Processing method of ultra-wideband UWB life signal

Abstract

The present application proposes a method, device, electronic device and storage medium for processing ultra-wideband UWB life signals. The method includes: collecting multiple echo signals corresponding to ultra-wideband UWB life signals to obtain a first echo signal matrix composed of multiple echo signals, then obtaining a second echo signal matrix after the first echo signal matrix is ​​subjected to clutter preprocessing, and performing singular value decomposition to obtain multiple singular values ​​corresponding to the second echo signal matrix, screening the multiple singular values ​​and performing important item screening to obtain multiple main singular values, and generating a third echo signal matrix corresponding to multiple main singular values, and then performing signal decomposition to obtain an intrinsic modal component matrix corresponding to the third echo signal matrix, and reconstructing the target ultra-wideband UWB life signal according to the intrinsic modal component matrix, thereby accurately determining the target ultra-wideband UWB life signal based on the decomposition and reconstruction processing of the ultra-wideband UWB life signal, and improving the processing accuracy of the ultra-wideband UWB life signal.

Description

Technical Field

[0001] The present application relates to the technical field of signal processing, and in particular to a method, device, electronic device and storage medium for processing ultra-wideband (UWB) life signals. Background Art

[0002] At present, with the rapid development of ultra-wideband radar detection and imaging technology, the use of ultra-wideband radar for life signal detection is an important application in this field. In the process of life signal detection, the micro-motion of the body surface caused by human activities, environmental noise, linear drift caused by equipment, detector noise, thermal noise, etc. will cause interference, which will interfere with the extraction and analysis of life signals. In related technologies, methods for data processing of life signals include: median filtering, Gaussian filtering, wavelet transform, empirical mode decomposition method, etc., but these methods for data processing of life signals have certain limitations, so a more efficient ultra-wideband UWB life signal processing method is urgently needed. Summary of the invention

[0003] The present application proposes a method, device, electronic device and storage medium for processing ultra-wideband (UWB) life signals.

[0004] The first aspect of the present application proposes a method for processing an ultra-wideband UWB life signal, the method comprising: collecting multiple echo signals corresponding to the ultra-wideband UWB life signal to obtain a first echo signal matrix composed of the multiple echo signals; performing clutter preprocessing on the multiple echo signals in the first echo signal matrix to obtain a second echo signal matrix without clutter; performing singular value decomposition processing on the second echo signal matrix to obtain multiple singular values ​​corresponding to the second echo signal matrix; performing important item screening on the sum of the multiple singular values ​​to obtain multiple main singular values, and generating a third echo signal matrix corresponding to the multiple main singular values; performing signal decomposition on the multiple echo signals in the third echo signal matrix to obtain an intrinsic modal component matrix corresponding to the third echo signal matrix; and reconstructing the ultra-wideband UWB life signal according to the intrinsic modal component matrix.

[0005] In one embodiment of the present application, the performing clutter elimination preprocessing on the multiple echo signals in the first echo signal matrix to obtain a second echo signal matrix without clutter includes: preprocessing the multiple echo signals in the first echo signal matrix with a first frequency clutter using a channel signal subtraction method to obtain a first clutter matrix; preprocessing the multiple echo signals in the first echo signal matrix with a second frequency clutter using a time subtraction averaging algorithm to obtain a second clutter matrix; and subtracting the difference between the first clutter matrix and the second clutter matrix from the first echo signal matrix to obtain a second echo signal matrix.

[0006] In one embodiment of the present application, the important item screening of the multiple singular values ​​and to obtain multiple main singular values, and generating a third echo signal matrix corresponding to the multiple main singular values, includes: obtaining the gradient difference between adjacent singular values ​​in the multiple singular values; taking the adjacent singular values ​​whose gradient difference is greater than a preset gradient threshold as candidate singular values; obtaining the relative numerical value of each of the candidate singular values; taking the candidate singular value whose relative numerical value is less than a preset numerical value as the main singular value; determining the main singular matrix component corresponding to the main singular value according to the mapping relationship between the main singular value and the singular value matrix component; and combining the main singular value and the main singular matrix component into the third echo signal matrix.

[0007] In one embodiment of the present application, the signal decomposition of multiple echo signals in the third echo signal matrix to obtain an intrinsic modal component matrix corresponding to the third echo signal matrix includes: acquiring multiple white noise signals of different frequencies; adding the multiple white noise signals of different frequencies to the multiple echo signals in the third echo signal matrix to obtain multiple fourth echo signal matrices containing white noise signals of different frequencies; signal decomposition of the multiple fourth echo signal matrices to obtain multiple candidate intrinsic modal component matrices; and taking the mean of the multiple candidate intrinsic modal component matrices as the intrinsic modal component matrix corresponding to the third echo signal matrix.

[0008] In one embodiment of the present application, after the main singular values ​​and the main singular matrix components are combined into the third echo signal matrix, it also includes: obtaining the spatial eigenvectors and time eigenvectors corresponding to each of the main singular values ​​in the main singular matrix components; storing each of the main singular values ​​together with the spatial eigenvectors and the time eigenvectors as a group of data, and storing them in a container.

[0009] In one embodiment of the present application, after performing clutter preprocessing on the multiple echo signals in the first echo signal matrix to obtain a second echo signal matrix without clutter, the method further includes: performing signal enhancement on the multiple echo signals in the second echo signal matrix.

[0010] The present application proposes a method for processing an ultra-wideband UWB life signal, which collects multiple echo signals corresponding to the ultra-wideband UWB life signal to obtain a first echo signal matrix composed of multiple echo signals, then obtains a second echo signal matrix after the first echo signal matrix is ​​subjected to clutter preprocessing, and performs singular value decomposition to obtain multiple singular values ​​corresponding to the second echo signal matrix, performs important item screening on the multiple singular values ​​and to obtain multiple main singular values, and generates a third echo signal matrix corresponding to the multiple main singular values, then performs signal decomposition to obtain an intrinsic mode component matrix corresponding to the third echo signal matrix, and reconstructs the target ultra-wideband UWB life signal according to the intrinsic mode component matrix. Thus, based on the decomposition and reconstruction processing of the ultra-wideband UWB life signal, the target ultra-wideband UWB life signal is accurately determined, and the processing accuracy of the ultra-wideband UWB life signal is improved.

