A method, apparatus, device and storage medium for measuring respiration and heartbeat of multiple objects

Abstract

The application relates to the technical field of data processing, in particular to a method and device for measuring respiration and heartbeat of multiple objects, equipment and a storage medium. The method is used to solve the problem of low measurement accuracy of traditional beamforming for measuring multiple target objects. The method comprises the following steps: determining a parameter matrix and a modulus matrix corresponding to the parameter matrix based on each frame of radar intermediate frequency signals, and selecting target elements from elements contained in the modulus matrix; then, selecting components corresponding to the target elements from the parameter matrix, determining phase values of target objects to be measured based on the components, and determining corresponding respiration and heartbeat waveforms based on the phase values of the multiple frames of radar intermediate frequency signals corresponding to the target objects to be measured, wherein each frame of radar intermediate frequency signals comprises multiple intermediate frequency sub-signals, each intermediate frequency sub-signal carries respiration and heartbeat information of multiple objects to be measured, and the target object to be measured is any one of the multiple objects to be measured. Thus, the measurement accuracy of measuring respiration and heartbeat of multiple objects can be improved.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to a method, apparatus, device, and storage medium for measuring the respiratory and heartbeats of multiple subjects. Background Technology

[0002] Respiratory and cardiac parameters are important indicators of whether cardiopulmonary activity is normal. For example, many sudden illnesses can cause abnormalities in cardiopulmonary activity. Therefore, real-time monitoring of respiratory and cardiac parameters is of great significance.

[0003] Currently, millimeter-wave radar is a relatively mature technology for measuring the respiratory and heart rate parameters of target objects. In practical applications, if there are multiple target objects, their intermediate frequency (IF) signals will be superimposed. To measure the respiratory and heart rate of each target object, it is necessary to separate the phases of their respective IF sub-signals.

[0004] Traditional methods use beamforming to directly separate the intermediate frequency (IF) sub-signals of each target object, thereby directly obtaining the phase of each IF signal. Beamforming is usually implemented using array antennas, which requires first initially locating the orientation of each target object, and then adjusting the phase of the frequency-modulated (FM) signals transmitted by each array antenna to concentrate the FM signals toward the target object.

[0005] However, there are unavoidable errors in locating the target object and adjusting the beamforming direction of the array antenna. The accumulation of these errors reduces the measurement accuracy. Furthermore, beamforming introduces clutter at the grating lobe position, which also exacerbates the measurement error. Therefore, traditional beamforming suffers from low measurement accuracy when measuring multiple targets. Summary of the Invention

[0006] This application provides a method, apparatus, device, and storage medium for measuring the respiratory and heartbeats of multiple subjects, thereby improving the measurement accuracy of the respiratory and heartbeats of multiple subjects.

[0007] The specific technical solutions provided in this application are as follows:

[0008] In a first aspect, embodiments of this application provide a method for measuring the respiratory and heart rate of multiple subjects, including:

[0009] Based on each frame of radar intermediate frequency signal, a parameter matrix is ​​determined, wherein each frame of radar intermediate frequency signal includes multiple intermediate frequency sub-signals, each intermediate frequency sub-signal carries multiple respiratory and heartbeat information of the target object, and the parameter matrix is ​​obtained by concatenating the target complex vectors of each intermediate frequency sub-signal, and the index value of each component of the target complex vector in the parameter matrix represents the distance and azimuth information with the radar;

[0010] Based on the parameter matrix, the corresponding modulus matrix is ​​determined, and target elements are selected from the elements contained in the modulus matrix, wherein the target elements represent the respiratory and heartbeat information of the subject to be tested, and the modulus value of the target elements is greater than a threshold.

[0011] The component corresponding to the target element is selected from the parameter matrix, and the phase value of the target object to be tested is determined based on the component, wherein the target object to be tested is any one of the plurality of objects to be tested;

[0012] Based on the phase values ​​of the multi-frame radar intermediate frequency signals corresponding to the target object, the corresponding respiratory and heartbeat waveforms are determined.

[0013] The above method directly analyzes the radar intermediate frequency signal and uses range Fourier transform and angle Fourier transform to directly separate the phase changes of each of the multiple objects under test. Since, according to prior knowledge, each phase change is equivalent to its own respiratory and heartbeat curve, the respiratory and heartbeat waveforms of each object under test can be obtained, which improves the measurement accuracy. More importantly, the objects under test only need to remain stationary during the measurement process, which improves the convenience and wide applicability of the solution.

[0014] In one possible implementation, determining the parameter matrix based on each frame of radar intermediate frequency signal includes:

[0015] For each intermediate frequency sub-signal included in each frame of radar intermediate frequency signal, sampling is performed according to a preset sampling period to obtain the corresponding sampling point sequence;

[0016] Perform a Fourier transform on each sampling point sequence to obtain the corresponding first complex vector, and then perform a transpose operation on each first complex vector to obtain the corresponding second complex vector;

[0017] Based on the receiving antenna array of the radar, the various second complex vectors are spliced ​​together to obtain a complex matrix;

[0018] Perform a Fourier transform on each row of the complex vectors in the complex matrix to obtain the target complex vector corresponding to each row, and then concatenate the target complex vectors to obtain the parameter matrix.

[0019] The above method obtains a parameter matrix carrying the range and azimuth information of multiple objects under test by performing range Fourier transform and angle Fourier transform on each frame of radar intermediate frequency signal. This allows the phase value of each object under test to be obtained based on the modulus matrix corresponding to the parameter matrix.

[0020] In one possible implementation, determining the corresponding modulus matrix based on the parameter matrix includes:

[0021] Based on the real and imaginary parts of each component in the parameter matrix, determine the corresponding modulus value;

[0022] The modulus matrix is ​​generated based on each modulus value, wherein the modulus matrix and the parameter matrix have the same number of rows and columns, and any component has the same index value as the modulus value corresponding to that component.

[0023] The above method can distinguish multiple test objects by analyzing the modulus matrix corresponding to the parameter matrix, so as to determine the target element based on the modulus matrix in the future.

[0024] In one possible implementation, selecting the component corresponding to the target element from the parameter matrix includes:

[0025] Obtain the index value of the target element in the modulus matrix;

[0026] Select the component corresponding to the index value from the parameter matrix.

[0027] In the above method, the modulus matrix and the parameter matrix have the same dimension. After determining the corresponding target element through the modulus matrix, the corresponding component can be selected from the parameter matrix based on the index value of the target element. The component carries the distance and azimuth information between the target object and the radar. In this way, it is possible to accurately determine which component in the parameter matrix corresponds to the target object, thereby accurately distinguishing the phase values ​​of multiple targets in each frame of radar intermediate frequency signal.

[0028] In one possible implementation, determining the phase value of the target object based on the component includes:

[0029] If the imaginary part of the component is not less than a preset value, then the phase value of the target object to be measured is obtained based on the imaginary part and the real part of the component.

[0030] If the imaginary part of the component is less than a preset value, a phase reference value is determined based on the imaginary part and the real part of the component, and the phase reference value is adjusted based on the phase adjustment value to obtain the phase value of the target object to be measured.

[0031] The above method can accurately determine the phase value of each subject after determining the components. According to prior knowledge, the phase change of each subject is equivalent to its own respiratory and heartbeat curve. Therefore, the respiratory and heartbeat waveforms of each subject can be obtained.

[0032] In one possible implementation, determining the corresponding respiratory and heartbeat waveform based on the phase values ​​of the multi-frame radar intermediate frequency signals corresponding to the target object includes:

[0033] The phase value of each frame of radar intermediate frequency signal corresponding to the target object is unwrapped to determine the respiratory, heartbeat, and chest cavity displacement of the target object.

