband signals, the microcontroller sets and controls waveform parameters, transmission power and signal gain parameters and monitoring processes, sets and controls acquisition parameters of the signal acquisition module of the processor, the processor extracts vital sign parameter information of the human body from the multi-channel intermediate frequency baseband signal, and the display and recording module displays and saves information obtained by the processor, including: multiple human position information, chest wall micro-displacement information and vital sign parameters. The present invention provides a non-contact vital sign monitoring system and method with high measurement accuracy, strong anti-interference ability, and reliable and stable for synchronous monitoring of vital signs of multiple human bodies.

Description

Technical Field

[0001] The present invention relates to a technology in the field of medical detection, specifically a system and method for synchronously monitoring multiple human vital signs based on millimeter wave sensing. Background Art

[0002] Traditional vital sign monitoring instruments are mostly used in clinical medicine, using contact sensors such as light, electricity, and pressure to detect the heart rate and respiratory rate of the human body. Contact vital sign monitoring methods represented by existing medical electrocardiographs (ECGs) and wearable health monitoring devices require the sensor to contact the body parts, which inevitably causes tension and discomfort to the subject, resulting in measurement errors and is not suitable for long-term monitoring. Laser-based non-contact measurement methods cannot be blocked by clothing, and their applicable scenarios are limited; in existing microwave vital sign monitoring methods, continuous wave Doppler radars have no distance resolution capability and cannot monitor multiple subjects simultaneously. Frequency modulated continuous wave radars are limited by the transmission bandwidth, and there is mutual coupling interference in the vital sign monitoring of multiple human targets, especially when the distance between multiple targets is relatively close, resulting in huge measurement errors. When two or more human targets are in the same distance unit, there will be serious aliasing interference, resulting in monitoring failure. In addition, since microwave or millimeter wave radar vital signs monitoring is achieved by sensing the chest wall ups and downs caused by human cardiopulmonary activity, and the chest wall ups and downs caused by breathing and heartbeat are superimposed on each other, and since the radar beam has a large range, the existing technology can only test the average result of the human chest wall ups and downs movement, resulting in the weak heartbeat component being difficult to accurately and reliably extract. Accurate and stable heart rate monitoring has always been a difficult technical problem to overcome. Summary of the invention

[0003] In view of the shortcomings of existing vital sign monitoring methods that are unable to achieve synchronous monitoring of multiple human bodies and accurate extraction of vital signs, and the problems of coupling interference of multiple adjacent human targets and aliasing interference of multiple human targets at the same distance in existing microwave measurement methods, the present invention proposes a synchronous monitoring system and method for multiple human vital signs based on millimeter wave sensing, providing a non-contact vital sign monitoring system and method with high measurement accuracy, strong anti-interference ability, reliability and stability for synchronous monitoring of multiple human vital signs.

[0004] The present invention is achieved through the following technical solutions:

[0005] The present invention relates to a multi-body vital sign synchronous monitoring system based on millimeter wave perception, comprising: a millimeter wave radar front-end module, a microcontroller, a processor and a display and recording module, wherein: the millimeter wave radar front-end module is used to repeatedly transmit linear frequency modulated continuous wave (LFMCW) microwave or millimeter wave signals, and receive reflected echo signals, generate multi-channel intermediate frequency baseband signals and output them to the processor, the microcontroller respectively sets and controls the waveform parameters, transmission power and signal gain parameters of the millimeter wave radar front-end module and the monitoring process, sets and controls the acquisition parameters of the signal acquisition module of the processor, and the processor extracts multi-body position information, chest wall micro-displacement information and vital sign parameter information from the multi-channel intermediate frequency baseband signals, and the display and recording module displays and saves them.

[0006] The millimeter wave radar front-end module comprises: an LFMCW signal source, a power divider, a power amplifier, a low noise amplifier, a mixer, a low pass filter, at least one transmitting antenna and a plurality of receiving antennas, wherein: the signal of the LFMCW signal source is connected to the transmitting antenna through the power amplifier and transmitted by the transmitting antenna; the receiving antenna receives the reflected signal and transmits it to the mixer through the low noise amplifier; the mixer mixes the signal transmitted by the low noise amplifier with the signal of another LFMCW signal source after passing through the power divider, and outputs a multi-channel intermediate frequency baseband signal after being processed by the low pass filter.