[0011] The second aspect of the present application proposes a processing device for an ultra-wideband UWB life signal, the device comprising: an acquisition module, used to acquire multiple echo signals corresponding to the ultra-wideband UWB life signal to obtain a first echo signal matrix composed of the multiple echo signals; a preprocessing module, used to perform noise preprocessing on the multiple echo signals in the first echo signal matrix to obtain a second echo signal matrix without noise; a first decomposition module, used to perform singular value decomposition processing on the second echo signal matrix to obtain multiple singular values ​​corresponding to the second echo signal matrix; a generation module, used to screen the multiple singular values ​​and perform important item screening to obtain multiple main singular values, and generate a third echo signal matrix corresponding to the multiple main singular values; a second decomposition module, used to perform signal decomposition on the multiple echo signals in the third echo signal matrix to obtain an intrinsic modal component matrix corresponding to the third echo signal matrix; a reconstruction module, used to reconstruct the ultra-wideband UWB life signal according to the intrinsic modal component matrix.

[0012] In one embodiment of the present application, the preprocessing module is specifically used to: use a channel signal subtraction method to preprocess the first frequency clutter of the multiple echo signals in the first echo signal matrix to obtain a first clutter matrix; use a time subtraction average algorithm to preprocess the second frequency clutter of the multiple echo signals in the first echo signal matrix to obtain a second clutter matrix; and use the difference between the first clutter matrix and the second clutter matrix subtracted from the first echo signal matrix as the second echo signal matrix.

[0013] In one embodiment of the present application, the generation module is specifically used to: obtain the gradient difference between adjacent singular values ​​among the multiple singular values; use the adjacent singular values ​​whose gradient difference is greater than a preset gradient threshold as candidate singular values; obtain the relative numerical value of each of the candidate singular values; use the candidate singular value whose relative numerical value is less than a preset numerical value as the main singular value; determine the main singular matrix component corresponding to the main singular value according to the mapping relationship between the main singular value and the singular value matrix component; and combine the main singular value and the main singular matrix component into the third echo signal matrix.

[0014] In one embodiment of the present application, the second decomposition module is specifically used to: obtain multiple white noise signals of different frequencies; add the multiple white noise signals of different frequencies to the multiple echo signals in the third echo signal matrix to obtain multiple fourth echo signal matrices containing white noise signals of different frequencies; perform signal decomposition on the multiple fourth echo signal matrices to obtain multiple candidate intrinsic modal component matrices; and use the mean of the multiple candidate intrinsic modal component matrices as the intrinsic modal component matrix corresponding to the third echo signal matrix.

[0015] In one embodiment of the present application, the generation module is further specifically used to: obtain the spatial eigenvectors and time eigenvectors corresponding to each of the main singular values ​​in the main singular matrix components; store each of the main singular values, the spatial eigenvectors and the time eigenvectors as a group of storage data, and store them in a container.

[0016] In one embodiment of the present application, the enhancement module is used to perform signal enhancement on multiple echo signals in the second echo signal matrix.

[0017] The present application proposes a processing device for an ultra-wideband UWB life signal, which collects multiple echo signals corresponding to an ultra-wideband UWB life signal to obtain a first echo signal matrix composed of multiple echo signals, then obtains a second echo signal matrix after the first echo signal matrix is ​​subjected to clutter preprocessing, and performs singular value decomposition to obtain multiple singular values ​​corresponding to the second echo signal matrix, performs important item screening on the sum of the multiple singular values ​​to obtain multiple main singular values, and generates a third echo signal matrix corresponding to the multiple main singular values, and then performs signal decomposition to obtain an intrinsic mode component matrix corresponding to the third echo signal matrix, and reconstructs a target ultra-wideband UWB life signal according to the intrinsic mode component matrix. Thus, based on the decomposition and reconstruction processing of the ultra-wideband UWB life signal, the target ultra-wideband UWB life signal is accurately determined, and the processing accuracy of the ultra-wideband UWB life signal is improved.

[0018] The third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the method for processing ultra-wideband (UWB) life signals in the embodiment of the present application is implemented.

[0019] The fourth aspect of the present application provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, a method for processing an ultra-wideband UWB life signal in the embodiment of the present application is provided.

[0020] Other effects of the above optional manner will be described below in conjunction with specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0022] Figure 1 It is a flowchart of a method for processing an ultra-wideband UWB life signal provided in an embodiment of the present application;

[0023] Figure 2 A first echo signal matrix X provided in the embodiment of the present application m×n Schematic diagram of time domain information;

[0024] Figure 3 A second echo signal matrix R provided in an embodiment of the present application m×n Schematic diagram of time domain information;

[0025] Figure 4 It is a flowchart of another method for processing ultra-wideband UWB life signals provided in an embodiment of the present application;

[0026] Figure 5 It is a flowchart of another method for processing ultra-wideband UWB life signals provided in an embodiment of the present application;

[0027] Figure 6 A singular value numerical scree plot using the Cattell scree test method provided in an embodiment of the present application;

[0028] Figure 7 A schematic diagram of a spatial eigenvector corresponding to a first-order singular value provided in an embodiment of the present application;

[0029] Figure 8 A schematic diagram of a time characteristic vector corresponding to a first-order singular value provided in an embodiment of the present application;

[0030] Fig. 9A schematic diagram of a spatial eigenvector corresponding to a second-order singular value provided in an embodiment of the present application;

[0031] Fig.10 A schematic diagram of a time characteristic vector corresponding to a second-order singular value provided in an embodiment of the present application;

[0032] Fig.11 A schematic diagram of a spatial eigenvector corresponding to a third-order singular value provided in an embodiment of the present application;

[0033] Fig.12 A schematic diagram of a time characteristic vector corresponding to a third-order singular value provided in an embodiment of the present application;

[0034] Fig.13 A comparison diagram of the data volume of a first echo signal matrix and a third echo signal provided in an embodiment of the present application;

[0035] Fig.14 A schematic diagram of time domain information of a third echo signal matrix provided in an embodiment of the present application;

[0036] Fig.15 It is a flowchart of another method for processing ultra-wideband UWB life signals provided in an embodiment of the present application;

[0037] Fig.16 A schematic diagram of a reconstructed breathing signal provided in an embodiment of the present application;

[0038] Fig.17 A schematic diagram of a reconstructed heartbeat signal provided in an embodiment of the present application;

[0039] Fig.18 It is a structural schematic diagram of an ultra-wideband UWB life signal processing device provided in an embodiment of the present application;

[0040] Fig.19 It is a structural schematic diagram of another ultra-wideband UWB life signal processing device provided in an embodiment of the present application;

[0041] Fig. 20 It is a block diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0042] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0043] The following describes an ultra-wideband UWB vital signal processing method, device, and electronic device according to an embodiment of the present application with reference to the accompanying drawings.