[0034] Based on the respiratory, heartbeat, and chest cavity displacement of the multi-frame radar intermediate frequency signal corresponding to the target object, the respiratory and heartbeat waveform of the target object is generated.

[0035] The above method restores the true phase value of each frame of radar intermediate frequency signal of the target object, thereby accurately obtaining the respiratory, heartbeat, and chest displacement of the target object, and thus obtaining the accurate respiratory and heartbeat waveform of the target object.

[0036] In one possible implementation, if the radar is a millimeter-wave radar and the millimeter-wave radar is equipped with multiple transmitting antennas and multiple receiving antennas, then each intermediate frequency sub-signal is obtained by mixing the frequency-modulated signal transmitted by any of the multiple transmitting antennas and the echo signal received by any of the multiple receiving antennas using a mixer.

[0037] The above method, by equipping the radar with multiple receiving antennas, can accurately obtain the azimuth information of multiple objects under test. Based on this scheme, the phase value of each object under test can be separated to obtain the respiratory and heartbeat waveform of each object under test, thereby improving the measurement accuracy of respiratory and heartbeat measurements of multiple objects.

[0038] Secondly, embodiments of this application provide an apparatus for measuring the respiratory and heart rate of multiple subjects, comprising:

[0039] The first determining module is used to determine a parameter matrix based on each frame of radar intermediate frequency signal, wherein each frame of radar intermediate frequency signal includes multiple intermediate frequency sub-signals, each intermediate frequency sub-signal carries multiple respiratory and heartbeat information of the target object, and the parameter matrix is ​​obtained by concatenating the target complex vectors of each intermediate frequency sub-signal, and the index value of each component of the target complex vector in the parameter matrix represents the distance and azimuth information with the radar;

[0040] The filtering module is used to determine the corresponding modulus matrix based on the parameter matrix, and to filter out target elements from the elements contained in the modulus matrix, wherein the target elements represent the respiratory and heartbeat information of the test object, and the modulus value of the target elements is greater than a threshold.

[0041] The second determining module is used to select the component corresponding to the target element from the parameter matrix, and determine the phase value of the target object to be tested based on the component, wherein the target object to be tested is any one of the plurality of objects to be tested;

[0042] The third determining module is used to determine the corresponding respiratory and heartbeat waveform based on the phase value of the multi-frame radar intermediate frequency signal corresponding to the target object under test.

[0043] In one possible implementation, the parameter matrix is ​​determined based on each frame of radar intermediate frequency signal, wherein the first determining module is used to:

[0044] For each intermediate frequency sub-signal included in each frame of radar intermediate frequency signal, sampling is performed according to a preset sampling period to obtain the corresponding sampling point sequence;

[0045] Perform a Fourier transform on each sampling point sequence to obtain the corresponding first complex vector, and then perform a transpose operation on each first complex vector to obtain the corresponding second complex vector;

[0046] Based on the receiving antenna array of the radar, the various second complex vectors are spliced ​​together to obtain a complex matrix;

[0047] Perform a Fourier transform on each row of the complex vectors in the complex matrix to obtain the target complex vector corresponding to each row, and then concatenate the target complex vectors to obtain the parameter matrix.

[0048] In one possible implementation, the step of determining the corresponding modulus matrix based on the parameter matrix, wherein the filtering module is used for:

[0049] Based on the real and imaginary parts of each component in the parameter matrix, determine the corresponding modulus value;

[0050] The modulus matrix is ​​generated based on each modulus value, wherein the modulus matrix and the parameter matrix have the same number of rows and columns, and any component has the same index value as the modulus value corresponding to that component.

[0051] In one possible implementation, the second determining module is used to select the component corresponding to the target element from the parameter matrix.

[0052] Obtain the index value of the target element in the modulus matrix;

[0053] Select the component corresponding to the index value from the parameter matrix.

[0054] In one possible implementation, the second determining module is used to determine the phase value of the target object based on the component, wherein the phase value of the target object is determined by:

[0055] If the imaginary part of the component is not less than a preset value, then the phase value of the target object to be measured is obtained based on the imaginary part and the real part of the component.

[0056] If the imaginary part of the component is less than a preset value, a phase reference value is determined based on the imaginary part and the real part of the component, and the phase reference value is adjusted based on the phase adjustment value to obtain the phase value of the target object to be measured.

[0057] In one possible implementation, the third determining module is used to determine the corresponding respiratory and heartbeat waveform based on the phase values ​​of the multi-frame radar intermediate frequency signals corresponding to the target object being tested.

[0058] The phase value of each frame of radar intermediate frequency signal corresponding to the target object is unwrapped to determine the respiratory, heartbeat, and chest cavity displacement of the target object.

[0059] Based on the respiratory, heartbeat, and chest cavity displacement of the multi-frame radar intermediate frequency signal corresponding to the target object, the respiratory and heartbeat waveform of the target object is generated.

[0060] In one possible implementation, if the radar is a millimeter-wave radar and the millimeter-wave radar is equipped with multiple transmitting antennas and multiple receiving antennas, then each intermediate frequency sub-signal is obtained by mixing the frequency-modulated signal transmitted by any of the multiple transmitting antennas and the echo signal received by any of the multiple receiving antennas using a mixer.

[0061] Thirdly, embodiments of this application provide an electronic device, including:

[0062] Memory is used to store computer programs that can be executed by the controller;

[0063] The controller is connected to the memory and configured to perform the method as described in any of the first aspects above.

[0064] Fourthly, embodiments of this application provide a computer-readable storage medium that, when instructions in the storage medium are executed by a processor, enables the processor to perform the method described in any one of the first aspects above.

[0065] Furthermore, the technical effects of any of the implementation methods in the second to fourth aspects can be found in the technical effects of different implementation methods in the first aspect, and will not be repeated here. Attached Figure Description

[0066] Figure 1 A schematic diagram of a beamforming principle in existing technology;

[0067] Figure 2 This is a schematic diagram illustrating an application scenario in an embodiment of this application;

[0068] Figure 3 This is a schematic diagram illustrating another application scenario in the embodiments of this application;

[0069] Figure 4 This is a flowchart illustrating a method for measuring the respiratory and heart rate of multiple subjects according to an embodiment of this application.

[0070] Figure 5 This is a schematic diagram illustrating the definition of a radar intermediate frequency signal in an embodiment of this application;

[0071] Figure 6 This is a schematic diagram of a process for obtaining a parameter matrix in an embodiment of this application;

[0072] Figure 7 This is a schematic diagram of a simulation scenario for measuring the breathing and heart rate of multiple objects in an embodiment of this application;

[0073] Figure 8 This is a flowchart illustrating a process for determining the modulus matrix corresponding to a parameter matrix in an embodiment of this application.

[0074] Figure 9 This is a three-dimensional surface schematic diagram of a modulus matrix in an embodiment of this application;

[0075] Figure 10 This is a schematic diagram of a modulus matrix after zeroing processing in an embodiment of this application;

[0076] Figure 11 This is a schematic diagram of a process for selecting the component corresponding to the target element from the parameter matrix in an embodiment of this application;

[0077] Figure 12 This is a schematic diagram of a process for determining the phase value of a component in an embodiment of this application;

[0078] Figure 13 This is a schematic diagram of a process for determining the respiratory and heart rate waveform of a target test subject in an embodiment of this application;

[0079] Figure 14 This is a schematic diagram of the cosine curve in the embodiments of this application;

[0080] Figure 15 This is a schematic diagram of the original respiratory and heart rate waveforms of three subjects in this embodiment of the application;

[0081] Figure 16 This is a normalized comparison diagram of the original waveform and the analyzed waveform of the test object 1 in this embodiment of the application;

[0082] Figure 17 This is a normalized comparison diagram of the original waveform and the analyzed waveform of the test object 2 in this embodiment of the application;

[0083] Figure 18 This is a normalized comparison diagram of the original waveform and the analyzed waveform of the test object 3 in this embodiment of the application;

[0084] Figure 19 This is a schematic diagram of the logical architecture of a device for measuring the respiratory and heart rate of multiple objects according to an embodiment of this application;

[0085] Figure 20 This is a schematic diagram of the physical architecture of the electronic device in the embodiments of this application. Detailed Implementation

[0086] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0087] It should be noted that the terms "first," "second," "third," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in sequences other than those illustrated or described herein.