[0007] The number of equivalent receiving channels of the radar front end is equal to the product of the number of effective transmitting antennas and receiving antennas.

[0008] The processor includes: a signal acquisition module and a signal processing module, wherein: the signal acquisition module receives a multi-channel intermediate frequency baseband signal from a millimeter wave radar front-end module and acquisition parameters from a microcontroller, and the signal processing module is used to realize the positioning and thermal map position index processing of a single or multiple human targets, the extraction of time domain information of human chest wall micro-displacement, and the extraction of vital sign parameters.

[0009] The present invention relates to a millimeter wave multi-human body vital sign synchronous monitoring method based on the above monitoring system. The method comprises the following steps: setting the transmitting beam of a millimeter wave radar front-end module toward a detection area, synchronously collecting multi-channel multi-channel intermediate frequency baseband signals, extracting a distance-angle image heat map of the detection area, locating the position and index of each human chest in the distance-angle image heat map in the field of view according to characteristic frequency information of human breathing and heartbeat, extracting and inverting micro-motion information in a distance-angle joint dimension, measuring the micro-motion displacement time domain information of each human chest wall, finally estimating the breathing and heartbeat frequencies of each human body, and realizing synchronous monitoring of the vital signs of multiple human bodies.

[0010] The multi-channel multi-channel intermediate frequency baseband signal is specifically: the radar intermediate frequency baseband signal C = [S1, S2, ... SM ], where: M is the number of equivalent receiving channels of the millimeter wave radar front-end module, and the baseband signal S of the mth channel m is [s(1,m),s(2,m),…s(N,m)] T , N is the total number of baseband signal samples for each channel within a single transmission cycle.

[0011] The distance-angle image heat map of the area to be measured is obtained by performing a two-dimensional fast Fourier transform on the signal matrix C composed of the radar intermediate frequency baseband signal, that is, performing a fast Fourier transform on each column of the baseband signal of the matrix C to obtain the distance image information matrix C of all objects in the range to be measured. F , then for the matrix C F Perform fast Fourier transform on each row to obtain the angle image information matrix C of all objects within the detection range FF , the distance-angle image heat map of the area to be measured is obtained by taking the modulus value. Based on the heat map, the distance-angle image positioning of each human target in the measurement area is realized by extreme value search.

[0012] The chest wall position of each human body is accurately located by one or a combination of the following methods:

[0013] A) After generating a three-dimensional matrix through the distance-angle image heat map of the area to be measured, the successive cycle difference method is used to eliminate the interference of static targets in the surrounding environment and identify the heat map information of the human chest wall;

[0014] B) After generating a three-dimensional matrix through the distance-angle image thermal map of the area to be measured, the three-dimensional matrix is ​​successively subtracted along the direction of the multi-emission cycle, and the calculated new matrix is ​​band-pass filtered and periodically accumulated to accurately locate the distance-angle image thermal map of the human chest wall position in the field of view.

[0015] The three-dimensional matrix is ​​obtained by selecting the distance-angle image heat map obtained by K emission cycles

[0016] The successive cyclic difference method is: for the three-dimensional matrix C K The difference processing is performed every L emission cycles, and then the distance-angle image heat map highlighting the position of the human chest is obtained by accumulation along the emission cycle direction to obtain the corresponding position index.

[0017] The bandpass filtering means: setting the upper and lower cutoff frequencies of the bandpass filter according to the frequency range of human vital signs (f1, f2), and performing the difference operation on the new matrix D K Take the modulus and perform bandpass filtering along the transmission period direction to obtain a three-dimensional matrix

[0018] The periodic accumulation refers to: for the three-dimensional matrix Accumulation is performed along multiple emission cycles to realize the distance-angle image information and its index of the human chest wall, especially the heartbeat position.