[0044] Figure 1 It is a flow chart of a method for processing an ultra-wideband UWB life signal provided in an embodiment of the present application. It should be noted that the execution subject of the method for processing an ultra-wideband UWB life signal provided in this embodiment is an ultra-wideband UWB life signal processing device, which can be implemented by software and / or hardware. The ultra-wideband UWB life signal processing device in this embodiment can be configured in an electronic device, and the electronic device in this embodiment can include a server. This embodiment does not specifically limit the electronic device.

[0045] Figure 1 It is a flowchart of a method for processing an ultra-wideband UWB life signal provided in an embodiment of the present application.

[0046] like Figure 1 As shown, the processing method of the ultra-wideband UWB life signal may include:

[0047] Step 101 : collecting a plurality of echo signals corresponding to an ultra-wideband UWB life signal to obtain a first echo signal matrix composed of the plurality of echo signals.

[0048] In some embodiments, ultra wide band (UWB) life signals may be collected by an ultra wide band radar, but is not limited thereto.

[0049] In some embodiments, the ultra-wideband UWB vital signal may include a heartbeat signal and a breathing signal, but is not limited thereto, and this embodiment does not specifically limit this.

[0050] In some embodiments, a life detector in an ultra-wideband radar may be used to transmit a continuous periodic pulse sequence to detect the area of ​​an ultra-wideband UWB life signal and perform sampling, thereby obtaining a continuous plurality of groups of multiple echo signals {X1, X2, X3, ..., X n}, and then arrange the multiple echo signals obtained by sampling each pulse sequence in rows to form a first echo signal matrix X mxn , the first echo signal matrix X mxn The representation form can be:

[0051]

[0052] Among them, the frequency of transmitting periodic pulse sequence can be F PR , the frequency of collecting life signals can be F S, m, n (m>1, n>1, and m, n are integers) are matrices X mxn The number of rows and columns also represent the number of samples of the same pulse wave and the number of pulses in a continuous periodic pulse sequence, respectively.

[0053] In some embodiments, after obtaining a first echo signal matrix X composed of a plurality of echo signals mxn Afterwards, the first echo signal matrix X can be generated mxn The corresponding time domain information, such as Figure 2 As shown, according to the first echo signal matrix X mxn The corresponding time domain information can accurately determine the problem of time domain information coupling when collecting ultra-wideband UWB life signals.

[0054] Step 102: performing clutter preprocessing on a plurality of echo signals in the first echo signal matrix to obtain a second echo signal matrix without clutter.

[0055] In some embodiments, the clutter in the multiple echo signals may include, but is not limited to, multiple reflection clutter outside the wall formed by signal waves and strong clutter, coupled signal clutter between objects and antennas, thermal noise clutter caused by passive components in the circuit, and linear trend clutter caused by DC components. This embodiment does not make specific limitations on this.

[0056] In some embodiments, by performing clutter preprocessing of different frequencies on multiple echo signals in the first echo signal matrix to obtain a more accurate second echo signal matrix without clutter, the influence of clutter on ultra-wideband UWB life signals is minimized.

[0057] In other embodiments, after performing clutter preprocessing on multiple echo signals in the first echo signal matrix to obtain a second echo signal matrix without clutter, in order to improve the availability of the second echo signal matrix, signal enhancement may be performed on the multiple echo signals in the second echo signal matrix, thereby making the multiple echo signals in the second echo signal matrix clearer.

[0058] The signal of the second echo signal matrix may be enhanced by using a priori normalization and automatic gain control (AGC), but is not limited thereto.

[0059] In some embodiments, in order to more clearly determine the time domain information corresponding to the vital signal, such as Figure 3 As shown, the present application proposes a time domain information diagram of the second echo signal matrix after clutter preprocessing.

[0060] Step 103: Perform singular value decomposition processing on the second echo signal matrix to obtain a plurality of singular values ​​corresponding to the second echo signal matrix.

[0061] In some embodiments, after performing singular value decomposition processing on the second echo signal matrix, a singular value matrix corresponding to the second echo signal matrix can be obtained, and then multiple singular values ​​corresponding to the second echo signal matrix are obtained from the main diagonal line of the singular value matrix.

[0062] Step 104 , screening the important items of the plurality of singular values ​​and , so as to obtain a plurality of main singular values, and generating a third echo signal matrix corresponding to the plurality of main singular values.

[0063] In some embodiments, screening conditions for important singular value items may be preset, singular values ​​that meet the screening conditions may be used as main singular values, and singular values ​​that do not meet the screening conditions may be discarded, thereby improving the analysis efficiency of singular values.

[0064] The screening conditions for the important singular value items may be set according to a descending gradient threshold between multiple singular values ​​and relative values ​​of multiple singular values, but are not limited thereto.

[0065] Step 105: performing signal decomposition on a plurality of echo signals in the third echo signal matrix to obtain an intrinsic mode component matrix corresponding to the third echo signal matrix.

[0066] In some embodiments, Ensemble Empirical Mode Decomposition (EEMD) may be used to perform signal decomposition on multiple echo signals in the third echo signal matrix, but the present invention is not limited thereto.

[0067] In some embodiments, the set empirical mode decomposition can be controlled to perform signal decomposition on multiple echo signals in the third echo signal matrix to obtain an intrinsic mode component matrix and a residual component matrix. The residual component can be discarded to improve the signal decomposition efficiency of the third echo signal matrix.

[0068] Step 106: reconstruct the ultra-wideband UWB life signal according to the intrinsic mode component matrix.

[0069] In some embodiments, different ultra-wideband UWB life signals can be constructed according to the inherent modal component matrices in different frequency ranges. Specifically, the human heart rate and breathing rate can be taken as examples. For example, the distribution range of the heart rate is 1 to 2.5 Hz, and the distribution range of the breathing rate is 0.2 to 0.8 Hz. Thus, according to the inherent modal component matrices in the heart rate and breathing rate ranges, the heart rate signal and the breathing signal can be reconstructed to accurately determine the ultra-wideband UWB life signal.

[0070] The present application proposes a method for processing an ultra-wideband UWB life signal, which collects multiple echo signals corresponding to the ultra-wideband UWB life signal to obtain a first echo signal matrix composed of multiple echo signals, then obtains a second echo signal matrix after the first echo signal matrix is ​​subjected to clutter preprocessing, and performs singular value decomposition to obtain multiple singular values ​​corresponding to the second echo signal matrix, performs important item screening on the multiple singular values ​​and to obtain multiple main singular values, and generates a third echo signal matrix corresponding to the multiple main singular values, then performs signal decomposition to obtain an intrinsic mode component matrix corresponding to the third echo signal matrix, and reconstructs the target ultra-wideband UWB life signal according to the intrinsic mode component matrix. Thus, based on the decomposition and reconstruction processing of the ultra-wideband UWB life signal, the target ultra-wideband UWB life signal is accurately determined, and the processing accuracy of the ultra-wideband UWB life signal is improved.

