Physical sign monitoring method and device, equipment and storage medium

Abstract

The invention discloses a physical sign monitoring method and device, equipment and a storage medium, and the method comprises the steps: obtaining n target signals and azimuth angles corresponding to a target object, the n target signals corresponding to n signal receiving channels; determining n first steering vectors corresponding to the n signal receiving channels according to the azimuth angle; performing gain compensation on each first steering vector based on the gain of each signal receiving channel to obtain n second steering vectors; determining n weights in beam forming processing according to the n second steering vectors; performing beam forming processing on the n target signals based on the n weights to obtain an output signal corresponding to the target object; and performing physical sign monitoring on the target object according to the output signal. According to the scheme, when the weight of the beam forming algorithm is determined, the actual gains of different signal receiving channels are considered, so that the beam forming algorithm can still achieve an expected effect under the condition of non-uniform gains, and the accuracy of sign monitoring can be ensured.

Description

Technical Field

[0001] The present application relates to the technical field of health monitoring, and particularly to a physical sign monitoring method, device, equipment and storage medium. Background Technique

[0002] Using microwave radar for physical sign monitoring has the characteristic of realizing physical sign monitoring without physical contact with the object to be measured, and has been widely applied in aspects such as home and medical health monitoring, driver vital status monitoring, etc. Compared with single-object physical sign monitoring, multi-object physical sign monitoring can greatly improve the monitoring efficiency and has become the research focus in recent years.

[0003] In multi-target physical sign detection, in order to separate the physical sign components of different objects, related technologies usually adopt beamforming methods (for example, algorithms such as least squares beamforming, minimum variance distortionless response (MVDR) beamforming, etc.) to obtain signals in a specified direction and suppress signals in other interference directions. And no matter which beamforming algorithm is adopted, the steering vector needs to be used in the calculation process of the beamforming weight.

[0004] However, in related technologies, the steering vector is usually determined on the basis of the default that the gains of each channel of the radar are the same, without considering that in actual applications, the gain distribution of each channel of the radar may be uneven, resulting in the possible failure of the above beamforming algorithms and the inability to achieve the effect of suppressing interference.

[0005] Application Content

[0006] The main purpose of the present application is to provide a physical sign monitoring method, device, equipment and storage medium, aiming to solve the technical problem that the beamforming algorithm fails because the uneven gain distribution of each channel of the radar is not considered when determining the steering vector in related technologies.

[0007] To achieve the above purpose, the present application provides a physical sign monitoring method, and the method includes:

[0008] Obtain n target signals and azimuth angles corresponding to a target object, where the n target signals correspond to n signal receiving channels one by one, and n is a positive integer greater than or equal to 2;

[0009] Determine n first steering vectors corresponding to the n signal receiving channels according to the azimuth angles corresponding to the target object;

[0010] Perform gain compensation on each of the first steering vectors corresponding to each signal receiving channel in the n signal receiving channels to obtain n second steering vectors;

[0011] Determine n weights in the beamforming process according to the n second steering vectors;

[0012] Perform beamforming processing on the n target signals based on the n weights to obtain the output signal corresponding to the target object;

[0013] Perform physical sign monitoring on the target object according to the output signal corresponding to the target object.

[0014] Optionally, the step of performing gain compensation on each corresponding first steering vector based on the gain of each signal receiving channel in the n signal receiving channels includes:

[0015] Determine n gains corresponding to the target object on the n signal receiving channels;

[0016] Respectively use the n gains as multiplication factors to compensate into the n first steering vectors.

[0017] Optionally, the step of determining n gains corresponding to the target object on the n signal receiving channels includes:

[0018] Look up and determine the corresponding gain in a preset table according to the azimuth angle corresponding to the target object and the serial number of each signal receiving channel, where the preset table includes the corresponding relationship between the azimuth angle, the serial number of the signal receiving channel, and the gain.

[0019] Optionally, the preset table is generated in the following manner:

[0020] In a microwave anechoic chamber, obtain the echo signals of n signal receiving channels of the radar when the corner reflector is at various azimuth angles;

[0021] Determine the gains of the n signal receiving channels when the corner reflector is at various azimuth angles according to the echo signals of the n signal receiving channels when the corner reflector is at various azimuth angles;

[0022] Generate the preset table according to the gains of the n signal receiving channels when the corner reflector is at various azimuth angles.

[0023] Optionally, before the step of obtaining n target signals corresponding to the target object, the method further includes:

[0024] Obtain the distance of the target object;

[0025] Obtain n input signals corresponding to the target object, where the n input signals correspond one-to-one to the n signal receiving channels, and the input signal is a signal obtained by performing mixing processing on the echo signal received by the signal receiving channel;

[0026] Window each input signal and perform fast Fourier transform (FFT) in the range dimension to obtain the frequency-domain signal corresponding to each input signal;

[0027] Extract the n frequency-domain signals corresponding to the target object according to the distance of the target object to obtain the n target signals corresponding to the target object.