[0019] The method for extracting time domain information of micro-displacement of human chest wall is to extract the distance-angle image heat map position information (k q ,p q ), where: k q and p q are the distance dimension index and angle dimension index of the qth person to be tested, respectively. The chest wall micro-displacement information of the qth person to be tested in the i-th transmission cycle is extracted by the following formula: Where: T is the radar repetitive transmission period, arg[·] is the complex phase angle calculation, s i (·) is the multi-channel discrete baseband signal of the i-th transmission period, N fft is the number of points of the first dimension transformation in the two-dimensional fast Fourier transform, M fft is the number of points transformed in the second dimension in the two-dimensional fast Fourier transform, and λ is the wavelength of the radar transmitting carrier.

[0020] The method for estimating the breathing and heart rate of each human body refers to: based on the extracted time domain information of the chest wall micro-displacement of each person to be tested, the information including the breathing rate and heart rate of each person to be tested is estimated through a sliding window using methods including: signal decomposition, filtering processing and spectrum analysis, autocorrelation analysis, and time-frequency analysis.

[0021] Technical Effects

[0022] The present invention comprehensively solves the problems of the prior art of human vital signs monitoring based on microwave or millimeter wave radar, especially the difficulty in accurately, stably and reliably monitoring the heartbeat frequency of multiple human vital signs monitoring, as well as the coupling and aliasing interference problems of multiple human targets in proximity, which makes it impossible to achieve accurate multi-human vital signs monitoring.

[0023] Compared with the prior art, the present invention adopts a single-shot or multi-shot multi-receiver radar to realize multi-body positioning and chest wall micro-motion information measurement in the distance-angle joint dimension. Through the demodulation and phase evolution tracking in the distance-angle joint dimension, it solves the mutual coupling interference of multiple human targets, especially adjacent targets, and the aliasing interference of multiple human targets in the same distance unit, and realizes the synchronous monitoring of multiple human vital signs, greatly improving the measurement accuracy of human vital sign parameters. In addition, the chest wall, especially the distance angle image heat map of the chest wall corresponding to the heartbeat, can be significantly highlighted through the successive cycle difference and bandpass filter period accumulation method, laying the foundation for accurately and reliably extracting the micro-motion time domain information of the chest wall of multiple human bodies, and greatly improving the accurate and stable monitoring capability of weak heartbeat signals. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a schematic diagram of the system of the present invention;

[0025] Figure 2 It is a structural schematic diagram of the millimeter wave radar front end of the present invention;

[0026] Figure 3 Testing scene graph for implementation example;

[0027] Figure 4 It is a flow chart of the present invention;

[0028] Figure 5 It is a heat map of the distance-angle image of the chest position of multiple human bodies in the area to be tested;

[0029] Figure 6 Schematic diagram of time domain information of chest movement displacement of three test persons measured in the embodiment;

[0030] Figure 7 Schematic diagram of the breathing and heart rate variation curves of three test persons extracted in the embodiment; DETAILED DESCRIPTION

[0031] like Figure 1 As shown, the present embodiment relates to a multi-human vital signs synchronous monitoring system based on millimeter wave sensing, including: a millimeter wave radar front-end module, a microcontroller, a processor for collecting multi-channel intermediate frequency baseband signals, and processing and extracting vital sign parameter information of a single or multiple human bodies, and a display and recording module, wherein: the millimeter wave radar front-end module is used to repeatedly transmit linear frequency modulated continuous wave (LFMCW) microwave or millimeter wave signals, and receive reflected echo signals to generate multi-channel intermediate frequency baseband signals, and the microcontroller sets and controls the waveform parameters, transmission power and signal gain parameters of the millimeter wave radar front end and the monitoring process, and sets and controls the acquisition parameters of the signal acquisition module of the processor.