[0071] For a clear understanding of this application, the following Figure 4 The processing process of the method for processing an ultra-wideband UWB life signal is described exemplarily, wherein this embodiment is a further refinement or expansion of the above embodiment.

[0072] like Figure 4 As shown, the processing method of the ultra-wideband UWB life signal may include:

[0073] Step 401 : collect multiple echo signals corresponding to an ultra-wideband UWB life signal to obtain a first echo signal matrix composed of the multiple echo signals.

[0074] It should be noted that, for the specific implementation of step 401, reference may be made to the relevant description in the above embodiment.

[0075] Step 402: Preprocess the first frequency clutter of multiple echo signals in the first echo signal matrix by using a channel signal subtraction method to obtain a first clutter matrix.

[0076] In some embodiments, the first frequency clutter may be background clutter in the process of ultra-wideband radar collecting ultra-wideband UWB life signals, and clutter caused by a constant component corresponding to the ultra-wideband UWB life signal, but is not limited thereto.

[0077] In some embodiments, the first echo signal matrix X is subtracted by using a channel signal subtraction method. mxn The multiple echo signals {X1, X2, X3, ..., X n One implementation method of preprocessing the first frequency clutter may be to obtain a fast time series X of any group of first echo signals. j , j = 1, 2, 3, ..., n, and use the channel signal subtraction method to perform clutter preprocessing to obtain the first clutter matrix X'. The calculation method of the first clutter matrix X' can be:

[0078] X' j =X j -X j-1

[0079] Step 403: Preprocess the second frequency clutter of multiple echo signals in the first echo signal matrix using a time-subtracted averaging algorithm to obtain a second clutter matrix.

[0080] In some embodiments, the second frequency clutter may be background clutter caused by stationary objects in the scene during the process of the ultra-wideband radar collecting the ultra-wideband UWB life signal, but is not limited thereto.

[0081] In some embodiments, the first echo signal matrix X is processed by using a time-subtracted averaging method. mxn The multiple echo signals {X1, X2, X3, ..., X n One implementation method of preprocessing the second frequency clutter may be to estimate the second clutter matrix S using a time-subtracted average method. The second clutter matrix S may be estimated in the following manner:

[0082]

[0083]

[0084] Step 404: The difference between the first echo signal matrix and the second clutter matrix is ​​obtained by subtracting the first clutter matrix from the first echo signal matrix to obtain a second echo signal matrix.

[0085] In some embodiments, the first echo signal matrix X mxn Subtract the difference between the first clutter matrix X' and the second clutter matrix S as the second echo signal matrix R mxn One way to calculate can be:

[0086] R m×n =X m×n -S-X'

[0087] Step 405: Perform singular value decomposition processing on the second echo signal matrix to obtain a plurality of singular values ​​corresponding to the second echo signal matrix.

[0088] Step 406 , screening the important items of the sum of the plurality of singular values ​​to obtain a plurality of main singular values, and generating a third echo signal matrix corresponding to the plurality of main singular values.

[0089] Step 407: performing signal decomposition on the multiple echo signals in the third echo signal matrix to obtain an intrinsic mode component matrix corresponding to the third echo signal matrix.

[0090] Step 408: reconstruct the ultra-wideband UWB life signal according to the intrinsic mode component matrix.

[0091] The present application proposes a method for processing an ultra-wideband UWB life signal, collecting multiple echo signals corresponding to the ultra-wideband UWB life signal to obtain a first echo signal matrix composed of multiple echo signals, using a channel signal subtraction method to pre-process the multiple echo signals in the first echo signal matrix with a first frequency clutter to obtain a first clutter matrix, using a time subtraction average algorithm to pre-process the multiple echo signals in the first echo signal matrix with a second frequency clutter to obtain a second clutter matrix, and using the difference between the first echo signal matrix and the second clutter matrix as the first clutter matrix. A second echo signal matrix is ​​obtained, and singular value decomposition is performed to obtain multiple singular values ​​corresponding to the second echo signal matrix, multiple singular values ​​and important items are screened to obtain multiple main singular values, and a third echo signal matrix corresponding to the multiple main singular values ​​is generated, and then signal decomposition is performed to obtain an intrinsic mode component matrix corresponding to the third echo signal matrix, and the target ultra-wideband UWB life signal is reconstructed according to the intrinsic mode component matrix. Therefore, based on the preprocessing of the life signal clutter, the target ultra-wideband UWB life signal is accurately determined, and the accuracy of extracting the ultra-wideband UWB life signal is improved.

[0092] Figure 5 It is a flowchart of another method for processing ultra-wideband UWB life signals provided in an embodiment of the present application.

[0093] Step 501 : collect multiple echo signals corresponding to an ultra-wideband UWB life signal to obtain a first echo signal matrix composed of the multiple echo signals.

[0094] Step 502: Perform clutter preprocessing on multiple echo signals in the first echo signal matrix to obtain a second echo signal matrix without clutter.

[0095] It should be noted that, for the specific implementation of step 501 to step 502, reference may be made to the relevant description in the above embodiment.

[0096] Step 503: Perform singular value decomposition processing on the second echo signal matrix to obtain a plurality of singular values ​​corresponding to the second echo signal matrix.

[0097] In some embodiments, the second echo signal matrix R mxn The calculation formula for singular value decomposition can be:

[0098]

[0099]

[0100] U m×m =[u1,u2,u3,…,u m ];

[0101] V n×n =[v1, v2, v3, …v n ];

[0102] Among them, U mxm and V nxn They are all unit orthogonal matrices, namely UU T =I and VV T =I,U mxm is called the left singular matrix, V nxn is called a right singular matrix. mxn It is called a singular value matrix, which has singular values ​​only on the main diagonal, and all other elements are 0. mxn The main diagonal elements σ1, σ2, σ3, …, σ k is the preprocessed echo signal matrix R mxn k singular values ​​of , and satisfy σ1≥σ2≥σ3≥…≥σ k .u i Denotes the matrix U mxm The i-th column vector of is called the i-th order left singular vector. i Represents the matrix V nxn The i-th column vector of is called the i-th order right singular vector. i Represents the i-th element of the singular value spectrum.

[0103] In summary, we can get the singular value matrix ∧ mxn Multiple singular values ​​corresponding to the second echo signal matrix are obtained.

