Methods, devices, storage media and computer equipment for detecting concealed electrical facilities

Abstract

The method, apparatus, storage medium, and computer equipment for detecting concealed power facilities provided in this application include: decomposing a radar signal to obtain a clutter matrix and a target matrix; further decomposing the clutter matrix into a first matrix and a second matrix; and constructing a target optimization function using the first matrix, the second matrix, and the target matrix. This reduces the complexity of solving the optimization function and decreases the dependence of the target optimization function on regularization parameters, thereby reducing the sensitivity of the target optimization function to regularization parameters and improving the accuracy of subsequent solutions. Then, the target matrix that enables the target optimization function to achieve its optimization objective is determined. The target radar signal is then determined based on this target matrix. Finally, back-projection imaging is performed based on the target radar signal. The clutter-suppressed target radar signal is used to achieve imaging detection of concealed power facilities, improving imaging quality and thus increasing the accuracy of concealed power facility detection.

Description

Technical Field

[0001] This application relates to the field of power detection technology, and in particular to a method, device, storage medium and computer equipment for detecting concealed power facilities. Background Technology

[0002] Concealed power facilities are vital power transmission channels, and accurately detecting their distribution and operational status is crucial for power system operation. Traditional methods for detecting concealed power facilities, including excavation, acoustic methods, and electromagnetic induction methods, have many limitations. Ground penetrating radar (GPR), on the other hand, is an emerging non-destructive testing technology with promising prospects due to its advantages such as fast detection speed, accurate positioning, and high imaging resolution, and it has wide applications in the field of concealed power facility detection.

[0003] The detection scenario for concealed power line targets is complex. Besides fine sand and covers, the area around cables often contains gravel, municipal pipelines, drainage pipes, and other conduits. Ground-penetrating radar (GPR) echo signals contain significant clutter interference, making direct detection and identification of concealed power line targets difficult. Currently, mean filtering can remove strong waves such as direct waves and coupled waves; however, it is less effective at suppressing clutter generated by other objects in the detection environment, thus affecting the radar scanning imaging effect and resulting in lower accuracy in detecting concealed power line facilities. Summary of the Invention

[0004] The purpose of this application is to at least solve one of the aforementioned technical defects, particularly the poor suppression effect of existing technologies on clutter generated by other impurities in the detection scene, which affects the imaging effect of radar scanning and leads to low accuracy in the detection of concealed power facilities.

[0005] Firstly, this application provides a method for detecting concealed electrical facilities, the method comprising:

[0006] The radar signal is acquired and decomposed to obtain the clutter matrix and the target matrix;

[0007] The clutter matrix is ​​decomposed into a first matrix and a second matrix, and a target optimization function is constructed based on the first matrix, the second matrix, and the target matrix; wherein, the target optimization function aims to constrain the sparsity of the target matrix as much as possible and extract the effective signal components in the clutter matrix.

[0008] Solve the objective optimization function to determine the target matrix that enables the objective optimization function to achieve the optimization objective;

[0009] The target radar signal is reconstructed based on the target matrix that makes the target optimization function reach the optimization target.

[0010] Back projection imaging is performed based on the target radar signal to detect concealed power facilities.

[0011] In one embodiment, the objective optimization function is expressed as:

[0012]

[0013] In the formula, For the first matrix, For the second matrix, This represents the product of the first and second matrices, i.e., the clutter matrix. For the target matrix, For the noise matrix, Indicates radar signal, and For regularization parameters, This represents summing the absolute values ​​of the 2-norms of the column vectors of the first matrix. This represents summing the absolute values ​​of the 2-norms of the column vectors of the transpose of the second matrix. This represents the sum of the absolute values ​​of all elements in the transpose of the target matrix.

[0014] In one embodiment, the step of decomposing the clutter matrix into a first matrix and a second matrix includes:

[0015] The clutter matrix is ​​grouped using factor group sparsity regularization to determine a first matrix and a second matrix, wherein the product of the first matrix and the second matrix is ​​the clutter matrix.

[0016] In one embodiment, the step of performing back projection imaging based on the target radar signal includes:

[0017] For each imaging point in the target radar signal, determine the scattering response of multiple apertures corresponding to that imaging point;

[0018] The effective echo sequence for each aperture is determined based on the scattering response of each aperture.