[0032] like Figure 2As shown, the millimeter wave radar front end includes: an LFMCW signal source, a power divider, a power amplifier, a low noise amplifier, a mixer, a low pass filter, a transmitting antenna and a receiving antenna, wherein: the LFMCW signal source is connected to the power divider, one end of the power divider is connected to the power amplifier, and the other end is connected to the mixer; the power amplifier is connected to the transmitting antenna, the receiving antenna is connected to the low noise amplifier, the low noise amplifier is connected to the mixer, and the output end of the mixer is connected to the low pass filter; the signal of the LFMCW signal source is divided into two paths through the power divider, one path is connected to the transmitting antenna through the power amplifier and transmitted by the transmitting antenna; the receiving antenna receives the reflected signal and transmits it to the mixer through the low noise amplifier; the mixer mixes the microwave signal transmitted by the low noise amplifier with the other microwave signal after passing through the power divider, and outputs a multi-channel intermediate frequency baseband signal after being processed by the low pass filter.

[0033] There are multiple receiving antennas and at least one transmitting antenna.

[0034] The number of equivalent receiving channels of the radar front end is equal to the product of the number of effective transmitting antennas and receiving antennas. Based on the multiple transmission and multiple reception mode, a higher angle resolution capability can be achieved under a smaller antenna aperture.

[0035] The number of power amplifiers in the power divider is the same as the number of transmitting antennas.

[0036] The number of the low noise amplifiers and mixers is the same as the number of receiving antennas.

[0037] The processor includes: a signal acquisition module and a signal processing module, wherein: the signal acquisition module is used to synchronously acquire multi-channel intermediate frequency baseband signals of multiple channels, and the signal processing module is used to realize the positioning of a single or multiple human targets and their chest walls, especially the positioning of the chest wall position corresponding to the heartbeat and the heat map position index processing, and the extraction of time domain information of human chest wall micro-displacement based on the distance-angle joint dimension and the extraction of time domain information based on chest wall micro-displacement to obtain vital sign parameters.

[0038] The vital sign parameters include breathing information and heartbeat information.

[0039] The display and recording module displays and saves the information obtained by the processor, including: multiple human body position information, chest wall micro-displacement information and vital sign parameters.

[0040] like Figure 3 As shown, this embodiment involves a scenario of synchronous monitoring of multiple human vital signs based on the above system. Three persons to be tested sit side by side, and the transmitting beam of the millimeter-wave radar front-end module illuminates the entire area to be tested.

[0041] like Figure 4As shown, this embodiment relates to a method for synchronously monitoring multiple human vital signs based on millimeter wave sensing, including the following steps:

[0042] Step 1: Set the transmission beam of the millimeter-wave radar front-end module toward the area to be measured, configure the perception system parameters, control the continuous transmission and reception of millimeter-wave radar signals, and at the same time, the signal acquisition module of the processor collects the multi-channel intermediate frequency baseband signal C = [S1, S2, ... S M ], where: M is the number of equivalent receiving channels at the radar front end, and the baseband signal S of the mth channel in each transmission cycle time is m is [s(1,m),s(2,m),…s(N,m)] T , where: N is the total number of baseband signal samples for each channel within a single transmission cycle.

[0043] Step 2: Process the multi-channel intermediate frequency baseband signal to obtain the distance-angle image heat map of the area to be measured: Perform a two-dimensional fast Fourier transform on the multi-channel intermediate frequency baseband signal matrix C obtained in step 1. First, perform a fast Fourier transform on each column of the baseband signal in the matrix C to obtain the distance image information of all objects in the range to be measured, that is, the matrix C F , then for the matrix C F Perform fast Fourier transform on each row of the matrix to obtain the angle image information of all objects within the measurement range, that is, the matrix C FF The distance-angle image heat map of the area to be measured is obtained by taking the modulus value. Based on the heat map, the distance-angle image positioning of all targets in the measurement scene is achieved through extreme value search.

[0044] Step 3, locating the position and index of each human chest wall in the field of view in the distance-angle image heat map according to the characteristic frequency information of human breathing and heartbeat, specifically includes:

[0045] Step 3.1: Select the distance-angle image heat map obtained from a certain K emission cycles to obtain a three-dimensional matrix The choice of K value can be determined according to the length of sampling time and emission period.