[0104] Step 504: Obtain gradient differences between adjacent singular values ​​in the plurality of singular values.

[0105] In some embodiments, the principal component scree test method Cattell can be used to screen multiple singular values ​​and important items, such as Figure 6 As shown, Figure 6 To use the Cattell scree test method for the numerical scree plot of singular values, we can obtain Figure 6 In the example above, we get the gradient difference g between adjacent singular values. j , j=1,2,3,…,k-1.

[0106] Specifically, the gradient difference g between adjacent singular values j The calculation method can be:

[0107]

[0108] Step 505: Take the adjacent singular values ​​whose gradient difference is greater than the preset gradient threshold as candidate singular values.

[0109] In some embodiments, the preset gradient threshold T1 can be manually set by relevant technicians or determined in combination with the actual application scenario, and this embodiment does not make specific limitations on this.

[0110] In some embodiments, the process of taking adjacent singular values with a gradient difference greater than the preset gradient threshold as candidate singular values can be as follows: starting from g1 (j = 1), calculate g in sequence j , and judge whether g j > T1 holds. If not, let j = j + 1 and continue to calculate g j . If so, stop the calculation, record the current order j = p, and thus take the singular values between the current order p as candidate singular values.

[0111] Step 506: Obtain the relative values of each candidate singular value.

[0112] In some embodiments, the relative values h of each candidate singular value can be obtained from Figure 6 , where j = 1, 2, 3,..., k. Among them, the calculation formula for the relative value h of each candidate singular value j can be: j

[0113]

[0114] Step 507: Take the candidate singular values with relative values less than the preset value as the main singular values.

[0115] In some embodiments, the preset value T2 can be manually set by relevant technicians or determined in combination with the actual application scenario, and this embodiment does not make specific limitations on this.

[0116] In some embodiments, the process of taking the candidate singular values with relative values less than the preset value as the main singular values can be as follows: calculate the relative magnitude h of the current singular value of the j = pth order j , and judge whether h j < T2 holds. If not, let j = j + 1 and continue to calculate h j ; if so, stop the calculation, record the current order j = q, and select the first q main singular values σ1, σ2, σ3,..., σ q as the filtered result.

[0117] Step 508: Determine the main singular matrix components corresponding to the main singular values according to the mapping relationship between the main singular values and the singular value matrix components.

[0118] In some embodiments, the singular value matrix components include left singular matrix components and right singular matrix components. The left singular matrix components and right singular matrix components corresponding to the main singular values ​​are determined based on the mapping relationship between singular values ​​and singular value matrix components during singular value decomposition.

[0119] Step 509: combine the principal singular values ​​and the principal singular matrix components into a third echo signal matrix.

[0120] In some embodiments, the principal singular values ​​and the left and right singular matrix components are combined into a third echo signal matrix.

[0121] In other embodiments, in order to reduce the storage pressure of the third echo signal matrix, the third echo signal matrix may be compressed and stored according to the main singular value q, the space vector s and the time variation characteristic t of the third echo signal matrix.

[0122] Specifically, we can use the first q-order main singular values ​​σ1, σ2, σ3, …, σ q , extract the corresponding left singular vectors u1, u2, u3, ..., u q are spatial eigenvectors of various orders, and right singular vectors of various orders v1, v2, v3, …, v q , is the time characteristic vector of each order, and then coordinate conversion is performed to calculate the distance vector s corresponding to each order of spatial characteristic vector, and the time vector t corresponding to each order of time characteristic vector, where s i represents the i-th element in the distance vector s, t j Represents the jth element in the time vector t. The coordinate conversion formula can be:

[0123]

[0124] Among them, c = 3x108m / s is the speed of light, that is, the pulse detection speed, F S is the sampling frequency of the ultra-wideband UWB life signal, F PR is the frequency of the continuous pulse sequence, and the spatial eigenvector u of each order j is an m-order vector, and each order time characteristic vector v j is an n-order vector, the distance vector s is an m-order vector, and the time vector t is an n-order vector.

[0125] It is understandable that the first q order main singular values ​​σ1, σ2, σ3, ..., σ q , spatial eigenvectors u1, u2, u3, …, u q , and the time feature vectors v1, v2, v3, …, v q , one-to-one storage, that is, the j-th order main singular value σ j The corresponding spatial eigenvector u jCreate a container with the time feature vector v for corresponding storage, storing q containers in total, each container contains 3 elements, and the total amount of data in each container is m+n+1. Use it to replace the original first echo signal matrix X mxn To achieve data compression, the compression ratio ks is calculated as follows:

[0126]

[0127] In summary, in order to more clearly describe the relationship between the main singular value q of the third echo signal matrix and the space vector s and the inter-variation characteristic t, the present application takes the space vector s and the inter-variation characteristic t corresponding to the first-order, second-order and third-order singular values ​​as examples for description, such as Figure 7 , Figure 8 , Fig. 9 , Fig.10 , Fig.11 and Fig.12 .

[0128] In some other embodiments, the present application also proposes a first echo signal matrix X mxn Compared with the data volume of the third echo signal matrix after compression, Fig.13 As shown, data compression of ultra-wideband UWB life signals is achieved, reducing the storage pressure of data volume.

[0129] It can be understood that the present application also proposes a time domain information diagram of a third echo signal matrix, such as Fig.14 As shown, the compression result of the ultra-wideband UWB life signal is accurately determined according to the comparison result of the time domain information diagram of the third echo signal matrix and the time domain information diagram of the second echo signal matrix.

[0130] Step 510: perform signal decomposition on a plurality of echo signals in the third echo signal matrix to obtain an intrinsic mode component matrix corresponding to the third echo signal matrix.

[0131] Step 511: reconstruct the ultra-wideband UWB life signal according to the intrinsic mode component matrix.

[0132] The present application proposes a method for processing an ultra-wideband UWB life signal, which collects multiple echo signals corresponding to the ultra-wideband UWB life signal to obtain a first echo signal matrix composed of multiple echo signals, then obtains a second echo signal matrix after the first echo signal matrix is ​​subjected to clutter preprocessing, and performs singular value decomposition to obtain multiple singular values ​​corresponding to the second echo signal matrix, obtains gradient differences between adjacent singular values ​​in the multiple singular values, takes adjacent singular values ​​whose gradient differences are greater than a preset gradient threshold as candidate singular values, obtains values ​​of each candidate singular value, takes candidate singular values ​​whose values ​​are less than a preset value as main singular values, determines main singular matrix components corresponding to the main singular values ​​according to a mapping relationship between the main singular values ​​and the components of the singular value matrix, and then performs signal decomposition to obtain an intrinsic mode component matrix corresponding to the third echo signal matrix, and reconstructs the target ultra-wideband UWB life signal according to the intrinsic mode component matrix, thereby reducing the storage space of the ultra-wideband UWB life signal based on the main singular matrix components corresponding to the generated ultra-wideband UWB life signal.