[0028] Optionally, the step of performing physical sign monitoring on the target object according to the output signal corresponding to the target object includes:

[0029] Perform DC removal, phase extraction, and phase unwrapping on the output signal corresponding to the target object to obtain the phase corresponding to the target object;

[0030] Perform windowing in the slow-time dimension and FFT processing on multiple frames of the phase corresponding to the target object to obtain the physical sign change condition of the target object.

[0031] This application also provides a physical sign monitoring device, and the device includes:

[0032] An acquisition module, configured to acquire n target signals and an azimuth angle corresponding to a target object, where the n target signals correspond one-to-one to n signal receiving channels, and n is a positive integer greater than or equal to 2;

[0033] A physical sign monitoring module, configured to determine n first steering vectors corresponding to the n signal receiving channels according to the azimuth angle corresponding to the target object; perform gain compensation on each of the corresponding first steering vectors based on the gain of each signal receiving channel in the n signal receiving channels to obtain n second steering vectors; determine n weights in beamforming processing according to the n second steering vectors; perform beamforming processing on the n target signals based on the n weights to obtain an output signal corresponding to the target object; perform physical sign monitoring on the target object according to the output signal corresponding to the target object.

[0034] This application also provides a physical sign monitoring device, and the physical sign monitoring device includes: a memory, a processor, and a physical sign monitoring program stored on the memory and executable on the processor. When the physical sign monitoring program is executed by the processor, the steps of the physical sign monitoring method described above are implemented.

[0035] This application also proposes a storage medium, on which a physical sign monitoring program is stored. When the physical sign monitoring program is executed by a processor, the steps of the physical sign monitoring method described above are implemented.

[0036] A method, device, equipment and storage medium for physical sign monitoring provided by the present application. Compared with the related technology where the beamforming algorithm fails because the uneven gain distribution of each channel of the radar is not considered when determining the steering vector, in the present application, n target signals and azimuth angles corresponding to a target object are obtained, where the n target signals correspond one-to-one to n signal receiving channels, and n is a positive integer greater than or equal to 2; n first steering vectors corresponding to the n signal receiving channels are determined according to the azimuth angle corresponding to the target object; gain compensation is performed on each of the n first steering vectors corresponding to each signal receiving channel based on the gain of each signal receiving channel in the n signal receiving channels to obtain n second steering vectors; n weights in beamforming processing are determined according to the n second steering vectors; beamforming processing is performed on the n target signals based on the n weights to obtain an output signal corresponding to the target object; and physical sign monitoring of the target object is performed according to the output signal corresponding to the target object. That is, in the present application, when determining the weights in the beamforming algorithm, the actual gains of different signal receiving channels are considered, that is, the steering vector is compensated by the actual gains corresponding to different channels, so that the beamforming algorithm can still achieve the desired effect under the condition of uneven gain, and further ensure the accuracy of physical sign monitoring. Description of the Drawings

[0037] The drawings here are incorporated into the specification and form a part of this specification, showing embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application. To more clearly illustrate the embodiments of the present application or the technical solutions in the related art, the following will briefly introduce the drawings required for use in the description of the embodiments or the related art. Obviously, for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0038] Figure 1 It is a schematic diagram of the overall process of physical sign monitoring related to the present application;

[0039] Figure 2 It is a schematic diagram of the process of the physical sign monitoring method of the present application;

[0040] Figure 3 It is a schematic diagram of the process of generating a preset table of the present application;

[0041] Figure 4 It is a schematic diagram of the structure of the physical sign monitoring device of the present application;

[0042] Figure 5 It is a schematic diagram of the device structure of the hardware operating environment related to the solution of the embodiment of the present application.

[0043] The realization, functional features, and advantages of the present application will be further described in conjunction with embodiments and with reference to the accompanying drawings. Detailed Embodiments

[0044] It should be understood that the specific embodiments described herein are merely used to explain the present application and are not intended to limit the present application.

[0045] Before introducing the embodiments of the present application, the terms related to the present application will be introduced first:

[0046] Vital Sign Monitoring: The vital sign monitoring involved in the present application refers to the vital sign monitoring using a microwave radar (e.g., millimeter-wave radar). Due to the ultra-high precision of short waves, the microwave radar can detect movements as short as millimeters. For example, when a human body is at rest and breathing, the microwave radar can accurately identify minute movements such as the heartbeat and breathing at the chest and abdominal positions of the human body. Due to these minute movements, the reflected signal of the microwave radar is phase-modulated, where the modulation includes components of minute movements, such as movements caused by the heartbeat and breathing. Therefore, by transmitting multiple frequency-modulated signals through the microwave radar and demodulating, integrating, amplifying, filtering, etc. the echo signals reflected by the human body, the vital sign parameters of the object to be measured can be obtained, such as the heartbeat frequency or breathing frequency, etc.

[0047] It should be noted that the microwave radar involved in the present application refers to a multiple-input multiple-output (MIMO) radar. This MIMO radar uses multiple transmitting antennas and receiving antennas at the transmitting end and the receiving end respectively, where the multiple receiving antennas can be understood as multiple signal receiving channels.