[0046] Step 3.2, during normal cardiopulmonary activity, the chest wall moves slightly back and forth, and the surrounding environment is relatively static. In addition, the frequency range of human breathing is about 0.2-0.35Hz, the range of heart rate is about 0.9-1.6Hz, and the amplitude of chest wall micro-motion caused by breathing is about 10 times that caused by heartbeat, and the heartbeat component is very weak. In order to effectively extract vital signs, it is necessary to accurately locate the chest wall position of each subject, and accurate positioning can be achieved by one of the following methods or a combination thereof:

[0047] A) After generating a three-dimensional matrix through the distance-angle image heat map of the area to be measured, the successive cycle difference method is used to eliminate the interference of static targets in the surrounding environment and identify the heat map information of the chest wall position of the human body. The successive cycle difference method refers to: K The difference processing is performed every L (L = 1, 2, ...) emission cycles, and then accumulated along the emission cycle direction to obtain the distance-angle image heat map that highlights the position of the human chest cavity, and obtain the corresponding position index. This method can effectively identify static targets and static parts of the human body, highlight the position information of the human chest wall, and lay the foundation for the subsequent extraction of time domain information of micro-motion of multiple human chest walls.

[0048] B) After generating a three-dimensional matrix through the distance-angle image heat map of the area to be measured, the three-dimensional matrix is ​​successively subtracted along the direction of the multi-emission cycle, that is, the three-dimensional matrix C K The difference processing is performed every one or more transmission cycles to obtain a new matrix D K , where: D K (:,:,i)=C K (:,:,i+L)-C K (:,:,i), i is the serial number of the transmission cycle. K Take the modulus and perform bandpass filtering along the transmission period direction to obtain a three-dimensional matrix In actual use, bandpass filtering can be performed along the transmission cycle direction according to the possible heat map position of the human body. In order to monitor weak heartbeat frequency, the upper and lower cutoff frequencies of the bandpass filter are set according to the frequency range of the human heartbeat frequency to accurately locate the heat map index corresponding to the chest wall position where the heartbeat is located. Accumulation is performed along the transmission cycle direction to realize the distance-angle image information and index of the human chest wall, especially the heartbeat position. This operation greatly improves the ability to extract weak heartbeat signals and lays the foundation for solving the problem of average effect of chest wall micro-displacement extraction in heart rate monitoring. Figure 3 As shown, the distance-angle image heat map of the chest positions of multiple human bodies in the field of view obtained in the measurement scene in this embodiment.

[0049] Step 4, extracting the time domain information of the micro-displacement of the chest wall of each person to be tested in the field of view, specifically including:

[0050] Step 4.1: Determine the chest position information (k q ,p q ), where: k q and p q are the distance dimension index and angle dimension index of the qth person to be tested respectively;

[0051] Step 4.2, extract the time domain information of the chest wall micro-displacement of the qth person to be tested in the i-th transmission cycle: Where: T is the radar repetitive transmission period, arg[·] is the complex phase angle calculation, s i (·) is the multi-channel discrete baseband signal of the i-th transmission period, N fft is the number of points of the first dimension transformation in the two-dimensional fast Fourier transform, M fft is the number of points transformed in the second dimension in the two-dimensional fast Fourier transform, and λ is the wavelength of the radar transmitting carrier.

[0052] like Figure 4 As shown in the figure, T=10ms and the transmission bandwidth is 3GHz, and the time domain waveforms of the micro-motion displacement of the chest wall of the three persons to be measured are measured in this embodiment. Through the demodulation and phase evolution tracking of the distance-angle joint dimension, the coupling and aliasing interference of multiple human bodies in proximity are effectively eliminated, and the chest wall micro-motion information caused by the cardiopulmonary activities of each human target is greatly improved.

[0053] Step 5, extracting the breathing and heart rate of each human body, specifically including:

[0054] For the time domain information of chest wall micro-displacement of each person to be tested obtained in step 4, the information including respiratory rate and heart rate of each person to be tested is estimated through a sliding window using methods including signal decomposition, filtering processing, spectrum analysis, autocorrelation analysis, and time-frequency analysis.