[0019] Based on the effective echo sequence of each aperture, the correlation coefficient of each aperture is determined, and the scattering response of each aperture is weighted based on the correlation coefficient of each aperture to enhance the reflection energy of the target region in the target radar signal.

[0020] Cross-correlation processing is performed on the weighted scattering responses of each aperture to reduce the reflection energy of non-target regions in the target radar signal and determine the reflection intensity of the imaging point.

[0021] When the reflection intensity of each imaging point in the target radar signal is determined, a radar image is generated based on the reflection intensity of each imaging point.

[0022] In one embodiment, the step of cross-correlation processing of the weighted scattering responses of each aperture includes:

[0023] Determine the pairwise correlations between the weighted scattering responses of each aperture, and sum the pairwise correlations between the weighted scattering responses of each aperture to obtain the initial reflection intensity of the imaging point.

[0024] The coherence factor of the imaging point is determined based on the pairwise correlation between the weighted scattering responses of each aperture.

[0025] The initial reflection intensity is weighted using the coherence factor to determine the reflection intensity of the imaging point.

[0026] In one embodiment, the step of determining the correlation coefficient of each aperture based on the effective echo sequence of each aperture includes:

[0027] The effective echo sequence of the middle aperture among all apertures is determined as the reference sequence;

[0028] Calculate the correlation coefficient between the effective echo sequence and the reference sequence for each aperture, and use the correlation coefficient between the effective echo sequence and the reference sequence for each aperture as the correlation coefficient for that aperture.

[0029] In one embodiment, the step of determining the scattering response of the plurality of apertures corresponding to the imaging point includes:

[0030] Based on the coordinates of the imaging point and the coordinates of each aperture, calculate the time delay vector for each aperture.

[0031] Based on the time delay vector of each aperture, determine the A-type scan signal received by each aperture;

[0032] Based on the A-type scan signals received from each aperture, the scattering response corresponding to each aperture is generated.

[0033] Secondly, this application provides a device for detecting concealed electrical facilities, the device comprising:

[0034] The signal acquisition module is used to acquire radar signals and decompose the radar signals to obtain clutter matrix and target matrix;

[0035] A matrix decomposition module is used to decompose the clutter matrix into a first matrix and a second matrix, and to construct a target optimization function based on the first matrix, the second matrix, and the target matrix; wherein the target optimization function aims to constrain the sparsity of the target matrix as much as possible and extract the effective signal components in the clutter matrix.

[0036] The function solving module is used to solve the objective optimization function to determine the target matrix that makes the objective optimization function achieve the optimization objective;

[0037] The signal reconstruction module is used to reconstruct the signal based on the target matrix determined when the target optimization function reaches the optimization target, so as to obtain the target radar signal;

[0038] An imaging detection module is used to perform rear projection imaging based on the target radar signal to perform imaging detection of concealed power facilities.

[0039] Thirdly, this application provides a storage medium storing computer-readable instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of the electrical concealed facility detection method as described in any of the above embodiments.

[0040] Fourthly, this application provides a computer device, including: one or more processors, and a memory;

[0041] The memory stores computer-readable instructions, and when the one or more processors execute the computer-readable instructions, they perform the steps of the electrical concealed facility detection method as described in any of the above embodiments.

[0042] As can be seen from the above technical solutions, the embodiments of this application have the following advantages:

[0043] The present application provides a method, apparatus, storage medium, and computer equipment for detecting concealed power facilities. The method includes: decomposing a radar signal to obtain a clutter matrix and a target matrix; then decomposing the clutter matrix into a first matrix and a second matrix; and constructing a target optimization function using the first matrix, the second matrix, and the target matrix. This reduces the complexity of solving the optimization function and also reduces the dependence of the target optimization function on regularization parameters, thereby reducing the sensitivity of the target optimization function to regularization parameters and improving the accuracy of subsequent solutions. Next, the target matrix that enables the target optimization function to achieve its optimization objective is determined. Then, the target radar signal is determined based on the target matrix. Finally, back-projection imaging is performed based on the target radar signal. The clutter-suppressed target radar signal is used to achieve imaging detection of concealed power facilities, improving imaging quality and thus increasing the accuracy of concealed power facility detection. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 A flowchart illustrating a method for detecting concealed electrical facilities provided in this application embodiment;

[0046] Figure 2 A flowchart illustrating the steps of back projection imaging based on target radar signals provided in an embodiment of this application;