[0048] Gain: It refers to the ratio of the power density of the signal generated by an actual antenna and an ideal radiation element at the same point in space under the condition of equal input power, and is used to quantitatively describe the degree to which an antenna concentrates and radiates the input power.

[0049] Corner Reflector: Also known as a radar reflector, it is made of metal plates. When the radar electromagnetic wave scans the corner reflector, the electromagnetic wave will be refracted and amplified at the metal corner, generating a very strong echo signal, and a very strong echo target will appear on the radar screen.

[0050] Beamforming: A signal processing technology. In array signal processing, often the signals collected from multiple signal receiving channels are weighted and combined to fuse the data of multiple channels into a composite signal with a specific directional response, which can achieve signal enhancement in a specific direction and suppress signal interference in other directions to improve the signal-to-noise ratio of the received signal. This weighted combination process is called beamforming.

[0051] Steering vector: A complex signal vector composed of phase differences caused by path differences on different channels, which is a vector used to guide and indicate directions. Usually, the n steering vectors corresponding to a certain object to be measured can be determined respectively according to the array information of n signal receiving channels and the azimuth angle of the object to be measured. Among them, the n signal receiving channels correspond to n receiving antennas.

[0052] Fast Fourier Transform (FFT) processing: A technique that converts a time-domain signal into a frequency-domain signal. Further, range-dimension FFT: A signal processing technique for processing radar data. By performing FFT on the received signal, the signal in the time domain can be converted into a signal in the frequency domain. In a millimeter-wave radar, range-dimension FFT can be used to convert the received echo signal into the distance information of the target object.

[0053] Windowing: Usually, the collected signal may not be an integer number of cycles. The signal with a non-integer number of cycles usually shows different characteristics from the original signal with an integer number of continuous cycles, thus affecting data analysis. Therefore, in actual signal processing, windowing can be used to present a continuous waveform as much as possible, thereby reducing the error generated when performing FFT on a non-integer number of cycles.

[0054] DC removal: A signal usually contains a DC component and an AC component. For many applications, the DC component is useless and may even interfere with signal processing. Therefore, the DC component in the signal can be removed during signal processing.

[0055] Phase extraction: Since the signal output after beamforming processing is a complex signal, and more accurate position information of the target lies in the phase of the complex signal, it is necessary to extract the phase in the complex signal to monitor the physical signs of the target object based on this phase.

[0056] Phase unwrapping: Phase unwrapping is a signal processing technique that eliminates the phase discontinuity by continuously adding or subtracting integer multiples of 2π to the phase jumps, so as to accurately analyze and process the signal. The purpose of phase unwrapping is to merge phase jumps. A phase jump refers to a discontinuous mutation in the phase of a signal, where the phase value suddenly jumps from one period to another, making the phase information unable to be directly and correctly interpreted and used.

[0057] As an example, the solution of this application can be applied to the multi-object physical sign monitoring scenario, where the physical signs can be respiration or heartbeat, etc., or other physical signs, and this application does not make any limitations in this regard.

[0058] As an example, the method for gain compensation of the steering vector involved in the solution of the present application can also be applied to other scenarios that require the use of the steering vector to solve the weights of the beamforming algorithm, and the present application does not limit this.

[0059] Taking the monitoring scenario including the object to be measured 1, the object to be measured 2, channel 1, and channel 2 as an example, the overall process of vital sign monitoring will be introduced. Refer to Figure 1 The overall process of vital sign monitoring includes:

[0060] Step S110: Obtain the echo signal and prior information of the object to be measured.

[0061] Specifically, the echo signal of the object to be measured can be obtained from the signal receiving channel of the radar.

[0062] It can be understood that in the scenario including the object to be measured 1, the object to be measured 2, channel 1, and channel 2, channel 1 can receive the echo signal 1 of the object to be measured 1 and the echo signal 1 of the object to be measured 2, and channel 2 can receive the echo signal 2 of the object to be measured 1 and the echo signal 2 of the object to be measured 2. Based on this, the echo signal 1 of the object to be measured 1 and the echo signal 1 of the object to be measured 2 can be obtained from channel 1, and the echo signal 2 of the object to be measured 1 and the echo signal 2 of the object to be measured 2 can be obtained from channel 2.

[0063] Among them, the prior information of the object to be measured includes the distance and azimuth angle. For example, the distance 1 and azimuth angle 1 of the object to be measured 1, and the distance 2 and azimuth angle 2 of the object to be detected 2.

[0064] Optionally, the prior information can be detected in advance by a sensor, or can be set in advance by a user or a staff member, and the present application does not limit this.

[0065] Step S120: Perform mixing processing on each echo signal to obtain the corresponding input signal.

[0066] Among them, the mixing processing refers to the processing of mixing the radar echo signal with the transmitted signal to obtain a beat signal.

[0067] Step S130: Window each input signal, and then perform distance-dimensional FFT processing to obtain the corresponding frequency-domain signal.

[0068] Step S140: Extract based on the distance of the object to be measured in each frequency-domain signal to obtain the corresponding target signal.

[0069] Step S150: Perform beamforming processing on the target signal corresponding to each object to be measured to obtain the output signal of each object to be measured.