[0055] For example, using a time length of T W =15s sliding window for sliding interception, through autocorrelation analysis, according to the human body's breathing and heart rate range, extract the breathing and heart rate within each sliding window. Figure 5 As shown, the breathing and heart rate change curves of the three subjects in the test scenario are as a function of time.

[0056] The above-mentioned specific implementation can be partially adjusted in different ways by those skilled in the art without departing from the principle and purpose of the present invention. The protection scope of the present invention shall be based on the claims and shall not be limited by the above-mentioned specific implementation. Each implementation scheme within its scope shall be subject to the constraints of the present invention.

Claims

1. A multi-human vital signs synchronous monitoring system based on millimeter wave sensing, characterized in that: include: Millimeter-wave radar front-end module, microcontroller, processor and display and recording module, wherein: the millimeter-wave radar front-end module is used to repeatedly transmit linear frequency-modulated continuous wave millimeter-wave signals, receive reflected echo signals, generate multi-channel intermediate frequency baseband signals and output them to the processor, the microcontroller sets and controls the waveform parameters, transmission power and signal gain parameters of the millimeter-wave radar front-end module and the monitoring process, and sets and controls the acquisition parameters of the signal acquisition module of the processor, the processor extracts the distance-angle image heat map of the area to be measured from the multi-channel intermediate frequency baseband signal, and then locates the distance-angle image heat map position and index corresponding to the chest wall position where each human heartbeat is located in the field of view according to the characteristic frequency information of human breathing and heartbeat, and realizes micro-motion information extraction and inversion based on the demodulation and phase evolution tracking of the distance-angle joint dimension, and measures the time domain information of the micro-motion displacement of each human chest wall, and finally obtains the vital sign parameter information and is displayed and saved by the display and recording module; The method for extracting time domain information of micro-displacement of human chest wall is as follows: according to the distance-angle image heat map position information (k q ,p q ), where: k q and p q are the distance dimension index and angle dimension index of the qth person to be tested, respectively. The chest wall micro-displacement information of the qth person to be tested in the i-th transmission cycle is extracted by the following formula: Where: T is the radar repetitive transmission period, arg[·] is the complex phase angle calculation, s i (·) is the multi-channel discrete baseband signal of the i-th transmission period, N fft is the number of points of the first dimension transformation in the two-dimensional fast Fourier transform, M fft is the number of points transformed in the second dimension of the two-dimensional fast Fourier transform, λ is the wavelength of the radar transmitting carrier, M is the number of equivalent receiving channels of the millimeter-wave radar front-end module, N is the number of sampling points of the baseband signal of each channel, m is the index of the equivalent receiving channel, n is the index of the sampling point, 0≤m≤M-1, 0≤n≤N-1.

2. The multi-human vital signs synchronous monitoring system based on millimeter wave sensing according to claim 1 is characterized in that: The millimeter wave radar front-end module comprises: an LFMCW signal source, a power divider, a power amplifier, a low noise amplifier, a mixer, a low pass filter, at least one transmitting antenna and a plurality of receiving antennas, wherein: the signal of the LFMCW signal source is connected to the transmitting antenna through the power amplifier and transmitted by the transmitting antenna; the receiving antenna receives the reflected signal and transmits it to the mixer through the low noise amplifier; the mixer mixes the signal transmitted by the low noise amplifier with another LFMCW signal source signal after passing through the power divider, and outputs a multi-channel intermediate frequency baseband signal after being processed by the low pass filter.

3. The multi-human vital signs synchronous monitoring system based on millimeter wave sensing according to claim 2 is characterized in that: The number of equivalent receiving channels of the millimeter wave radar front-end module is equal to the product of the number of effective transmitting antennas and receiving antennas.