[0088] The design concept of the embodiments of this application will be briefly introduced below.

[0089] This application relates to the field of data processing technology, and mainly to a method, apparatus, device and storage medium for measuring the respiratory and heartbeats of multiple subjects.

[0090] The principle of millimeter-wave radar for measuring the breathing and heartbeat of a target object is as follows: The radar transmits a frequency-modulated (FM) signal, which is reflected after reaching the target object. The radar mixer mixes the FM signal with the received reflected signal to obtain an intermediate frequency (IF) signal. The minute displacement caused by the breathing and heartbeat of the target object is proportional to the phase transformation of the IF signal. Therefore, extracting the phase of the IF signal is equivalent to extracting the minute displacement of the breathing and heartbeat of the target object. Thus, based on the minute displacement of the breathing and heartbeat, the breathing and heartbeat waveform of the target object is generated, and the frequencies of the breathing and heartbeat of the target object are analyzed based on the breathing and heartbeat waveform.

[0091] In practical applications, beamforming is commonly used in multi-target respiratory and heart rate measurement schemes. This involves directing the transmitted frequency-modulated signal towards each target to minimize phase interference between the resulting intermediate frequency sub-signals. Beamforming is typically implemented using array antennas: first, the target's location is initially determined; then, the phase of the transmitted signals from each antenna in the array is adjusted to concentrate the transmitted signal towards the target.

[0092] Figure 1 A schematic diagram illustrating the beamforming principle is shown. (See attached image.) Figure 1As shown in the diagram, the schematic includes feed A and feed B. On the parabolic surface emitted by feed A and feed B, there are two positions where the peaks meet, one being the beam direction and the other being the grating lobe position; there is also a position where the peak and trough meet, which is the zero-depth position.

[0093] Based on wave interference, when wave crests meet wave crests, or wave troughs meet wave troughs, their energy is added, resulting in higher crests and deeper troughs; when wave crests meet wave troughs, their energy cancels out. (See also...) Figure 1 As shown, since the grating lobe position is where wave crests meet, the energy is added together. The energy at the grating lobe position is equivalent to the energy of the beam direction. Therefore, clutter interference formed here is unavoidable. When superimposed on the echo signal, it will also cause significant interference, thus exacerbating the measurement error.

[0094] Furthermore, in traditional beamforming schemes, the target object's orientation needs to be initially located. Therefore, the target object cannot be moved during the beamforming process. If the target object moves during the beamforming process, the initially located orientation will become invalid, and the adjusted array antenna based on the initial orientation will also become invalid, meaning the beamforming scheme fails. This reduces the convenience and universal applicability of traditional beamforming for measuring multiple targets.

[0095] In view of this, in order to solve the problem of low measurement accuracy in the measurement of multiple targets by traditional beamforming, in this embodiment, a parameter matrix and a corresponding modulus matrix are determined based on each frame of radar intermediate frequency signal, and target elements are selected from the elements contained in the modulus matrix; then, the components corresponding to the target elements are selected from the parameter matrix, and the phase value of the target object is determined based on the components. Each frame of radar intermediate frequency signal includes multiple intermediate frequency sub-signals, each of which carries respiratory and heartbeat information of multiple targets. The parameter matrix is ​​obtained by concatenating the target complex vectors of each intermediate frequency sub-signal. The index value of each component of the target complex vector in the parameter matrix represents the distance and azimuth information with the radar; the target object is any one of multiple targets; finally, the corresponding respiratory and heartbeat waveform is determined based on the phase value of the multiple frames of radar intermediate frequency signals corresponding to the target object.

[0096] Thus, by using the method for measuring the breathing and heartbeat of multiple objects provided in this application, the phase of the intermediate frequency sub-signal of each object under test can be directly separated from the radar intermediate frequency signal, directly filtering out the mutual interference between multiple signals. There is no need to locate the position of the object under test in advance, thereby eliminating the positioning error caused by the preliminary location of the object under test; there is also no need to adjust the signal phase of each array antenna, eliminating the phase error caused by adjusting the signal phase of the array antenna, thereby improving the measurement accuracy of the measurement results.

[0097] Furthermore, since no additional preparations are required before implementation, the ease of implementation is improved. More importantly, during implementation, it is only necessary to ensure that the target being measured is stationary, without having to keep the position of the target object fixed. This also enhances the wide applicability of the implementation of this scheme.

[0098] After introducing the design concept of the embodiments of this application, the preferred embodiments of this application will be further described in detail below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only for illustration and explanation of this application and are not intended to limit this application. Furthermore, the embodiments of this application and the features in the embodiments can be combined with each other without conflict.

[0099] See Figure 2 The diagram shown illustrates an application scenario according to an embodiment of this application. This application scenario includes a millimeter-wave radar 110 and a terminal device 120, wherein...

[0100] The millimeter-wave radar 110 is equipped with multiple transmitting antennas and multiple receiving antennas. It is used to transmit frequency-modulated signals through any one of the transmitting antennas and to receive echo signals through any one of the receiving antennas. The echo signal is the signal reflected after the frequency-modulated signal reaches the object under test.

[0101] It is also used to send each frame of radar intermediate frequency signal to terminal device 120. Each frame of radar intermediate frequency signal includes multiple intermediate frequency sub-signals. Each intermediate frequency sub-signal carries multiple respiratory and heartbeat information of the subject under test. Each intermediate frequency sub-signal is obtained by mixing the frequency modulation signal sent by any one of the multiple transmitting antennas and the echo signal received by any one of the multiple receiving antennas by a mixer.

[0102] Terminal device 120 is used to determine a parameter matrix based on each frame of radar intermediate frequency signal received from millimeter-wave radar 110, and to determine the corresponding modulus matrix based on the parameter matrix. It then filters out target elements from the elements contained in the modulus matrix, selects the components corresponding to the target elements from the parameter matrix, and determines the phase value of the target object based on the components. The parameter matrix is ​​obtained by concatenating the target complex vectors of each intermediate frequency sub-signal. The index value of each component of the target complex vector in the parameter matrix represents the distance and azimuth information with the radar. The target elements represent the respiratory and heartbeat information of the target object, and the modulus value of the target element is greater than a threshold. The target object is any one of multiple target objects.

[0103] It is also used to determine the corresponding respiratory and heartbeat waveforms based on the phase values ​​of the multi-frame radar intermediate frequency signals corresponding to the target object.

[0104] In this application embodiment, the aforementioned terminal device can be a smart mobile terminal, tablet computer, laptop computer, smart handheld device, personal computer (PC), computer, smart screen, various wearable devices, personal digital assistant (PDA), etc.; the aforementioned terminal device can also be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms. This application does not limit the specific form of the aforementioned terminal device.

[0105] See Figure 3 The diagram shown illustrates another application scenario of this application. This application scenario includes a smart terminal 210 integrating a millimeter-wave radar module, wherein...