[0070] That is, weighted summation processing is performed on multiple target signals corresponding to each object to be measured. For example, weighted summation processing is performed on target signal 1 and target signal 2 corresponding to object to be measured 1 to obtain the output signal of object to be measured 1; weighted summation processing is performed on target signal 1 and target signal 2 corresponding to object to be measured 2 to obtain the output signal of object to be measured 2.

[0071] Step S160: Perform DC removal, phase extraction, and phase unwrapping processing on each output signal to obtain the phase corresponding to each object to be measured.

[0072] As an example, filtering processing can also be performed on the output signal to filter other interference signals in the scene.

[0073] Step S170: Obtain the phases obtained from multiple frames, window the phases obtained from multiple frames along the slow time dimension, and perform FFT processing to obtain the physical sign change conditions of each object to be measured.

[0074] The physical sign change conditions can be, for example, respiratory rate, heart rate, etc.

[0075] Based on the above scenario, the background involved in this application is as follows:

[0076] Regarding the above step S150, in the related art, beamforming methods (such as algorithms like least squares beamforming, MVDR beamforming, etc.) are usually used to obtain signals in a specified direction and suppress signals in other interference directions. It can be understood that no matter which beamforming algorithm is adopted, it is necessary to first calculate the weights of the beamforming algorithm, and the steering vector needs to be used in the calculation process of the beamforming weights.

[0077] Taking the least squares beamforming algorithm as an example, this algorithm calculates the weights of different channels based on the principle of "minimizing the mean square error between the actual response and the desired response of the beamformer".

[0078] Specifically, the formula expression of the above principle is:

[0079]

[0080] Among them, w H is the conjugate transpose matrix of the weight vector, A = [α(θ1), α(θ2), …, α(θ j ), …, α(θ p )] is the steering vector matrix of p directions to be constrained, that is, the steering vector matrix corresponding to p objects to be measured, α(θ j ) is the steering vector corresponding to the jth object to be measured, r d is a 1×p dimensional desired response, θ jis the azimuth angle corresponding to the j-th object to be measured, where 1 ≤ j ≤ p. Each object to be measured corresponds to n steering vectors, and n is the number of signal receiving channels. For example, the steering vector α(θ j ) = [α1(θ j ), α2(θ j ), …, α n (θ j )].

[0081] Based on the above expression, by selecting an appropriate weight vector w, the actual response w H A of the beamformer can approach the desired response r d . That is to say, the above problem can be understood as solving for the weight vector in the formula.

[0082] In specific implementation, the above problem can be equivalently transformed into solving the following system of equations based on the least squares criterion:

[0083]

[0084] where w i is the weight vector corresponding to the i-th signal receiving channel, and r d (θ j ) is the desired response corresponding to the j-th object to be measured, where 1 ≤ i ≤ n.

[0085] Generally, we expect the output of the algorithm to ensure that the signal is not distorted and suppress the interference signals in other directions to the greatest extent. Based on this, the weights of beamforming can be determined in the following way:

[0086] First, let one of the p objects to be measured be the target object, and the other objects to be measured be interference objects. Let the desired response corresponding to the target object be r d1 ; the desired response corresponding to the interference objects be r d2 .

[0087] Exemplarily, r d1 = 1, r d2 = 0. Based on this, when taking the 1st object to be measured as the target object, it can be equivalently transformed into solving the following system of equations:

[0088]

[0089] Based on this, the weights for beamforming processing of the 1st object to be measured can be obtained.

[0090] Similarly, the 2nd object to be measured can be taken as the target object, and the others as interference objects, and the weights for beamforming processing of the 2nd object to be measured can be obtained according to the above method. By analogy, the weights corresponding to all objects to be measured can be obtained.

[0091] When calculating the weights in the above manner, the above-mentioned steering vector A is usually determined on the basis of assuming that the gains of all channels of the radar are the same. Based on this, assuming the actual received signal s, when the gains of the radar on different receiving channels are the same, the weights solved based on the above-mentioned steering vector can make the actual received signal w H As and the desired received signal r d The mean square error of s Obtain the minimum value.

[0092] However, in practice, there may be an uneven gain distribution among the channels of the radar. In this case, the actual received signal is w H A r s, where A r = BA, where B is the received gain on the actual different channels. Then, the weights determined in the above manner can no longer make the mean square error Obtain the minimum value. And when the deviation of the received gain on different channels is large, the least squares beamforming algorithm will fail and cannot achieve the effect of suppressing interference.

[0093] In order to make the above algorithm recover its effect, it is necessary to make the actual mean square error Minimum. Therefore, the actual constraint equation in the process of calculating the weights should become:

[0094]

[0095] Based on this, the present application proposes to perform gain compensation on the steering vector adopted in the related art, and determine the weights of the beamforming algorithm based on the compensated steering vector, so as to effectively suppress the interference signal and improve the signal-to-noise ratio of the output signal.

[0096] As an example, the physical sign monitoring method involved in the present application can be applied to a physical sign monitoring device. Exemplarily, as Figure 4 shown; it can also be applied to a physical sign monitoring device. Exemplarily, as Figure 5 shown.