[0133] Fig.15 It is a flowchart of another method for processing ultra-wideband UWB life signals provided in an embodiment of the present application.

[0134] Step 1501 , collecting multiple echo signals corresponding to an ultra-wideband UWB life signal to obtain a first echo signal matrix composed of the multiple echo signals.

[0135] Step 1502: perform clutter preprocessing on multiple echo signals in the first echo signal matrix to obtain a second echo signal matrix without clutter.

[0136] Step 1503: Perform singular value decomposition processing on the second echo signal matrix to obtain multiple singular values ​​corresponding to the second echo signal matrix.

[0137] Step 1504 , screening the multiple singular values ​​and for important items to obtain multiple main singular values, and generating a third echo signal matrix corresponding to the multiple main singular values.

[0138] It should be noted that, for the specific implementation of steps 1501 to 1504, reference may be made to the relevant description in the above embodiments.

[0139] Step 1505: Acquire multiple white noise signals of different frequencies.

[0140] In some embodiments, in order to suppress frequency mixing between the intrinsic modal component matrices IMF corresponding to the third echo signal, a plurality of white noise signals with different frequencies may be added to the plurality of echo signals in the third echo signal matrix.

[0141] Step 1506: Add a plurality of white noise signals of different frequencies to the plurality of echo signals in the third echo signal matrix to obtain a plurality of fourth echo signal matrices containing white noise signals of different frequencies.

[0142] In some embodiments, the multiple echo signals in the third echo signal matrix are denoted as x(t). In order to suppress mixing between the IMFs, at least one cycle process can be performed on x(t), wherein each cycle process includes: adding white noise to x(t), performing signal decomposition on x(t) after adding the white noise, and obtaining multiple IMF components and residual components.

[0143] For example, the number of execution rounds of the marking cycle process is M, where M is a positive integer. For the i-th cycle process, where i=1, 2, ..., M, random white noise with a certain frequency can be added to x(t) to obtain a plurality of echo signals x after adding white noise in the fourth echo signal matrix. i (t) is:

[0144] x i (t) = x(t) + n i (t)

[0145] Step 1507: perform signal decomposition on the plurality of fourth echo signal matrices to obtain a plurality of candidate intrinsic mode component matrices.

[0146] In some embodiments, x i (t) Perform empirical mode decomposition (EMD), x i (t) The method of performing empirical mode decomposition can be:

[0147]

[0148] Where n is the number of IMFs decomposed by EMD, c i,n (t) is the IMF component (IMFs), r i,n (t) is the residual component.

[0149] Repeat M rounds of EMD cycles, adding white noise of different amplitudes in each cycle, and a series of IMFs can be obtained.

[0150] Step 1508: taking the mean value of the plurality of candidate intrinsic modal component matrices as the intrinsic modal component matrix corresponding to the third echo signal matrix.

[0151] In some embodiments, the average value of the IMF components in each cycle is calculated and the average value is used as the target IMF component. That is, the average value of the IMFs in each cycle can be used as the IMF component c of the EEMD.n (t), in this application, c n (t) is denoted as the target IMF component. Specifically, the target IMF component c is determined n (t) can be calculated as:

[0152]

[0153] Among them, c i,n (t) is the IMF component in the i-th cycle, that is, the IMF components in each cycle are: [{c 1,n (t)},{c 2,n (t)},...,{c M,n (t)}].

[0154] Wherein, n=1,2,...,N; i=1,2,...,M. It should be noted that the number of execution rounds M of the loop process is a key parameter of the EEMD algorithm. M can be set to 50 times, but is not limited thereto.

[0155] In some embodiments, to accurately determine the intrinsic modal component matrix, Gaussian white noise may be added at 0.2 times the standard deviation of x(t).

[0156] Step 1509: reconstruct the ultra-wideband UWB life signal according to the intrinsic mode component matrix.

[0157] In other embodiments, the human breathing frequency may be taken as an example. For example, the distribution range of the breathing frequency is 0.2 to 0.8 Hz. Thus, the breathing signal is reconstructed according to the intrinsic modal component matrix within the breathing frequency range, such as Fig.16 shown.

[0158] In some embodiments, the human heartbeat frequency can be taken as an example. For example, the distribution range of the heartbeat frequency is 1 to 2.5 Hz, so the heartbeat signal is reconstructed according to the inherent modal component matrix within the heartbeat frequency range, such as Fig.17 shown.

[0159] The present application proposes a processing method for an ultra-wideband UWB life signal, which collects multiple echo signals corresponding to the ultra-wideband UWB life signal to obtain a first echo signal matrix composed of multiple echo signals, then obtains a second echo signal matrix after the first echo signal matrix is ​​subjected to clutter preprocessing, performs singular value decomposition to obtain multiple singular values ​​corresponding to the second echo signal matrix, performs important item screening on the sum of the multiple singular values ​​to obtain multiple main singular values, generates a third echo signal matrix corresponding to the multiple main singular values, obtains multiple white noise signals of different frequencies, and performs noise preprocessing on the multiple echo signal matrices in the third echo signal matrix. A plurality of white noise signals of different frequencies are added to the third echo signal matrix to obtain a plurality of fourth echo signal matrices containing white noise signals of different frequencies, signal decomposition is performed on the plurality of fourth echo signal matrices to obtain a plurality of candidate intrinsic modal component matrices, the mean of the plurality of candidate intrinsic modal component matrices is used as the intrinsic modal component matrix corresponding to the third echo signal matrix, and the target ultra-wideband UWB life signal is reconstructed according to the intrinsic modal component matrix. Thus, based on the intrinsic modal component matrix corresponding to the ultra-wideband UWB life signal, the target ultra-wideband UWB life signal is accurately reconstructed, and the processing accuracy of the ultra-wideband UWB life signal is improved.

[0160] Fig.18 It is a structural schematic diagram of an ultra-wideband UWB life signal processing device provided in an embodiment of the present application.

[0161] like Fig.18 As shown, the ultra-wideband UWB life signal processing device 1800 includes: an acquisition module 1801, a pre-processing module 1802, a first decomposition module 1803, a generation module 1804, a second decomposition module 1805 and a reconstruction module 1806, wherein:

[0162] The acquisition module 1801 is used to acquire multiple echo signals corresponding to the ultra-wideband UWB life signal to obtain a first echo signal matrix composed of the multiple echo signals.