[0047] Figure 3 A flowchart illustrating the steps of cross-correlation processing of the weighted scattering responses of each aperture, as provided in an embodiment of this application;

[0048] Figure 4 A comparison diagram of power concealment facility detection based on measured cable signals provided in this application embodiment;

[0049] Figure 5 A comparison diagram of power concealment facility detection based on cable simulation signals provided in the embodiments of this application;

[0050] Figure 6 This is a schematic diagram of the structure of a power concealment facility detection device provided in an embodiment of this application;

[0051] Figure 7 This is an internal structural diagram of a computer device provided in an embodiment of this application. Detailed Implementation

[0052] 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 some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0053] In one embodiment, this application provides a method for detecting concealed power facilities. The following embodiments illustrate the application of this method to a server. It is understood that the method for detecting concealed power facilities can be performed by a single server or by a server cluster consisting of multiple servers, and this application does not impose any specific limitations on this.

[0054] like Figure 1 As shown, this application provides a method for detecting concealed electrical facilities, the method comprising:

[0055] S101: Acquire radar signals and decompose them to obtain clutter matrix and target matrix.

[0056] In this context, radar signal refers to the signal scanned within the area of ​​concealed power facilities. In this embodiment, the radar signal is a B-scan signal, which can be obtained through non-destructive scanning using ground-penetrating radar. Clutter matrix refers to the clutter signal components in the radar signal, and target matrix refers to the main signal components in the radar signal.

[0057] In this step, when it is necessary to detect concealed power facilities, a radar scanning tool is used to scan and detect them to collect radar signals. Then, the radar signals are decomposed using the principal component analysis method to obtain the clutter matrix and the target matrix.

[0058] In one example, Robust Principal Component Analysis (RPCA) can be used to decompose radar signals. Compared to other principal component analysis methods, Robust Principal Component Analysis is more robust to noise and outliers in the data.

[0059] S102: Decompose the clutter matrix into a first matrix and a second matrix, and construct the objective optimization function based on the first matrix, the second matrix, and the objective matrix.

[0060] The objective optimization function aims to constrain the sparsity of the objective matrix as much as possible and extract the effective signal components from the clutter matrix.

[0061] In this step, the clutter matrix is ​​decomposed into the product of a first matrix and a second matrix to determine the first and second matrices obtained from the decomposition. Then, the objective optimization function is constructed based on the first matrix, the second matrix, and the objective matrix. Replacing the clutter matrix with the first and second matrices to construct the objective optimization function reduces the complexity of solving the objective optimization function and decreases the dependence on the regularization parameter through decomposition. This reduces the sensitivity of the objective optimization function to the regularization parameter, thereby improving the accuracy of the subsequent solution to the objective optimization function. Specifically, the regularization parameter is used to control the weights of the sparse terms to balance low-rank and sparse components.

[0062] S103: Solve the objective optimization function to determine the objective matrix that makes the objective optimization function achieve the optimization objective.

[0063] In this step, algorithms such as the alternating direction multiplier method, the singular value thresholding method, or the incremental algorithm can be used to solve the objective optimization function, in order to find the objective matrix, the first matrix, and the second matrix that enable the objective optimization function to achieve its optimization objective. When the objective optimization function achieves its optimization objective, the objective matrix in the objective optimization function at this point is obtained.

[0064] S104: Reconstruct the target signal based on the target matrix that makes the target optimization function reach the optimization target, so as to obtain the target radar signal.

[0065] In this step, after obtaining the target matrix when the target optimization function achieves its optimization objective, signal reconstruction is performed based on the target matrix to obtain the target radar signal.

[0066] Furthermore, the process of signal reconstruction based on the target matrix includes: signal recovery based on the target matrix, and filtering the recovered target matrix to obtain the target radar signal.

[0067] S105: Performs rear projection imaging based on target radar signals to image and detect concealed power facilities.

[0068] Among them, concealed electrical facilities refer to electrical equipment and systems buried inside buildings or underground, including but not limited to cable trenches, cable ducts, grounding systems, transformers, distribution boxes, switch cabinets, etc.

[0069] In this step, a target radar signal is generated based on the target matrix obtained after clutter suppression, and then back projection imaging is performed based on the target radar signal, which can improve the final imaging effect and accurately reconstruct the distribution of power concealment facilities to complete the imaging detection of power concealment facilities.