[0097] The physical sign detection solution involved in the present application will be introduced below.

[0098] Referring to Figure 2 , an embodiment of the present application provides a physical sign monitoring method, and the method includes:

[0099] Step S210, obtaining n target signals and azimuth angles corresponding to the target object;

[0100] Wherein, the n target signals correspond to n signal receiving channels one by one, and n is a positive integer greater than or equal to 2.

[0101] Optionally, the azimuth angle corresponding to the target object can be detected in advance by a sensor or set in advance by a user or a staff member. This application does not make any limitations in this regard.

[0102] As an example, before the step of obtaining the n target signals corresponding to the target object, the method further includes:

[0103] Step A1, obtaining the distance of the target object;

[0104] Step A2, obtaining the n input signals corresponding to the target object, where the n input signals correspond one-to-one to the n signal receiving channels, and the input signals are signals obtained by performing mixing processing on the echo signals received by the signal receiving channels;

[0105] That is to say, first receive the n echo signals corresponding to the target object from the n signal receiving channels, and then perform mixing processing on each echo signal to obtain the n input signals corresponding to the target object.

[0106] Step A3, performing windowing and range dimension FFT on each input signal to obtain the frequency domain signal corresponding to each input signal;

[0107] Step A4, extracting the n frequency domain signals corresponding to the target object according to the distance of the target object to obtain the n target signals corresponding to the target object.

[0108] It can be understood that steps A1 to A4 correspond to steps S110 to S140 above and will not be elaborated here.

[0109] Step S220, determining the n first steering vectors corresponding to the n signal receiving channels according to the azimuth angle corresponding to the target object.

[0110] It can be understood that in this application, the n steering vectors (for example, the n first steering vectors or the n second steering vectors) form an n-dimensional steering vector, and each steering vector in the n steering vectors is a component of the n-dimensional steering vector.

[0111] For example, when the azimuth angle corresponding to the target object is θ j at this time, based on the azimuth angle θ j the n first steering vectors corresponding to the n signal receiving channels determined are α(θ j ) = [α1(θ j ), α2(θ j ), …, α n (θ j )].

[0112] Step S230: Based on the gain of each signal receiving channel among the n signal receiving channels, perform gain compensation on each corresponding first steering vector to obtain the n second steering vectors;

[0113] For example, when the azimuth angle corresponding to the target object is θ j , the gain of channel 1 can be used to compensate the first steering vector α1(θ j ) corresponding to channel 1, and the gain of channel 2 can be used to compensate the first steering vector α2(θ j ) corresponding to channel 2, and so on to achieve the compensation of the n first steering vectors.

[0114] It can be understood that to achieve the above gain compensation, in practice, the gain of each signal receiving channel at this azimuth angle can be determined first, and then each gain can be compensated into the corresponding first steering vector to obtain each second steering vector.

[0115] As an example, the steps of performing the gain compensation may include: first determining the n gains corresponding to the target object on the n signal receiving channels; then using the n gains as multiplication factors to compensate into the n first steering vectors respectively to obtain n second steering vectors.

[0116] Taking the above n first steering vectors as α(θ j ) = [α1(θ j ), α2(θ j ), …, α n (θ j )] as an example, when the determined n gains are B(θ j ) = [B1(θ j ), B2(θ j ), …, B n (θ j )], B(θ j ) = [B1(θ j ), B2(θ j ), …, B n (θ j )] can be used as a multiplication factor to compensate into the n first steering vectors α(θ j ) = [α1(θ j ), α2(θ j ), …, α n (θ j )], that is, n second steering vectors B(θ j )α(θ j ) = [B1(θ j )α1(θ j ), B2(θ j)α2(θ j ), …, B n (θ j )α n (θ j )].

[0117] As an example, a preset table including the corresponding relationships of azimuth angles, signal receiving channel numbers, and gains can be generated in advance, and then the corresponding gain can be determined by looking up the azimuth angle corresponding to the target object and the numbers of each signal receiving channel in the preset table.

[0118] As an example, a preset table including the corresponding relationships of p azimuth angles, n signal receiving channels, and p×n gains can be generated in advance.

[0119] Taking p = 2 and n = 3 as an example, the preset table may include:

[0120] The corresponding relationship of azimuth angle 1, channel 1, and gain 1;

[0121] The corresponding relationship of azimuth angle 1, channel 2, and gain 2;

[0122] The corresponding relationship of azimuth angle 1, channel 3, and gain 3;

[0123] The corresponding relationship of azimuth angle 2, channel 1, and gain 4;

[0124] The corresponding relationship of azimuth angle 2, channel 2, and gain 5;

[0125] The corresponding relationship of azimuth angle 2, channel 3, and gain 6.

[0126] As an example, the above preset table can be generated in the following manner:

[0127] Step B1, in an anechoic chamber, obtain the echo signals of n signal receiving channels of the radar when the corner reflector is at various azimuth angles;

[0128] It can be understood that other signal interferences can be prevented in the anechoic chamber.