[0106] The intelligent terminal 210 is used to obtain the radar intermediate frequency signal of each frame through the millimeter-wave radar module, and is also used to determine the parameter matrix and the mode matrix corresponding to the parameter matrix based on each frame of radar intermediate frequency signal, and to filter out the target element from the elements contained in the mode matrix, and to select the component corresponding to the target element from the parameter matrix, and to determine the phase value of the target object to be measured based on the component.

[0107] It is also used to determine the corresponding respiratory and heartbeat waveforms based on the phase values ​​of the multi-frame radar intermediate frequency signals corresponding to the target object.

[0108] In this embodiment of the application, the millimeter-wave radar is equipped with multiple transmitting antennas and multiple receiving antennas. Each frame of radar intermediate frequency signal contains multiple intermediate frequency sub-signals. Each intermediate frequency sub-signal is obtained by mixing the frequency modulation signal sent by any transmitting antenna among the multiple transmitting antennas and the echo signal received by any receiving antenna among the multiple receiving antennas by a mixer.

[0109] After introducing the application scenarios of the embodiments of this application, please refer to... Figure 4 As shown in the embodiments of this application, a method for measuring the respiratory and heart rate of multiple subjects has the following specific process:

[0110] Step 400: Based on each frame of radar intermediate frequency signal, determine the parameter matrix. Each frame of radar intermediate frequency signal includes multiple intermediate frequency sub-signals. Each intermediate frequency sub-signal carries respiratory and heartbeat information of multiple objects under test. The parameter matrix is ​​obtained by concatenating the target complex vectors of each intermediate frequency sub-signal. The index value of each component of the target complex vector in the parameter matrix represents the distance and azimuth information of the radar.

[0111] In this embodiment, the object under test is directly facing the radar at a distance R and remains stationary during the measurement process. Only vital functions such as breathing and heartbeat cause the chest cavity to rise and fall, resulting in a slight displacement change in the distance between the object under test and the radar.

[0112] Based on the working principle of radar: the radar transmits a series of continuous frequency-modulated signals and receives the echo signals reflected after the frequency-modulated signals reach the object under test. The mixer mixes the transmitted frequency-modulated signals and the received echo signals to form an intermediate frequency sub-signal.

[0113] In this embodiment of the application, the above-mentioned frequency modulation signal can be represented by the following formula:

[0114]

[0115] Where s(t) represents the frequency modulation signal, f is the rate of change of the frequency of the frequency-modulated signal, i.e., the slope, where c is the speed of light; c This is the starting frequency for frequency modulation of the frequency modulation signal.

[0116] Typically, the received echo signal lags behind the transmitted FM signal by a certain time interval. In this embodiment, this lag time is denoted as t. d Therefore, the received echo signal can be represented by the following formula:

[0117]

[0118] Where r(t) represents the echo signal.

[0119] Then, according to Formula 1 and Formula 2, the intermediate frequency (IF) sub-signals obtained by the mixer in mixing the above-mentioned frequency modulation signal and echo signal can be obtained. In this embodiment, each IF sub-signal can be represented by the following formula:

[0120]

[0121] Where b(t) represents the intermediate frequency sub-signal, λ is the wavelength of the intermediate frequency sub-signal, and R represents the distance between the object under test and the radar.

[0122] It should be noted that in this embodiment, the millimeter-wave radar is equipped with multiple transmitting antennas and multiple receiving antennas. Assuming that a continuous series of frequency-modulated signals transmitted by the transmitting antenna is called a chirp, and the multiple transmitting antennas transmit in turn for one round, the multiple receiving antennas can generate a total of (total number of transmitting antennas * total number of receiving antennas) intermediate frequency sub-signals of chirps. Then, these (total number of transmitting antennas * total number of receiving antennas) intermediate frequency sub-signals of chirps are combined into a group, which is called a frame of radar intermediate frequency signal.

[0123] For example, see Figure 5 As shown, a millimeter-wave radar equipped with 3 transmitting antennas and 4 receiving antennas is used as an example.

[0124] Since each transmitting antenna transmits a continuous series of frequency-modulated signals, which is one chrip, a millimeter-wave radar equipped with 3 transmitting antennas and 4 receiving antennas can output 12 (i.e., 3*4) chrip intermediate frequency sub-signals by the mixer after transmitting one round of the above frequency-modulated signals. These 12 (i.e., 3*4) chrip intermediate frequency sub-signals are combined into a group, which is called a frame of radar intermediate frequency signal.

[0125] See Figure 6 As shown in this embodiment, when performing step 400, the relevant functions can be achieved by performing the following steps:

[0126] Step 4001: Sample each intermediate frequency sub-signal included in each frame of radar intermediate frequency signal according to a preset sampling period to obtain the corresponding sampling point sequence.

[0127] In this embodiment of the application, when performing step 4001, a method commonly used for analyzing continuous signals is employed, namely, using a pulse sequence to obtain a series of discrete samples, i.e., a series of sampling points, from each intermediate frequency sub-signal. To characterize the order of each obtained sampling point, the aforementioned series of sampling points is recorded as a sampling point sequence.

[0128] Step 4002: Perform a Fourier transform on each sampling point sequence to obtain the corresponding first complex vector.

[0129] In this embodiment, since the intermediate frequency sub-signal is the superposition of the intermediate frequency sub-signals generated by multiple objects under test, the spectrum obtained by sampling the intermediate frequency sub-signal and performing a Fourier transform usually contains multiple peaks. The frequency corresponding to each peak is the frequency of each intermediate frequency sub-signal, and also corresponds to the distance from each object under test to the radar. Therefore, the above Fourier transform can be called the range Fourier transform. In this way, by executing step 4002, the distance information between the object under test and the radar corresponding to each intermediate frequency sub-signal can be obtained.

[0130] Step 4003: Perform a transpose operation on each first complex vector to obtain its corresponding second complex vector.

[0131] Step 4004: Based on the radar receiving antenna array, the various second complex vectors are spliced ​​together to obtain a complex matrix.

[0132] In this embodiment of the application, after executing step 4003, the transpose of each first complex vector, i.e., the second complex vector, is obtained. Then, when executing step 4004, based on the radar receiving antenna array, the second complex vectors are sequentially spliced ​​together in a top-to-bottom order to obtain a complex matrix, wherein each column in the complex matrix corresponds to the Fourier transform result of an intermediate frequency sub-signal.

[0133] Step 4005: Perform a Fourier transform on each row of complex vectors in the complex matrix to obtain the target complex vector corresponding to each row of complex vectors.

[0134] In this embodiment of the application, when performing step 4005, a Fourier transform is performed on each row of complex vectors in the complex matrix to obtain the azimuth information of each target object and radar contained in each intermediate frequency sub-signal.

[0135] If two or more of the above-mentioned objects to be measured are at the same distance from the radar, then step 4005 is executed. The two or more objects to be measured that are at the same distance from the radar can be distinguished by the difference in azimuth information. Therefore, the above-mentioned Fourier transform can also be called angle Fourier transform.

[0136] Step 4006: Concatenate the various target complex vectors to obtain the parameter matrix.

[0137] In this embodiment of the application, when executing arrangement 4006, the parameter matrix corresponding to each frame of radar intermediate frequency signal is obtained. The parameter matrix is ​​obtained by splicing multiple target complex vectors. The index information of each component contained in the target complex vector represents the distance and azimuth information with the radar. In this way, by further processing the parameter matrix, the phase value of each object to be measured can be obtained, thereby obtaining the respiratory, heartbeat and chest displacement of each object to be measured.

[0138] For example, see Figure 7 As shown, the example is measuring the breathing and heart rate of three subjects.