[0070] Specifically, back projection imaging refers to reconstructing a high-resolution image from multiple echo signals using back projection technology.

[0071] The present application provides a method, apparatus, storage medium, and computer equipment for detecting concealed power facilities. The method includes: decomposing a radar signal to obtain a clutter matrix and a target matrix; then decomposing the clutter matrix into a first matrix and a second matrix; and constructing a target optimization function using the first matrix, the second matrix, and the target matrix. This reduces the complexity of solving the optimization function and also reduces the dependence of the target optimization function on regularization parameters, thereby reducing the sensitivity of the target optimization function to regularization parameters and improving the accuracy of subsequent solutions. Next, the target matrix that enables the target optimization function to achieve its optimization objective is determined. Then, the target radar signal is determined based on the target matrix. Finally, back-projection imaging is performed based on the target radar signal. The clutter-suppressed target radar signal is used to achieve imaging detection of concealed power facilities, improving imaging quality and thus increasing the accuracy of concealed power facility detection.

[0072] In one embodiment, the objective optimization function is expressed as:

[0073]

[0074] In the formula, For the first matrix, For the second matrix, This represents the product of the first and second matrices, i.e., the clutter matrix. For the target matrix, For the noise matrix, Indicates radar signal, and For regularization parameters, This represents summing the absolute values ​​of the 2-norms of the column vectors of the first matrix. This represents summing the absolute values ​​of the 2-norms of the column vectors of the transpose of the second matrix. This represents the sum of the absolute values ​​of all elements in the transpose of the target matrix.

[0075] The noise matrix is ​​used to simulate noise interference in radar signals.

[0076] Specifically, if the clutter matrix is ​​not decomposed into a first matrix and a second matrix, the optimization function is expressed as:

[0077]

[0078]

[0079] In the formula, Represents the clutter matrix. Represents the target matrix. Represents the noise matrix. The rank of the clutter matrix is ​​represented by... Denotes the 0 norm of the target matrix. This is a regularization parameter used to balance sparsity and low rank.

[0080] The optimization function described above has high complexity and is sensitive to regularization parameters. Therefore, in this embodiment, the clutter matrix is ​​decomposed into a first matrix and a second matrix. Then, the rank function of the original clutter matrix is ​​replaced by the Schatten p norm to reduce complexity, speed up convergence, and further constrain the sparsity of the target matrix, thereby achieving a better clutter suppression effect.

[0081] In one example The calculation expression is:

[0082]

[0083]

[0084] In the formula, Represents the first matrix The column vectors in express The 2-norm, express Index of an element in the middle, Represents column vectors The first in Each element.

[0085] Similarly, The calculation method can also be based on the above. The calculation expression can be deduced by analogy.

[0086] In one embodiment, the step of decomposing the clutter matrix into a first matrix and a second matrix includes:

[0087] By using factor group sparsity regularization, the clutter matrix is ​​grouped to determine the first matrix and the second matrix, where the product of the first matrix and the second matrix is ​​the clutter matrix.

[0088] Factor Group Sparsity Regularization (FGSR) is a regularization strategy used when dealing with data that has multiple sets of features. This regularization strategy aims to induce sparsity in the model by penalizing certain sets of parameters in the model or function on those sets.

[0089] In this embodiment, the clutter matrix is ​​divided into two groups using the principle of factor group sparsity regularization, resulting in a first matrix and a second matrix.

[0090] In one example, assume the clutter matrix has dimensions of . When the clutter matrix Decomposed into the first matrix Second matrix When the product is, that is The first matrix The dimension is The first matrix can be represented as:

[0091]

[0092] In the formula, Indicates length is Column vectors.

[0093] Second matrix The dimension is The second matrix can be represented as:

[0094]

[0095] In the formula, Indicates length is Column vectors.

[0096] It is understandable that by decomposing the clutter matrix into a first matrix and a second matrix, the complexity of solving the optimization function can be reduced, and the dependence of the objective optimization function on the regularization parameter can be reduced, thereby reducing the sensitivity of the objective optimization function to the regularization parameter, improving the accuracy of the subsequent solution, and thus improving the imaging quality.

[0097] like Figure 2 As shown, in one embodiment, the step of performing back projection imaging based on the target radar signal includes:

[0098] S201: For each imaging point in the target radar signal, determine the scattering response of multiple apertures corresponding to that imaging point.