[0129] As an example, the radar can be horizontally placed on the turntable in the anechoic chamber, and a corner reflector can be placed directly in front of the radar to achieve the rotation of the radar within the field of view angle by controlling the rotation of the turntable, thereby enabling the corner reflector to be at different azimuth angles.

[0130] As an example, the corner reflector can also be moved to different azimuth angles. Optionally, the corner reflector can move within the field of view angle of the radar with the radar as the center.

[0131] Based on this, by transmitting a radar signal, the corner reflector reflects the signal at different azimuth angles, so that each of the n signal receiving channels of the radar can receive the echo signals at each azimuth angle.

[0132] Step B2: Determine the gains of the n signal receiving channels at each azimuth angle of the corner reflector according to the echo signals of the n signal receiving channels at each azimuth angle of the corner reflector.

[0133] In specific implementation, each of the above-obtained echo signals can be first subjected to mixing processing; then each of the signals after mixing processing is windowed and subjected to range-dimensional FFT processing to obtain corresponding frequency-domain signals; then the target signals corresponding to each frequency-domain signal are extracted from each frequency-domain signal according to the distance of the corner reflector; finally, the gain corresponding to each target signal is determined according to the amplitude value of each target signal.

[0134] Among them, the distance of the corner reflector can be obtained by sensor monitoring or can be set in advance by technicians, without limitation.

[0135] In addition, as an example, for a certain azimuth angle and a certain channel, the gain corresponding to the channel at the azimuth angle can be determined according to a frame of echo signal received by the channel at the azimuth angle.

[0136] As another example, the multiple gains corresponding to the channel at the azimuth angle can also be determined respectively according to multiple frames of echo signals received by the channel at the azimuth angle, and then the gain corresponding to the channel at the azimuth angle is comprehensively determined according to the multiple gains obtained from the multiple frames. For example, the gain corresponding to the channel at the azimuth angle is determined by means of weighted summation or average gain of the multiple gains obtained from the multiple frames.

[0137] Step B3: Generate the preset table according to the gains of the n signal receiving channels at each azimuth angle of the corner reflector.

[0138] That is to say, after obtaining the gains of each signal receiving channel among the n signal receiving channels at each azimuth angle, a preset table can be generated based on the corresponding relationship among each azimuth angle, each signal receiving channel and different gains, so that when the azimuth angle of the target object is known, the gain corresponding to each signal receiving channel can be obtained by looking up the table.

[0139] Step S240: Determine n weights in beamforming processing according to the n second steering vectors.

[0140] Specifically, the n weights can be determined in combination with the solution method of the above constraint equation where A ris the steering vector after gain compensation.

[0141] Step S250, performing beamforming processing on the n target signals based on the n weights to obtain an output signal corresponding to the target object;

[0142] Step S260: monitoring the vital signs of the target object according to the output signal corresponding to the target object.

[0143] As an example, the step of performing vital sign monitoring on the target object according to the output signal corresponding to the target object includes:

[0144] Step C1, performing DC removal, phase extraction and unwrapping processing on the output signal corresponding to the target object to obtain the phase corresponding to the target object;

[0145] Step C2, performing slow time dimension windowing and FFT processing on the multi-frame phases corresponding to the target object to obtain the changes in the vital signs of the target object.

[0146] It can be understood that step C1 and step C2 correspond to the above step S160 and step S170, and will not be described in detail.

[0147] It can be understood that the above only introduces the vital sign monitoring of the target object.

[0148] Similarly, in a multi-object monitoring scenario, the vital sign monitoring of each other object to be measured can also be implemented in the above manner, which will not be repeated here.

[0149] A method, device, equipment and storage medium for physical sign monitoring provided by the present application. Compared with the related art where the beamforming algorithm fails because the uneven gain distribution of each channel of the radar is not considered when determining the steering vector, in the present application, n target signals and azimuth angles corresponding to a target object are obtained, and the n target signals correspond one-to-one to n signal receiving channels, where n is a positive integer greater than or equal to 2; n first steering vectors corresponding to the n signal receiving channels are determined according to the azimuth angle corresponding to the target object; gain compensation is performed on each of the n first steering vectors according to the gain of each signal receiving channel in the n signal receiving channels to obtain n second steering vectors; n weights in beamforming processing are determined according to the n second steering vectors; beamforming processing is performed on the n target signals based on the n weights to obtain an output signal corresponding to the target object; and physical sign monitoring of the target object is performed according to the output signal corresponding to the target object. That is, in the present application, when determining the weights in the beamforming algorithm, the actual gains of different signal receiving channels are considered, that is, the steering vector is compensated by the actual gains corresponding to different channels, so that the beamforming algorithm can still achieve the desired effect in the case of uneven gain, and further ensure the accuracy of physical sign monitoring.

[0150] The present application also provides a physical sign monitoring device. Refer to Figure 4 , and the physical sign monitoring device includes:

[0151] An acquisition module 410, configured to acquire n target signals and azimuth angles corresponding to a target object, where the n target signals correspond one-to-one to n signal receiving channels, and n is a positive integer greater than or equal to 2;

[0152] A physical sign monitoring module 420, configured to determine n first steering vectors corresponding to the n signal receiving channels according to the azimuth angle corresponding to the target object; perform gain compensation on each of the n first steering vectors according to the gain of each signal receiving channel in the n signal receiving channels to obtain n second steering vectors; determine n weights in beamforming processing according to the n second steering vectors; perform beamforming processing on the n target signals based on the n weights to obtain an output signal corresponding to the target object; and perform physical sign monitoring of the target object according to the output signal corresponding to the target object.