[0163] The preprocessing module 1802 is used to perform clutter preprocessing on multiple echo signals in the first echo signal matrix to obtain a second echo signal matrix without clutter.

[0164] The first decomposition module 1803 is used to perform singular value decomposition processing on the second echo signal matrix to obtain multiple singular values ​​corresponding to the second echo signal matrix.

[0165] The generating module 1804 is used to screen the important items of the sum of the multiple singular values ​​to obtain multiple main singular values, and generate a third echo signal matrix corresponding to the multiple main singular values.

[0166] The second decomposition module 1805 is used to perform signal decomposition on multiple echo signals in the third echo signal matrix to obtain an intrinsic mode component matrix corresponding to the third echo signal matrix.

[0167] The reconstruction module 1806 is used to reconstruct the ultra-wideband UWB life signal according to the intrinsic mode component matrix.

[0168] The present application proposes a processing device for an ultra-wideband UWB life signal, which collects multiple echo signals corresponding to an ultra-wideband UWB life signal to obtain a first echo signal matrix composed of multiple echo signals, then obtains a second echo signal matrix after the first echo signal matrix is ​​subjected to clutter preprocessing, and performs singular value decomposition to obtain multiple singular values ​​corresponding to the second echo signal matrix, performs important item screening on the sum of the multiple singular values ​​to obtain multiple main singular values, and generates a third echo signal matrix corresponding to the multiple main singular values, and then performs signal decomposition to obtain an intrinsic mode component matrix corresponding to the third echo signal matrix, and reconstructs a target ultra-wideband UWB life signal according to the intrinsic mode component matrix. Thus, based on the decomposition and reconstruction processing of the ultra-wideband UWB life signal, the target ultra-wideband UWB life signal is accurately determined, and the processing accuracy of the ultra-wideband UWB life signal is improved.

[0169] In one embodiment of the present application, Fig.19 FIG. 1 is a schematic diagram of the structure of another ultra-wideband UWB life signal processing device provided in an embodiment of the present application. Fig.19 As shown, the ultra-wideband UWB life signal processing device 1900 may also include: an acquisition module 1901, a preprocessing module 1902, a first decomposition module 1903, a generation module 1904, a second decomposition module 1905 and a reconstruction module 1906, wherein the device also includes an enhancement module 1907.

[0170] For detailed descriptions of the acquisition module 1901, the preprocessing module 1902, the first decomposition module 1903, the generation module 1904, the second decomposition module 1905 and the reconstruction module 1906, please refer to Fig.18 The description of the acquisition module 1801, the preprocessing module 1802, the first decomposition module 1803, the generation module 1804, the second decomposition module 1805 and the reconstruction module 1806 in the illustrated embodiment will not be described here.

[0171] In one embodiment of the present application, the preprocessing module 1902 is specifically used to:

[0172] A first clutter matrix is ​​obtained by preprocessing the first frequency clutter of multiple echo signals in the first echo signal matrix using a channel signal subtraction method.

[0173] A time-subtraction averaging algorithm is used to pre-process the second frequency clutter on a plurality of echo signals in the first echo signal matrix to obtain a second clutter matrix.

[0174] The difference between the first echo signal matrix and the second clutter matrix is ​​obtained by subtracting the first clutter matrix from the first echo signal matrix to obtain the second echo signal matrix.

[0175] In one embodiment of the present application, the generating module 1904 is specifically used to:

[0176] Get the gradient differences between adjacent singular values ​​in multiple singular values.

[0177] Adjacent singular values ​​whose gradient difference is greater than a preset gradient threshold are taken as candidate singular values.

[0178] Get the relative numerical values ​​of each candidate singular value.

[0179] The candidate singular value whose relative value is smaller than the preset value is taken as the main singular value.

[0180] According to the mapping relationship between the main singular value and the singular value matrix component, the main singular matrix component corresponding to the main singular value is determined.

[0181] The principal singular values ​​and the principal singular matrix components are combined into a third echo signal matrix.

[0182] In one embodiment of the present application, the second decomposition module 1905 is specifically used to:

[0183] Get multiple white noise signals of different frequencies.

[0184] A plurality of white noise signals of different frequencies are added to the plurality of echo signals in the third echo signal matrix to obtain a plurality of fourth echo signal matrices containing white noise signals of different frequencies.

[0185] Signal decomposition is performed on the plurality of fourth echo signal matrices to obtain a plurality of candidate intrinsic modal component matrices.

[0186] The mean value of the plurality of candidate intrinsic modal component matrices is used as the intrinsic modal component matrix corresponding to the third echo signal matrix.

[0187] In one embodiment of the present application, the generating module 1904 is further specifically configured to:

[0188] The spatial eigenvector and the temporal eigenvector corresponding to each principal singular value in the principal singular matrix component are obtained.

[0189] Each principal singular value, the spatial eigenvector, and the temporal eigenvector are taken as a set of storage data and stored in a container.

[0190] In one embodiment of the present application, the device further includes:

[0191] The enhancement module 1907 is used to perform signal enhancement on multiple echo signals in the second echo signal matrix.

[0192] The present application proposes a processing device for an ultra-wideband UWB life signal, which collects multiple echo signals corresponding to an ultra-wideband UWB life signal to obtain a first echo signal matrix composed of multiple echo signals, then obtains a second echo signal matrix after the first echo signal matrix is ​​subjected to clutter preprocessing, and performs singular value decomposition to obtain multiple singular values ​​corresponding to the second echo signal matrix, performs important item screening on the sum of the multiple singular values ​​to obtain multiple main singular values, and generates a third echo signal matrix corresponding to the multiple main singular values, and then performs signal decomposition to obtain an intrinsic mode component matrix corresponding to the third echo signal matrix, and reconstructs a target ultra-wideband UWB life signal according to the intrinsic mode component matrix. Thus, based on the decomposition and reconstruction processing of the ultra-wideband UWB life signal, the target ultra-wideband UWB life signal is accurately determined, and the processing accuracy of the ultra-wideband UWB life signal is improved.

[0193] like Fig. 20 , which is a block diagram of an electronic device according to an embodiment of the present application.

[0194] like Fig. 20 As shown, the electronic device includes:

[0195] Memory 2001 , processor 2002 , and computer instructions stored in the memory 2001 and executable on the processor 2002 .

[0196] When the processor 2002 executes the instruction, the method for processing the ultra-wideband UWB life signal provided in the above embodiment is implemented.