[0139] Assuming the radar is a millimeter-wave radar, and the millimeter-wave radar is equipped with 3 transmitting antennas and 4 receiving antennas, and the transmitting antennas transmit a series of continuous frequency-modulated signals as a chirp, the 3 transmitting antennas transmit in turn for one round, and the 4 receiving antennas can generate a total of 12 intermediate frequency sub-signals of chirps, that is, one frame of radar intermediate frequency signal.

[0140] Then, according to the preset sampling period, the intermediate frequency sub-signals of the 12 chirps are sampled respectively to obtain their respective sampling point sequences.

[0141] Assuming that the number of samples of the intermediate frequency sub-signal of each chirp is 256, that is, 256 sampling points of data are obtained.

[0142] Therefore, the above 256 sampling points constitute a sampling point sequence. Then, the following operations are performed:

[0143] Operation 1: Perform Fourier transform on the 12 sample point sequences to obtain their respective first complex vectors.

[0144] Operation 2: Perform a transpose operation on the first complex vector corresponding to each of the 12 chirp intermediate frequency sub-signals (i.e., transpose the horizontal quantity into a column vector) to obtain the corresponding second complex vector.

[0145] Operation 3: Based on the radar receiving antenna array, the 12 second complex vectors are spliced ​​together in order from left to right to obtain a complex matrix.

[0146] Operation four: Perform a Fourier transform on each row of complex vectors in the complex matrix to obtain the target complex vector corresponding to each row.

[0147] Operation 5: Concatenate the 256 target complex vectors in top-to-bottom order to obtain the parameter matrix, denoted as the R_A matrix (i.e., the distance-orientation matrix).

[0148] Step 410: Determine the corresponding modulus matrix based on the parameter matrix.

[0149] See Figure 8 As shown in this embodiment, when performing step 410, the following steps are specifically executed:

[0150] Step 4101: Determine the corresponding modulus value based on the real and imaginary parts of each component in the parameter matrix.

[0151] In this embodiment of the application, when performing step 4101, the modulus of each component in the parameter matrix can be calculated using the following formula:

[0152] M=(a 2 +b 2 ) 1 / 2 Formula 4

[0153] Where a and b represent the real and imaginary parts of each component (complex number) in the parameter matrix, respectively.

[0154] Step 4102: Generate a modulus matrix based on each modulus value, wherein the modulus matrix and the parameter matrix have the same number of rows and columns, and the index value of any component and the modulus value corresponding to any component are the same.

[0155] For example, see Figure 9 As shown, the example still uses the measurement of the breathing and heart rate of three subjects.

[0156] Assuming the radar is a millimeter-wave radar, and that it is equipped with 3 transmitting antennas and 4 receiving antennas, and that a chirp is a series of continuous frequency-modulated signals transmitted by the transmitting antennas, with the 3 transmitting antennas transmitting in turn for one round, the 4 receiving antennas can generate a total of 12 chirps of intermediate frequency sub-signals, that is, one frame of radar intermediate frequency signal.

[0157] In this embodiment of the application, after obtaining the parameter matrix, the modulus of each component in the parameter matrix is ​​calculated using the above formula 4.

[0158] Since the parameter matrix is ​​a 256*256 matrix, the above formula 4 is used to calculate 256*256 moduli, and the moduli matrix is ​​also a 256*256 matrix.

[0159] Figure 9 A schematic diagram of the three-dimensional surface of the modulus matrix is ​​shown. (See reference...) Figure 9 As shown, the index value of each element in the above-mentioned modular matrix includes a first index value and a second index value, wherein the first index value represents distance information and the second index value represents orientation information.

[0160] Step 420: Select target elements from the elements contained in the modulus matrix, where the target elements represent the respiratory and heartbeat information of the subject to be tested, and the modulus value of the target elements is greater than the threshold.

[0161] In this embodiment of the application, when performing step 4102, the modulus value of the elements contained in the modulus matrix is ​​compared with a threshold. If the modulus value is greater than the threshold, the element corresponding to the modulus value is determined as the target element.

[0162] In some preferred embodiments, the element in the modulus matrix with the peak modulus value is determined as the target element.

[0163] For example, see Figure 10 As shown, the example still uses the measurement of the breathing and heart rate of three subjects.

[0164] Assuming the radar is a millimeter-wave radar, and that it is equipped with 3 transmitting antennas and 4 receiving antennas, and that a chirp is a series of continuous frequency-modulated signals transmitted by the transmitting antennas, with the 3 transmitting antennas transmitting in turn for one round, the 4 receiving antennas can generate a total of 12 chirps of intermediate frequency sub-signals, that is, one frame of radar intermediate frequency signal.

[0165] In this embodiment of the application, after obtaining the modulus matrix corresponding to the parameter matrix, the modulus value of each element contained in the modulus matrix is ​​compared with the threshold.

[0166] In some possible embodiments, elements with modulo values ​​greater than a threshold are retained, while elements with modulo values ​​less than or equal to the threshold are set to zero. A schematic diagram of the modulo matrix after the zeroing process is shown below. Figure 10 As shown.

[0167] Assume that among the three objects to be tested, object 1 and object 3 are at the same distance from the radar, and the positions of object 1 and object 2 are at the same azimuth angle as the radar.

[0168] See Figure 10 As shown in the embodiment of this application, the modulus matrix after zeroing contains three elements, corresponding to three objects to be measured. Among them, the distances from two objects to be measured to the radar are equal, and the azimuth angles of the two objects to be measured are equal.

[0169] In this way, by using the above method and calculating the modulus of the parameter matrix, the distance and orientation information of the object to be measured can be accurately found, thereby distinguishing the three objects to be measured.

[0170] Step 430: Select the component corresponding to the target element from the parameter matrix.

[0171] In this embodiment, after filtering out the target element from the modulus matrix, the distance and azimuth information of multiple objects to be measured are determined. In this way, combined with the actual scenario and the distance and azimuth angle between multiple objects to be measured and the radar, the relationship between the target element and the objects to be measured can be accurately distinguished. Then, step 430 is executed to select the component corresponding to the target element from the parameter evidence. Based on this component, the phase value of each object to be measured can be obtained.

[0172] For specific implementation details, please refer to... Figure 11 As shown, when executing step 430, the following steps are specifically performed:

[0173] Step 4301: Obtain the index value of the target element in the modulus matrix.

[0174] Step 4302: Select the component corresponding to the index value from the parameter matrix.

[0175] Step 440: Determine the phase value of the target object under test based on the components, wherein the target object under test is any one of the plurality of objects under test.

[0176] In the embodiments of this application, see the following: Figure 12 As shown, when executing step 440, the relevant function is achieved by performing the following steps:

[0177] Step 4401: Determine whether the imaginary part of the component is less than the preset value. If yes, proceed to steps 4402 to 4403; otherwise, proceed to step 4404.

[0178] In this embodiment of the application, when performing step 4401, if the imaginary part of the component is less than a preset value, then steps 4402 to 4403 are performed; otherwise, if the imaginary part of the component is not less than the preset value, then step 4404 is performed.

[0179] Step 4402: Determine the phase reference value based on the imaginary part value and the real part value of the component.

[0180] Step 4403: Adjust the phase reference value based on the phase adjustment value to obtain the phase value of the target object under test.

[0181] Step 4404: Based on the imaginary part and the real part of the component, obtain the phase value of the target object to be measured.

[0182] In this embodiment of the application, the phase value of the target object to be measured can be obtained by the following formula:

[0183]

[0184] in, The phase value of the target object under test, x i y i These represent the real and imaginary parts of the components corresponding to the target object in the parameter matrix, respectively, where i is the index of the target object. In this embodiment, the preset value is preferably 0.