[0099] Scattering response refers to the scattering characteristics of the imaging point to the radar signal of the corresponding aperture, including but not limited to the intensity, direction, phase, etc. of the scattering.

[0100] In this step, for each imaging point in the target radar signal, the scattering response of the image at each aperture is calculated by determining the time delay of the imaging point at each aperture.

[0101] S202: Determine the effective echo sequence for each aperture based on the scattering response of each aperture.

[0102] The effective echo sequence refers to the main energy concentration part of the scattering response.

[0103] In this step, a segment of effective signal can be taken above and below the scattering response corresponding to the aperture at the time delay location as the center, and used as the effective echo sequence for that aperture. The length of the truncated signal (i.e., the length of the effective echo sequence) can be a preset value or calculated based on the sampling frequency, the transmission signal frequency, etc., and this application does not impose specific restrictions on it.

[0104] Specifically, the time delay position refers to one of the moments within the time period during which the electromagnetic wave from the aperture travels from the aperture to the imaging point and then reflects back to the aperture.

[0105] In one example, the length of the valid echo sequence can be determined using the following expression:

[0106]

[0107] In the formula, Indicates the sampling frequency. Indicates the frequency of the transmitted signal. This indicates rounding down to the nearest integer.

[0108] S203: Based on the effective echo sequence of each aperture, determine the correlation coefficient of each aperture, and weight the scattering response based on the correlation coefficient of each aperture to enhance the reflection energy of the target region in the target radar signal.

[0109] The correlation coefficient is an indicator used to measure the degree of linear correlation between two variables. The target area refers to the region in the target radar signal that primarily represents concealed power facilities.

[0110] In this step, a reference sequence is determined from the effective echo sequences of each aperture. Then, the correlation coefficient between the effective echo sequence of each aperture and the reference sequence is calculated, and this correlation coefficient is defined as the correlation coefficient for that aperture. Next, the scattering response of each aperture is weighted based on its correlation coefficient to obtain the time delay response. It is understandable that by using the correlation coefficient to weight the scattering response, sequences with higher correlation to the reference sequence can be assigned higher weights, while those with lower correlation can be assigned lower weights. When the reference sequence itself has high energy, the weights can be primarily allocated to high-energy sequences, thereby reducing sidelobes and interference energy and enhancing the reflected energy of the target region.

[0111] S204: Perform cross-correlation processing on the weighted scattering responses of each aperture to reduce the reflection energy of non-target areas in the target radar signal and determine the reflection intensity of the imaging point.

[0112] The non-target area refers to the area in the target radar signal that mainly represents non-electric concealed facilities.

[0113] In this step, the cross-correlation back-projection (CBP) algorithm can be used to cross-correlate the weighted scattering responses of each aperture. Since this algorithm introduces invalid sidelobe interference, the coherence factor can be calculated and weighted with the processing result of the cross-correlation back-projection algorithm to suppress artifacts and interference.

[0114] S205: When the reflection intensity of each imaging point in the target radar signal is determined, a radar image is generated based on the reflection intensity of each imaging point.

[0115] Understandably, by enhancing the reflected energy of the target area and weakening the reflected energy of the non-target area through a series of processes, the quality of the imaging is improved, making the detection of concealed power facilities more accurate.

[0116] like Figure 3 As shown, in one embodiment, the step of cross-correlation processing of the weighted scattering responses of each aperture includes:

[0117] S301: Determine the pairwise correlations in the weighted scattering responses of each aperture, and sum the pairwise correlations in the weighted scattering responses of each aperture to obtain the initial reflection intensity of the imaging point.

[0118] In one example, the S301 procedure can be implemented using the following expression:

[0119]

[0120] In the formula, Indicates the initial reflection intensity. Indicates the first The weighted scattering response of each aperture Indicates the first The weighted scattering response of each aperture Indicates the number of apertures, and An index representing the aperture.

[0121] S302: Determine the coherence factor of the imaging point based on the correlation between pairs of scattering responses of each aperture after weighting.

[0122] The coherence factor (CF) is a measure used to describe the degree of linear correlation between two signals or data sequences.