4. The multi-human vital signs synchronous monitoring system based on millimeter wave sensing according to claim 1 is characterized in that: The processor includes: a signal acquisition module and a signal processing module, wherein: the signal acquisition module receives a multi-channel intermediate frequency baseband signal from a millimeter wave radar front-end module and acquisition parameters from a microcontroller, and the signal processing module is used to realize the positioning and thermal map position index processing of a single or multiple human targets, the extraction of time domain information of human chest wall micro-displacement, and the extraction of vital sign parameters.

5. A millimeter wave multi-human vital signs synchronous monitoring method based on the system described in any one of claims 1 to 4, characterized in that: By setting the transmitting beam of the millimeter-wave radar front-end module toward the area to be measured, multi-channel intermediate frequency baseband signals are synchronously collected to extract the distance-angle image heat map of the area to be measured. Then, the distance-angle image heat map position and index corresponding to the chest wall position where the heartbeat of each human body in the field of view is located according to the characteristic frequency information of human breathing and heartbeat. Based on the extraction and inversion of micro-motion information in the distance-angle joint dimension, the time domain information of the micro-motion displacement of the chest wall of each human body is measured, and finally the breathing and heartbeat frequencies of each human body are estimated to realize the synchronous monitoring of the vital signs of multiple human bodies.

6. The millimeter wave multi-human vital signs synchronous monitoring method according to claim 5 is characterized in that: The multi-channel intermediate frequency baseband signal is specifically: radar intermediate frequency baseband signal C = [S1, S2, ... S M ], where: M is the number of equivalent receiving channels of the millimeter wave radar front-end module, and the baseband signal S of the mth channel in each repeated transmission cycle time is m is [s(1,m),s(2,m),…s(N,m)] T , N is the number of sampling points of baseband signal for each channel.

7. The millimeter wave multi-human vital signs synchronous monitoring method according to claim 5 is characterized in that: The distance-angle image heat map of the area to be measured is obtained by performing a two-dimensional fast Fourier transform on the signal matrix C composed of the radar intermediate frequency baseband signal, that is, performing a fast Fourier transform on each column of the baseband signal of the matrix C to obtain the distance image information matrix C of all objects in the range to be measured. F , then for the matrix C F Perform fast Fourier transform on each row to obtain the angle image information matrix C of all objects within the detection range FF , the distance-angle image heat map of the area to be measured is obtained by taking the modulus value. Based on the heat map, the distance-angle image positioning of each human target in the measurement area is realized through extreme value search.

8. The millimeter wave multi-human vital signs synchronous monitoring method according to claim 5 is characterized in that: The chest wall position of each human body is accurately located by one or a combination of the following methods: A) After generating a three-dimensional matrix through the distance-angle image heat map of the area to be measured, the successive cycle difference method is used to eliminate the interference of static targets in the surrounding environment and identify the heat map information of the human chest wall; B) After generating a three-dimensional matrix through the distance-angle image thermal map of the area to be measured, the three-dimensional matrix is ​​successively subtracted along the direction of the multi-emission cycle, and the calculated new matrix is ​​band-pass filtered and periodically accumulated to accurately locate the distance-angle image thermal map of the human chest wall position in the field of view.

9. The millimeter wave multiple human vital signs synchronous monitoring method according to claim 8 is characterized in that: The three-dimensional matrix is ​​obtained by selecting the distance-angle image heat map obtained by K emission cycles.

10. The millimeter wave multiple human vital signs synchronous monitoring method according to claim 8 is characterized in that: The successive cyclic difference method refers to: K The difference processing is performed every L transmission cycles. L = 1, 2, ..., and then accumulate along the emission period direction to obtain a distance-angle image heat map highlighting the position of the human chest cavity, and obtain the corresponding position index.

11. The millimeter wave multi-human vital signs synchronous monitoring method according to claim 5 is characterized in that: The method for estimating the breathing and heart rate of each human body refers to: based on the extracted time domain information of the chest wall micro-displacement of each person to be tested, the information including the breathing rate and heart rate of each person to be tested is estimated through a sliding window using methods including: signal decomposition, filtering processing and spectrum analysis, autocorrelation analysis, and time-frequency analysis.

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