[0185] Step 450: Determine the corresponding respiratory and heartbeat waveforms based on the phase values ​​of the multi-frame radar intermediate frequency signals corresponding to the target object.

[0186] In the embodiments of this application, see the following: Figure 13 As shown, when executing step 450, the following steps are specifically performed:

[0187] Step 4501: Dewrap the phase value of each frame of radar intermediate frequency signal corresponding to the target object to determine the respiratory, heartbeat and chest displacement of the target object.

[0188] In this embodiment of the application, in order to restore the true phase value of each frame of the radar intermediate frequency signal of the target object under test, the phase value of each frame of the radar intermediate frequency signal of the target object under test needs to be unwrapped when performing step 450.

[0189] In practice, any untangling algorithm can be used to achieve the above function, and no specific limitation is made here.

[0190] Step 4502: Generate the respiratory and heartbeat waveform of the target object based on the respiratory, heartbeat, and chest displacement of the multi-frame radar intermediate frequency signal corresponding to the target object.

[0191] In this embodiment of the application, after unwinding the phase value in step 4501, the phase change obtained by unwinding is consistent with the respiratory, heartbeat, and chest displacement of the target object. Therefore, in step 4502, the respiratory, heartbeat, and chest displacement of multiple frames of radar intermediate frequency signals are collected for the target object. Based on the respiratory, heartbeat, and chest displacement of the multiple frames of radar intermediate frequency signals, the respiratory and heartbeat waveform of the target object can be obtained.

[0192] In practice, after unwinding the obtained phase value, further processing can be performed on the phase value, such as phase difference, filtering and frequency analysis, so as to obtain a more accurate respiratory, heartbeat and chest displacement of the target subject, and thus obtain a respiratory and heartbeat waveform that is more consistent with the target subject.

[0193] Furthermore, after obtaining the respiratory and heartbeat waveforms, Fourier transform analysis can be performed on the waveforms to obtain the vibration curves of the respiratory and heartbeat of the target subject.

[0194] For example, let's take the measurement of the breathing and heart rate of three subjects as an example.

[0195] For ease of description, the three test objects are referred to as Test Object 1, Test Object 2, and Test Object 3, respectively.

[0196] Figure 14 A schematic diagram of a cosine curve is shown. In this embodiment, cosine curves of different amplitudes are used to simulate the original waveforms of the respiratory and heartbeats of three subjects under test, such as... Figure 15 As shown.

[0197] In this embodiment of the application, according to Figure 15 The original waveforms of the breathing and heartbeat of the three subjects shown were used to construct the corresponding intermediate frequency sub-signals.

[0198] Assuming the radar is a millimeter-wave radar, and that it is equipped with 3 transmitting antennas and 4 receiving antennas, and that a chirp is a series of continuous frequency-modulated signals transmitted by the transmitting antennas, with the 3 transmitting antennas transmitting in turn for one round, the 4 receiving antennas can generate a total of 12 chirps of intermediate frequency sub-signals, that is, one frame of radar intermediate frequency signal.

[0199] Then, perform the following operations:

[0200] Operation 1: Perform Fourier transform on the intermediate frequency sub-signals of the 12 chirps.

[0201] Assume that the number of samples of the intermediate frequency sub-signal of each chirp is 256.

[0202] Therefore, each chirp is a 256-dimensional vector (i.e., a sequence of sampling points is a 256-dimensional vector). Performing a Fourier transform on this 256-dimensional vector yields a 256-dimensional vector, which is the first complex vector, denoted as range_fft.

[0203] Operation 2: Perform transpose operation on each of the 12 range_fft vectors, that is, transpose them all into column vectors (i.e., the second complex vectors), and concatenate them horizontally to form a 256*12 two-dimensional complex matrix, denoted as range_ffts.

[0204] Operation 3: Add (256-12) zeros to the end of each line of range_ffts to make it a 256*256 matrix.

[0205] In this embodiment of the application, after performing operation 2, the resulting range_ffts is a 256*12 matrix. In order to obtain more accurate phase values ​​in the subsequent Fourier transform, step 3 is performed to add (256-12) zeros to the end of each row of range_ffts, so that the zero-padded range_ffts is a 256*256 matrix.

[0206] Operation 4: Perform a Fourier transform on each row of the zero-padded range_ffts.

[0207] In this embodiment of the application, each row of the above range_ffts has 256 elements. Therefore, the result of the Fourier transform is still a 256-dimensional vector.

[0208] Then, these vectors are concatenated in order from top to bottom to obtain a new 256*256 matrix, namely the parameter matrix, denoted as R_A matrix, where each element in the parameter matrix (i.e., the component of the target complex vector) is a complex number.

[0209] Operation 5: Calculate the modulus matrix of the R_A matrix, and filter the target elements from the elements contained in the modulus matrix.

[0210] In this embodiment of the application, based on the above formula 4, the modulus value of each element contained in the R_A matrix is ​​obtained, and the above modulus matrix is ​​generated based on the obtained modulus value.

[0211] Then, target elements are selected from the elements contained in the modulus matrix, that is, elements whose modulus value is greater than the threshold are determined.

[0212] In some preferred embodiments, after determining the modulus matrix, the position of the peak value is found in the modulus matrix, that is, the target element is the element in the modulus matrix whose modulus value is the peak value.

[0213] Suppose that the modulus of the R_A matrix contains three peaks, and the index coordinates of the three peaks are (171, 61), (86, 61), and (171, 101) respectively.

[0214] Therefore, these three peaks are the positions of the three objects to be tested in this embodiment of the application. The index coordinate information of the three target elements is obtained as (171, 61), (86, 61), and (171, 101) respectively.

[0215] Operation 6: Select the component corresponding to the target element from the R_A matrix.

[0216] In this embodiment of the application, based on the index coordinate information of the above three target elements, the component corresponding to each index coordinate information is selected from the R_A matrix, that is, R_A(171, 61), R_A(86, 61), and R_A(171, 101) are extracted from the R_A matrix.

[0217] Step 7: Calculate the phase value corresponding to each component to obtain the phase values ​​of the three objects under test.

[0218] In this embodiment of the application, Formula 5 is used to calculate the phase values ​​of the three extracted components, thereby obtaining the phase values ​​of the three objects to be measured.

[0219] Operation 8: Execute operations 1 to 7 to obtain the phase values ​​of the three objects under test in one frame of radar intermediate frequency signal (i.e., intermediate frequency sub-signal of 12 chrips). Repeat operations 1 to 7 multiple times to obtain the phase values ​​of the three objects under test in multiple frames of radar intermediate frequency signal.

[0220] Operation 9: Detangle the phase values ​​of the three test objects obtained in Operation 8 to obtain the respiratory, heartbeat, and chest cavity displacement of each of the three test objects. Based on the respiratory, heartbeat, and chest cavity displacement of each test object in the multi-frame radar intermediate frequency signal, obtain the corresponding respiratory and heartbeat waveform.

[0221] Step 10: Normalize the respiratory and heart rate waveforms of each subject with the corresponding original waveforms, and compare the normalized analysis waveforms with the original waveforms. The corresponding comparison diagrams are shown below. Figure 16 (Corresponding to test object 1) Figure 17 (corresponding to test object 2) and Figure 18 (As shown in the figure for test object 3).

[0222] The comparison shows that the trend of the analyzed waveform is basically the same as that of the original waveform. There is an overall offset between the analyzed waveform and the original waveform of some test objects. However, since the above-mentioned overall offset does not affect the frequency analysis results when performing respiratory and heartbeat signal frequency analysis on the test objects, it can be ignored.