[0153] In a possible implementation manner of the present application, the physical sign monitoring module 420 is further configured to determine n gains corresponding to the target object on the n signal receiving channels; and compensate the n gains into the n first steering vectors respectively as multiplication factors;

[0154] And / or, the physical sign monitoring module 420 is further configured to determine the corresponding gain by looking up in a preset table according to the azimuth angle corresponding to the target object and the serial number of each signal receiving channel, where the preset table includes the corresponding relationship among the azimuth angle, the serial number of the signal receiving channel, and the gain;

[0155] And / or, the obtaining module 410 is further configured to obtain, in a microwave anechoic chamber, the echo signals of n signal receiving channels of the radar when the corner reflector is at each azimuth angle; the physical sign monitoring module 420 is further configured to determine the gains of the n signal receiving channels when the corner reflector is at each azimuth angle according to the echo signals of the n signal receiving channels when the corner reflector is at each azimuth angle; and generate the preset table according to the gains of the n signal receiving channels when the corner reflector is at each azimuth angle;

[0156] And / or, the obtaining module 410 is further configured to obtain the distance of the target object; obtain the n input signals corresponding to the target object, where the n input signals correspond to the n signal receiving channels one by one, and the input signal is a signal obtained by mixing the echo signal received by the signal receiving channel; the physical sign monitoring module 420 is further configured to perform windowing and range-dimensional FFT on each input signal to obtain the frequency-domain signal corresponding to each input signal; and extract the n target signals corresponding to the target object according to the distance of the target object;

[0157] And / or, the physical sign monitoring module 420 is further configured to perform DC removal, phase extraction, and phase unwrapping on the output signal corresponding to the target object to obtain the phase corresponding to the target object; perform windowing and FFT processing on multiple frames of phases corresponding to the target object in the slow time dimension to obtain the physical sign change situation of the target object.

[0158] The specific implementation manner of the physical sign monitoring device in this application is basically the same as that of the above embodiments of the physical sign monitoring method, and will not be elaborated here.

[0159] Refer to Figure 5 , Figure 5 which is a schematic diagram of the device structure of the hardware operating environment involved in the solution of the embodiment of this application.

[0160] As Figure 5 shown, the physical sign monitoring device may include: a processor 1001, a memory 1005, and a communication bus 1002. The communication bus 1002 is used to implement the connection and communication between the processor 1001 and the memory 1005.

[0161] Optionally, the vital sign monitoring device may further include a user interface, a network interface, a camera, an RF (Radio Frequency) circuit, sensors, a WiFi module, and so on. The user interface may include a display device and an input sub-module such as a keyboard. Optionally, the user interface may further include a standard wired interface and a wireless interface. The network interface may include a standard wired interface and a wireless interface (such as a WI-FI interface).

[0162] Those skilled in the art can understand that Figure 5 the structure of the vital sign monitoring device shown in does not constitute a limitation on the vital sign monitoring device, and it may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0163] As Figure 5 shown, in the memory 1005 as a storage medium, there may be included an operating system, a network communication module, and a vital sign monitoring program. The operating system is a program for managing and controlling the hardware and software resources of the vital sign monitoring device, and supports the operation of the vital sign monitoring program and other software and / or programs. The network communication module is used to implement the communication between the internal modules of the memory 1005, as well as the communication between the memory 1005 and other hardware and software in the vital sign monitoring device.

[0164] In Figure 5 the vital sign monitoring device shown, the processor 1001 is used to execute the vital sign monitoring program stored in the memory 1005 to implement the steps of the vital sign monitoring method described in any one of the above.

[0165] The specific implementation manner of the vital sign monitoring device of the present application is basically the same as that of each embodiment of the above vital sign monitoring method, and will not be repeated here.

[0166] The embodiments of the present application provide a storage medium, and the storage medium stores one or more programs, and the one or more programs can also be executed by one or more processors to implement the steps of the vital sign monitoring method described in any one of the above.

[0167] The specific implementation manner of the storage medium of the present application is basically the same as that of each embodiment of the above vital sign monitoring method, and will not be repeated here.

[0168] The present application also provides a computer program product, including a computer program, and when the computer program is executed by a processor, it implements the steps of the above vital sign monitoring method.

[0169] The specific implementation manner of the computer program product of the present application is basically the same as that of each embodiment of the above vital sign monitoring method, and will not be repeated here.

[0170] It should be noted that in this text, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising one..." does not exclude the presence of additional identical elements in the process, method, article or device comprising such element.

[0171] In the embodiments of the present application, prefix words such as "first" and "second" are only used to distinguish different described objects, and have no limiting effect on the position, order, priority, quantity or content of the described objects.