[0123] In one example, the procedure S302 can be implemented using the following expression:

[0124]

[0125] In the formula, Represents the coherence factor. Indicates the first The weighted scattering response of each aperture Indicates the first The weighted scattering response of each aperture Indicates the number of apertures, and An index representing the aperture.

[0126] S303: The initial reflection intensity is weighted using a coherence factor to determine the reflection intensity at the imaging point.

[0127] In one example, the S303 procedure can be implemented using the following expression:

[0128]

[0129] In the formula, Indicates the intensity of reflection. Indicates the first The weighted scattering response of each aperture Indicates the first The weighted scattering response of each aperture Indicates the number of apertures, and An index representing the aperture. This represents the initial reflection intensity.

[0130] Understandably, the coherence factor can calculate the correlation of each product term in the above formula, forming a CF-CBP cascaded correlation processing to reduce the reflected energy from non-target areas. This enables high-resolution imaging of concealed power facilities while also suppressing imaging artifacts.

[0131] In one embodiment, the step of determining the correlation coefficient for each aperture based on the effective echo sequence for each aperture includes:

[0132] S1: The effective echo sequence of the middle aperture among all apertures is determined as the reference sequence.

[0133] S2: Calculate the correlation coefficient between the effective echo sequence and the reference sequence for each aperture, and use the correlation coefficient between the effective echo sequence and the reference sequence for each aperture as the correlation coefficient for that aperture.

[0134] In this embodiment, since the signal strength of the effective echo sequence of the middle aperture is the largest among all effective echo sequences, the effective echo sequence of the middle aperture is used as the reference sequence so that a larger weight can be assigned to the effective echo sequence with higher energy, thereby enhancing the reflection energy of the target area in the target radar signal.

[0135] In one example, the correlation coefficient can be calculated using the expression for the Pearson correlation coefficient, as follows:

[0136]

[0137] In the formula, Represents the correlation coefficient. Indicates the valid echo sequence. Indicates the reference sequence.

[0138] In one embodiment, the step of determining the scattering response of multiple apertures corresponding to the imaging point includes:

[0139] S1: Calculate the time delay vector for each aperture based on the coordinates of the imaging point and the coordinates of each aperture.

[0140] S2: Determine the A-type scan signal received by each aperture based on the time delay vector of each aperture.

[0141] S3: Generate the scattering response corresponding to each aperture based on the A-type scanning signal received from each aperture.

[0142] The time delay vector refers to the time it takes for the electromagnetic wave from the aperture to travel to the imaging point and then back to the aperture. The A-scan signal is a single-channel waveform.

[0143] In this embodiment, the process of calculating the time delay vector of each aperture based on the coordinates of the imaging point and the coordinates of each aperture can be expressed as follows:

[0144]

[0145] In the formula, Indicates the first The time delay vector of each aperture, and These represent the x and y coordinates of the imaging point, respectively. and They represent the first The horizontal and vertical coordinates of each aperture. and These represent the relative permittivity and relative conductivity of the soil, respectively.

[0146] Next, based on the time delay vector of each aperture, the A-type scan signal received by each aperture is determined, which can be expressed as:

[0147]

[0148] In the formula, Indicates the first The time delay vector of each aperture, Indicates the first The A-type scan signal received by each aperture.

[0149] In one example, such as Figure 4 and Figure 5 As shown, Figure 4 and Figure 5 This paper demonstrates radar scanning signal processing for concealed power facilities, taking cables as an example. The signal processing flow proposed in this paper is verified using measured cable signals and cable simulation signals based on GprMax software. To verify the superiority of this application, the clutter suppression processing algorithm proposed in this application is compared with the traditional average cancellation method, and the imaging algorithm proposed in this application is compared with the traditional BP (Back-Projection) imaging algorithm and CBP imaging algorithm.

[0150] exist Figure 4 middle, Figure 4 (a) is the measured signal of the cable. Figure 4 (b) is a diagram showing the effect of using the average cancellation method to suppress clutter in the measured cable signal. Figure 4 (c) A diagram showing the effect of using the proposed power concealment facility detection method to suppress clutter in the measured cable signal. Figure 4 (d) shows the BP algorithm imaging results of the measured cable signal. Figure 4 (e) shows the CBP algorithm imaging results of the measured cable signal. Figure 4 (f) shows the improved BP algorithm imaging result of the measured cable signal. The improved BP algorithm imaging result described here is the imaging method used in the proposed method for detecting concealed power facilities in this application. It is understood that... Figure 4 (a) is the object being processed. Figure 4 (b) Figure 4 (d) and Figure 4 (e) is a diagram showing the processing effect of the existing technology. Figure 4 (c) and Figure 4 (f) is a diagram showing the improved processing effect of this application.