[0197] Furthermore, the electronic device further comprises:

[0198] The communication interface 2003 is used for communication between the memory 2001 and the processor 2002 .

[0199] The memory 2001 is used to store computer instructions that can be executed on the processor 2002 .

[0200] The memory 2001 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0201] The processor 2002 is configured to implement the method for processing the ultra-wideband UWB life signal of the above embodiment when executing a program.

[0202] If the memory 2001, the processor 2002 and the communication interface 2003 are implemented independently, the communication interface 2003, the memory 2001 and the processor 2002 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Fig. 20 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0203] Optionally, in a specific implementation, if the memory 2001, the processor 2002 and the communication interface 2003 are integrated on a chip, the memory 2001, the processor 2002 and the communication interface 2003 can communicate with each other through an internal interface.

[0204] The processor 2002 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0205] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0206] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0207] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for processing ultra-wideband (UWB) life signals, characterized in that: in, The method comprises: Collecting a plurality of echo signals corresponding to the ultra-wideband UWB life signal to obtain a first echo signal matrix composed of the plurality of echo signals; Performing clutter preprocessing on the multiple echo signals in the first echo signal matrix to obtain a second echo signal matrix without clutter; performing singular value decomposition processing on the second echo signal matrix to obtain a plurality of singular values ​​corresponding to the second echo signal matrix; Screening the plurality of singular values ​​for important items to obtain a plurality of main singular values, and generating a third echo signal matrix corresponding to the plurality of main singular values; Performing signal decomposition on a plurality of echo signals in the third echo signal matrix to obtain an intrinsic mode component matrix corresponding to the third echo signal matrix; Reconstructing a target ultra-wideband UWB life signal according to the intrinsic modal component matrix; The important item screening of the plurality of singular values ​​to obtain a plurality of main singular values, and generating a third echo signal matrix corresponding to the plurality of main singular values ​​includes: Obtaining gradient differences between adjacent singular values ​​among the plurality of singular values; The adjacent singular values ​​whose gradient difference is greater than a preset gradient threshold are taken as candidate singular values; Obtaining relative numerical values ​​of each of the candidate singular values; The candidate singular value whose relative value is smaller than the preset value is used as the main singular value; According to the mapping relationship between the main singular value and the singular value matrix component, determining the main singular matrix component corresponding to the main singular value; The principal singular values ​​and principal singular matrix components are combined into the third echo signal matrix.

2. The method according to claim 1, characterized in that The performing clutter elimination preprocessing on the multiple echo signals in the first echo signal matrix to obtain a second echo signal matrix without clutter includes: Preprocessing the first frequency clutter of the plurality of echo signals in the first echo signal matrix by using a channel signal subtraction method to obtain a first clutter matrix; Using a time-subtracted average algorithm to pre-process the plurality of echo signals in the first echo signal matrix for second frequency clutter, so as to obtain a second clutter matrix; The difference between the first clutter matrix and the second clutter matrix subtracted from the first echo signal matrix is ​​used as a second echo signal matrix.

3. The method according to claim 1, characterized in that The performing signal decomposition on the multiple echo signals in the third echo signal matrix to obtain an intrinsic modal component matrix corresponding to the third echo signal matrix includes: Obtain multiple white noise signals of different frequencies; adding the plurality of white noise signals of different frequencies to the plurality of echo signals in the third echo signal matrix to obtain a plurality of fourth echo signal matrices containing white noise signals of different frequencies; Performing signal decomposition on the plurality of fourth echo signal matrices to obtain a plurality of candidate intrinsic modal component matrices; The mean value of the plurality of candidate intrinsic modal component matrices is used as the intrinsic modal component matrix corresponding to the third echo signal matrix.

4. The method according to claim 1, characterized in that: After combining the main singular values ​​and the main singular matrix components into the third echo signal matrix, the method further comprises: Obtaining the spatial eigenvectors and the temporal eigenvectors corresponding to the respective principal singular values ​​in the principal singular matrix components; Each of the main singular values, the spatial eigenvector and the temporal eigenvector is taken as a group of storage data and stored in a container.

5. The method according to claim 1, characterized in that After performing clutter preprocessing on the plurality of echo signals in the first echo signal matrix to obtain a second echo signal matrix without clutter, the method further includes: Signal enhancement is performed on the multiple echo signals in the second echo signal matrix.

6. An ultra-wideband (UWB) life signal processing device, characterized in that: in, The device comprises: An acquisition module, used for acquiring a plurality of echo signals corresponding to the ultra-wideband UWB life signal, so as to obtain a first echo signal matrix composed of the plurality of echo signals; A preprocessing module, used for performing clutter preprocessing on the plurality of echo signals in the first echo signal matrix to obtain a second echo signal matrix without clutter; A first decomposition module, used for performing singular value decomposition processing on the second echo signal matrix to obtain a plurality of singular values ​​corresponding to the second echo signal matrix; A generating module, configured to screen the plurality of singular values ​​for important items to obtain a plurality of main singular values, and generate a third echo signal matrix corresponding to the plurality of main singular values; A second decomposition module, used for performing signal decomposition on a plurality of echo signals in the third echo signal matrix to obtain an intrinsic mode component matrix corresponding to the third echo signal matrix; A reconstruction module, used for reconstructing a target ultra-wideband UWB life signal according to the intrinsic modal component matrix; The generating module is specifically used for: Obtaining gradient differences between adjacent singular values ​​among the plurality of singular values; The adjacent singular values ​​whose gradient difference is greater than a preset gradient threshold are taken as candidate singular values; Obtaining relative numerical values ​​of each of the candidate singular values; The candidate singular value whose relative value is smaller than the preset value is used as the main singular value; According to the mapping relationship between the main singular value and the singular value matrix component, determining the main singular matrix component corresponding to the main singular value; The principal singular values ​​and principal singular matrix components are combined into the third echo signal matrix.

7. The device according to claim 6, characterized in that The preprocessing module is specifically used for: Preprocessing the first frequency clutter of the plurality of echo signals in the first echo signal matrix by using a channel signal subtraction method to obtain a first clutter matrix; Using a time-subtracted average algorithm to pre-process the plurality of echo signals in the first echo signal matrix for second frequency clutter, so as to obtain a second clutter matrix; The difference between the first clutter matrix and the second clutter matrix subtracted from the first echo signal matrix is ​​used as a second echo signal matrix.

8. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for processing an ultra-wideband UWB life signal as claimed in any one of claims 1 to 5 is implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for processing an ultra-wideband (UWB) life signal as claimed in any one of claims 1 to 5 is implemented.

Images