[0223] In summary, the method for measuring the respiratory and heartbeat of multiple objects provided in this application directly analyzes the radar intermediate frequency signal and uses range Fourier transform and angle Fourier transform to directly separate the phase changes of each of the objects under test. Since, according to prior knowledge, each phase change is equivalent to its own respiratory and heartbeat curve, the respiratory and heartbeat waveforms of each object under test can be obtained, improving the measurement accuracy and solving the problem of low measurement accuracy in the measurement of multiple targets by traditional beamforming. More importantly, the objects under test only need to remain stationary during the measurement process, which improves the convenience and wide applicability of the solution.

[0224] It should be noted that in the embodiments of this application, Formulas 1 to 5 are only used as examples of cosine waves to introduce this solution. In actual applications, radar transmits cosine waves and sine waves alternately. If the frequency modulation signal currently transmitted is a sine wave, the cosine in Formulas 1 to 5 needs to be adjusted to a sine wave accordingly, but the overall process of this solution is the same.

[0225] Based on the same inventive concept, see [reference] Figure 19 As shown, this application provides an apparatus for measuring the respiratory and heart rate of multiple subjects, comprising:

[0226] The first determining module 1910 is used to determine a parameter matrix based on each frame of radar intermediate frequency signal, wherein each frame of radar intermediate frequency signal includes multiple intermediate frequency sub-signals, each intermediate frequency sub-signal carries multiple respiratory and heartbeat information of the target object, and the parameter matrix is ​​obtained by splicing the target complex vector of each intermediate frequency sub-signal, and the index value of each component of the target complex vector in the parameter matrix represents the distance and azimuth information with the radar.

[0227] The filtering module 1920 is used to determine the corresponding modulus matrix based on the parameter matrix, and to filter out target elements from the elements contained in the modulus matrix, wherein the target elements represent the respiratory and heartbeat information of the subject to be tested, and the modulus value of the target elements is greater than a threshold.

[0228] The second determining module 1930 is used to select the component corresponding to the target element from the parameter matrix and determine the phase value of the target object to be tested based on the component, wherein the target object to be tested is any one of the plurality of objects to be tested;

[0229] The third determining module 1940 is used to determine the corresponding respiratory and heartbeat waveform based on the phase value of the multi-frame radar intermediate frequency signal corresponding to the target object under test.

[0230] In one possible implementation, the parameter matrix is ​​determined based on each frame of radar intermediate frequency signal, wherein the first determining module 1910 is used to:

[0231] For each intermediate frequency sub-signal included in each frame of radar intermediate frequency signal, sampling is performed according to a preset sampling period to obtain the corresponding sampling point sequence;

[0232] Perform a Fourier transform on each sampling point sequence to obtain the corresponding first complex vector, and then perform a transpose operation on each first complex vector to obtain the corresponding second complex vector;

[0233] Based on the receiving antenna array of the radar, the various second complex vectors are spliced ​​together to obtain a complex matrix;

[0234] Perform a Fourier transform on each row of the complex vectors in the complex matrix to obtain the target complex vector corresponding to each row, and then concatenate the target complex vectors to obtain the parameter matrix.

[0235] In one possible implementation, the step of determining the corresponding modulus matrix based on the parameter matrix, wherein the filtering module 1920 is used for:

[0236] Based on the real and imaginary parts of each component in the parameter matrix, determine the corresponding modulus value;

[0237] The modulus matrix is ​​generated based on each modulus value, wherein the modulus matrix and the parameter matrix have the same number of rows and columns, and any component has the same index value as the modulus value corresponding to that component.

[0238] In one possible implementation, the second determining module 1930 is used to: select the component corresponding to the target element from the parameter matrix.

[0239] Obtain the index value of the target element in the modulus matrix;

[0240] Select the component corresponding to the index value from the parameter matrix.

[0241] In one possible implementation, the second determining module 1930 is used to determine the phase value of the target object based on the component, wherein the second determining module 1930 is configured to:

[0242] If the imaginary part of the component is not less than a preset value, then the phase value of the target object to be measured is obtained based on the imaginary part and the real part of the component.

[0243] If the imaginary part of the component is less than a preset value, a phase reference value is determined based on the imaginary part and the real part of the component, and the phase reference value is adjusted based on the phase adjustment value to obtain the phase value of the target object to be measured.

[0244] In one possible implementation, the third determining module 1940 is used to determine the corresponding respiratory and heartbeat waveform based on the phase values ​​of the multi-frame radar intermediate frequency signals corresponding to the target object, wherein the third determining module 1940 is used to:

[0245] The phase value of each frame of radar intermediate frequency signal corresponding to the target object is unwrapped to determine the respiratory, heartbeat, and chest cavity displacement of the target object.

[0246] Based on the respiratory, heartbeat, and chest cavity displacement of the multi-frame radar intermediate frequency signal corresponding to the target object, the respiratory and heartbeat waveform of the target object is generated.

[0247] In one possible implementation, if the radar is a millimeter-wave radar and the millimeter-wave radar is equipped with multiple transmitting antennas and multiple receiving antennas, then each intermediate frequency sub-signal is obtained by mixing the frequency-modulated signal transmitted by any of the multiple transmitting antennas and the echo signal received by any of the multiple receiving antennas using a mixer.

[0248] Based on the same inventive concept, this application provides an electronic device, the structure of which can be as follows: Figure 20 As shown, it includes components such as: communication component 2010, memory 2020, display unit 2030, camera 2040, sensor 2050, audio circuit 2060, Bluetooth module 2070, and processor 2080.

[0249] The communication component 2010 is used to communicate with a server or other devices. In some embodiments, it may include a Wireless Fidelity (WiFi) module, which is a short-range wireless transmission technology that allows electronic devices to help users send and receive information.

[0250] The memory 2020 can be used to store software programs and data. The processor 2080 executes various functions of the electronic device and data processing by running the software programs or data stored in the memory 2020. The memory 2020 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. The memory 2020 stores an operating system that enables the electronic device to run. In this application, the memory 2020 may store the operating system and various applications, and may also store code that executes the image enhancement method of the embodiments of this application.

[0251] The display unit 2030 can also be used to display information input by the user or information provided to the user, as well as various menus of the electronic device, forming a graphical user interface (GUI). Specifically, the display unit 2030 may include a display screen 2032 disposed on the front of the electronic device. The display screen 2032 may be configured as a liquid crystal display, a light-emitting diode, or the like. The display unit 2030 can be used to display the image to be classified and the corresponding classification results in the embodiments of this application.

[0252] The display unit 2030 can also be used to receive input digital or character information and generate signal inputs related to user settings and function control of the electronic device. Specifically, the display unit 2030 may include a touch screen 2031 disposed on the front of the electronic device, which can collect touch operations of the user on or near it, such as clicking a button, dragging a scroll box, etc.

[0253] The touchscreen 2031 can be placed on top of the display screen 2032, or the touchscreen 2031 and the display screen 2032 can be integrated to realize the input and output functions of the electronic device. After integration, it can be referred to as a touch display screen. In this application, the display unit 2030 can display the application program and the corresponding operation steps.

[0254] Camera 2040 can be used to capture still images, and users can transmit underwater images captured by camera 2040 to other devices for processing. There can be one or multiple cameras 2040. An object is projected onto a photosensitive element through a lens, generating an optical image. The photosensitive element can be a charge-coupled device (CCD) or a complementary metal-oxide-semiconductor (CMOS) phototransistor. The photosensitive element converts the light signal into an electrical signal, which is then transmitted to processor 2080 to be converted into a digital image signal.

[0255] The electronic device may also include at least one sensor 2050, such as an accelerometer 2051, a proximity sensor 2052, a fingerprint sensor 2053, and a temperature sensor 2054. The electronic device may also be equipped with other sensors such as a gyroscope, barometer, hygrometer, thermometer, infrared sensor, light sensor, and motion sensor.