[0172] The serial numbers of the above embodiments of the present application are only for description and do not represent the superiority or inferiority of the embodiments.

[0173] Through the description of the above embodiments, those skilled in the art can clearly understand that the above embodiment methods can be implemented by means of software plus a hardware platform, or by hardware, but in many cases the former is a better implementation. Based on such an understanding, the technical solution of the present application, in essence or the part that contributes to the current technology, can be embodied in the form of a software product, which is stored in a storage medium (such as Read Only Memory (ROM) / Random Access Memory (RAM), magnetic disk, optical disk), and includes several instructions for causing a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of the present application.

[0174] The above are only the preferred embodiments of the present application, and do not limit the scope of the present application accordingly. Any equivalent structural or equivalent process transformation made by using the content of the specification and drawings of the present application, or directly or indirectly applied in other related technical fields, shall be included in the protection scope of the present application by the same token.

Claims

1. A physical sign monitoring method, characterized in that, The method includes: Obtaining n target signals and an azimuth angle corresponding to a target object, where the n target signals correspond one-to-one to n signal receiving channels, and n is a positive integer greater than or equal to 2; Determining n first steering vectors corresponding to the n signal receiving channels according to the azimuth angle corresponding to the target object; Performing gain compensation on each of the corresponding first steering vectors based on the gain of each signal receiving channel in the n signal receiving channels to obtain n second steering vectors; Determining n weights in beamforming processing according to the n second steering vectors; Performing beamforming processing on the n target signals based on the n weights to obtain an output signal corresponding to the target object; Performing physical sign monitoring on the target object according to the output signal corresponding to the target object.

2. The physical sign monitoring method according to claim 1, characterized in that, The step of performing gain compensation on each of the corresponding first steering vectors based on the gain of each signal receiving channel in the n signal receiving channels includes: Determining n gains corresponding to the target object on the n signal receiving channels; Compensating the n gains into the n first steering vectors respectively as multiplication factors.

3. The vital sign monitoring method according to claim 2, wherein The step of determining the n gains corresponding to the target object on the n signal receiving channels includes: Looking up and determining the corresponding gain in a preset table according to the azimuth angle corresponding to the target object and the serial number of each signal receiving channel, where the preset table includes the corresponding relationship between the azimuth angle, the serial number of the signal receiving channel, and the gain.

4. The physical sign monitoring method according to claim 3, characterized in that The preset table is generated in the following manner: In an anechoic chamber, obtaining echo signals of n signal receiving channels of a radar when a corner reflector is at various azimuth angles; Determining the gains of the n signal receiving channels when the corner reflector is at various azimuth angles according to the echo signals of the n signal receiving channels when the corner reflector is at various azimuth angles; Generating the preset table according to the gains of the n signal receiving channels when the corner reflector is at various azimuth angles.

5. The physical sign monitoring method according to any one of claims 1 to 4, characterized in that Before the step of obtaining n target signals corresponding to the target object, the method further includes: Obtaining the distance of the target object; Obtaining n input signals corresponding to the target object, where the n input signals correspond one-to-one to the n signal receiving channels, and the input signals are signals obtained by mixing the echo signals received by the signal receiving channels; Performing windowing and range dimension fast Fourier transform (FFT) on each input signal to obtain a frequency domain signal corresponding to each input signal; Extracting the n frequency domain signals corresponding to the target object according to the distance of the target object to obtain n target signals corresponding to the target object.

6. The physical sign monitoring method according to any one of claims 1 to 4, characterized in that, The step of performing physical sign monitoring on the target object according to the output signal corresponding to the target object includes: Performing DC removal, phase extraction, and phase unwrapping processing on the output signal corresponding to the target object to obtain the phase corresponding to the target object; Performing windowing in the slow time dimension and FFT processing on multiple frames of the phase corresponding to the target object to obtain the physical sign change situation of the target object.

7. A sign monitoring device, characterized in that, The device includes: An acquisition module, configured to acquire n target signals and an azimuth angle corresponding to a target object, where the n target signals correspond one-to-one to n signal receiving channels, and n is a positive integer greater than or equal to 2; A physical sign monitoring module, configured to determine n first steering vectors corresponding to the n signal receiving channels according to the azimuth angle corresponding to the target object; perform gain compensation on each of the n first steering vectors according to the gain of each signal receiving channel in the n signal receiving channels to obtain n second steering vectors; determine n weights in beamforming processing according to the n second steering vectors; perform beamforming processing on the n target signals according to the n weights to obtain an output signal corresponding to the target object; perform physical sign monitoring on the target object according to the output signal corresponding to the target object.

8. A physical sign monitoring device, characterized in that, The physical sign monitoring device includes: a memory, a processor, and a physical sign monitoring program stored on the memory and executable on the processor, and when the physical sign monitoring program is executed by the processor, the steps of the physical sign monitoring method according to any one of claims 1 to 6 are implemented.

9. A storage medium, characterized in that, A physical sign monitoring program is stored on the storage medium, and when the physical sign monitoring program is executed by a processor, the steps of the physical sign monitoring method according to any one of claims 1 to 6 are implemented.

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