[0256] Audio circuitry 2060, speaker 2061, and microphone 2062 provide an audio interface between the user and the electronic device. Audio circuitry 2060 converts received audio data into electrical signals and transmits them to speaker 2061, where speaker 2061 converts them into sound signals for output. The electronic device can also be equipped with volume buttons for adjusting the volume of the sound signal. On the other hand, microphone 2062 converts collected sound signals into electrical signals, which are then received by audio circuitry 2060, converted into audio data, and output to communication component 2010 for transmission to, for example, another electronic device, or to memory 2020 for further processing.

[0257] The Bluetooth module 2070 is used to interact with other Bluetooth devices that also have a Bluetooth module via the Bluetooth protocol. For example, an electronic device can establish a Bluetooth connection with a wearable electronic device (such as a smartwatch) that also has a Bluetooth module through the Bluetooth module 2070, thereby exchanging data.

[0258] The processor 2080 is the control center of the electronic device, connecting various parts of the terminal through various interfaces and lines. It executes software programs stored in the memory 2020 and calls data stored in the memory 2020 to perform various functions and process data. In some embodiments, the processor 2080 may include one or more processing units; the processor 2080 may also integrate an application processor and a baseband processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the baseband processor mainly handles wireless communication. It is understood that the baseband processor may not be integrated into the processor 2080. In this application, the processor 2080 can run an operating system, applications, user interface display and touch response, and the image enhancement method of this embodiment. Furthermore, the processor 2080 is coupled to the display unit 2030.

[0259] Based on the same inventive concept, embodiments of this application provide a computer-readable storage medium that, when the instructions in the storage medium are executed by a processor, enables the processor to perform any of the methods executed by the apparatus for measuring the respiratory and heartbeats of multiple objects in the above embodiments.

[0260] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0261] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to this application. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in one or more blocks of the flowchart illustrations and / or one or more blocks of the block diagrams.

[0262] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means that implement the functions specified in one or more processes in a flowchart and / or one or more blocks in a block diagram.

[0263] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, such that the instructions, which execute on the computer or other programmable apparatus, provide steps for implementing the functions specified in one or more processes in the flowchart and / or one or more blocks in the block diagram.

[0264] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for measuring the respiratory and heart rate of multiple subjects, characterized in that, include: Based on each frame of radar intermediate frequency signal, a parameter matrix is ​​determined, wherein each frame of radar intermediate frequency signal includes multiple intermediate frequency sub-signals, each intermediate frequency sub-signal carries multiple respiratory and heartbeat information of the target object, and the parameter matrix is ​​obtained by concatenating the target complex vectors of each intermediate frequency sub-signal, and the index value of each component of the target complex vector in the parameter matrix represents the range and azimuth information; A modulo operation is performed on each component of the parameter matrix to generate a modulo matrix with the same number of rows and columns as the parameter matrix. Elements in the modulo matrix whose modulo values ​​are greater than a threshold are taken as target elements. The index values ​​of the target elements in the modulo matrix correspond to a distance index and a bearing index, which are used to characterize the distance and bearing of a target object relative to the radar. Components with the same index value as the target element are selected from the parameter matrix, and the phase value of the target object to be tested is determined based on the components, wherein the target object to be tested is any one of the plurality of objects to be tested; Based on the phase values ​​of the multi-frame radar intermediate frequency signals corresponding to the target object, the corresponding respiratory and heartbeat waveforms are determined.

2. The method as described in claim 1, characterized in that, The determination of the parameter matrix based on each frame of radar intermediate frequency signal includes: For each intermediate frequency sub-signal included in each frame of radar intermediate frequency signal, sampling is performed according to a preset sampling period to obtain the corresponding sampling point sequence; Perform a Fourier transform on each sampling point sequence to obtain the corresponding first complex vector, and then perform a transpose operation on each first complex vector to obtain the corresponding second complex vector; Based on the receiving antenna array of the radar, the various second complex vectors are spliced ​​together to obtain a complex matrix; Perform a Fourier transform on each row of the complex vectors in the complex matrix to obtain the target complex vector corresponding to each row, and then concatenate the target complex vectors to obtain the parameter matrix.

3. The method as described in claim 1, characterized in that, The step of performing a modulo operation on each component of the parameter matrix to generate a modulo matrix with the same number of rows and columns as the parameter matrix includes: Based on the real and imaginary parts of each component in the parameter matrix, determine the corresponding modulus value; The modulus matrix is ​​generated based on each modulus value, wherein any component has the same index value as the modulus value corresponding to that component.

4. The method as described in claim 3, characterized in that, Selecting the component from the parameter matrix that has the same index value as the target element includes: Obtain the index value of the target element in the modulus matrix; Select the component corresponding to the index value from the parameter matrix.

5. The method as described in claim 1, characterized in that, Determining the phase value of the target object based on the component includes: If the imaginary part of the component is not less than a preset value, then the phase value of the target object to be measured is obtained based on the imaginary part and the real part of the component. If the imaginary part of the component is less than a preset value, a phase reference value is determined based on the imaginary part and the real part of the component, and the phase reference value is adjusted based on the phase adjustment value to obtain the phase value of the target object to be measured.

6. The method as described in claim 1, characterized in that, The step of determining the corresponding respiratory and heartbeat waveform based on the phase values ​​of the multi-frame radar intermediate frequency signals corresponding to the target object includes: The phase value of each frame of radar intermediate frequency signal corresponding to the target object is unwrapped to determine the respiratory, heartbeat, and chest cavity displacement of the target object. Based on the respiratory, heartbeat, and chest cavity displacement of the multi-frame radar intermediate frequency signal corresponding to the target object, the respiratory and heartbeat waveform of the target object is generated.

7. The method according to any one of claims 1-6, characterized in that, If the radar is a millimeter-wave radar, and the millimeter-wave radar is equipped with multiple transmitting antennas and multiple receiving antennas, then each intermediate frequency sub-signal is obtained by mixing the frequency-modulated signal transmitted by any of the multiple transmitting antennas and the echo signal received by any of the multiple receiving antennas using a mixer.

8. A device for measuring the respiratory and heart rate of multiple subjects, characterized in that, include: The first determining module is used to determine a parameter matrix based on each frame of radar intermediate frequency signal, wherein each frame of radar intermediate frequency signal includes multiple intermediate frequency sub-signals, each intermediate frequency sub-signal carries multiple respiratory and heartbeat information of the target object, and the parameter matrix is ​​obtained by concatenating the target complex vectors of each intermediate frequency sub-signal, and the index value of each component of the target complex vector in the parameter matrix represents the range and azimuth information; The filtering module is used to perform a modulo operation on each component in the parameter matrix to generate a modulo matrix with the same number of rows and columns as the parameter matrix, and to take the elements in the modulo matrix whose modulo value is greater than a threshold as target elements. The index value of the target element in the modulo matrix corresponds to a distance index and a bearing index, which are used to characterize the distance and bearing of a target object relative to the radar. The second determining module is used to select components from the parameter matrix that have the same index value as the target element, and determine the phase value of the target object based on the components, wherein the target object is any one of the plurality of objects to be tested; The third determining module is used to determine the corresponding respiratory and heartbeat waveform based on the phase value of the multi-frame radar intermediate frequency signal corresponding to the target object under test.

9. An electronic device, characterized in that, include: Memory is used to store computer programs that can be executed by the controller; The controller is connected to the memory and is configured to perform the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, When the instructions in the storage medium are executed by the processor, the processor is able to perform the method as described in any one of claims 1-7.

Images