[0151] exist Figure 5 middle, Figure 5 (a) is a cable simulation scenario. Figure 5 (b) is the cable simulation signal. Figure 5(c) A diagram showing the effect of using the proposed power concealment facility detection method to suppress clutter in cable simulation signals. Figure 5 (d) shows the BP algorithm imaging results of the cable simulation signal. Figure 5 (e) shows the CBP algorithm imaging results of the cable simulation signal. Figure 5 (f) shows the improved BP algorithm imaging result of the cable simulation signal. The improved BP algorithm imaging result mentioned here is the imaging method used in the power concealed facility detection method proposed in this application. It is understood that... Figure 5 (b) is the object being processed. Figure 5 (d) and Figure 5 (e) is a diagram showing the processing effect of the existing technology. Figure 5 (c) and Figure 5 (f) is a diagram showing the improved processing effect of this application.

[0152] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0153] The following describes the electrical concealed facility detection device provided in the embodiments of this application. The electrical concealed facility detection device described below can be referred to in correspondence with the electrical concealed facility detection method described above.

[0154] like Figure 6 As shown, this application provides a power concealment facility detection device 400, the device comprising:

[0155] The signal acquisition module 401 is used to acquire radar signals and decompose the radar signals to obtain clutter matrix and target matrix;

[0156] The matrix decomposition module 402 is used to decompose the clutter matrix into a first matrix and a second matrix, and to construct a target optimization function based on the first matrix, the second matrix, and the target matrix; wherein, the target optimization function aims to constrain the sparsity of the target matrix as much as possible and extract the effective signal components in the clutter matrix.

[0157] The function solving module 403 is used to solve the objective optimization function in order to determine the objective matrix that makes the objective optimization function achieve the optimization objective.

[0158] The signal reconstruction module 404 is used to reconstruct the signal based on the target matrix that makes the target optimization function reach the optimization target, so as to obtain the target radar signal;

[0159] The imaging detection module 405 is used to perform rear projection imaging based on the target radar signal to perform imaging detection of concealed power facilities.

[0160] In one embodiment, the matrix factorization module includes: the objective optimization function is expressed as:

[0161]

[0162] In the formula, For the first matrix, For the second matrix, This represents the product of the first and second matrices, i.e., the clutter matrix. For the target matrix, For the noise matrix, Indicates radar signal, and For regularization parameters, This represents summing the absolute values ​​of the 2-norms of the column vectors of the first matrix. This represents summing the absolute values ​​of the 2-norms of the column vectors of the transpose of the second matrix. This represents the sum of the absolute values ​​of all elements in the transpose of the target matrix.

[0163] In one embodiment, the matrix factorization module includes:

[0164] The matrix grouping submodule is used to group the clutter matrix using factor group sparse regularization to determine the first matrix and the second matrix, where the product of the first matrix and the second matrix is ​​the clutter matrix.

[0165] In one embodiment, the imaging detection module includes:

[0166] The scattering determination submodule is used to determine the scattering response of multiple apertures corresponding to each imaging point in the target radar signal.

[0167] The sequence determination submodule is used to determine the effective echo sequence for each aperture based on the scattering response of each aperture.

[0168] The energy enhancement submodule is used to determine the correlation coefficient of each aperture based on the effective echo sequence of each aperture, and to weight the scattering response based on the correlation coefficient of each aperture in order to enhance the reflected energy of the target region in the target radar signal.

[0169] The energy attenuation submodule is used to perform cross-correlation processing on the weighted scattering response of each aperture to reduce the reflection energy of non-target areas in the target radar signal and determine the reflection intensity of the imaging point.

[0170] The image generation submodule is used to generate a radar image based on the reflection intensity of each imaging point when the reflection intensity of each imaging point in the target radar signal is determined.

[0171] In one embodiment, the energy attenuation submodule includes:

[0172] The intensity determination unit is used to determine the pairwise correlation between each aperture in the weighted scattering response and to sum the pairwise correlation between each aperture in the weighted scattering response to obtain the initial reflection intensity of the imaging point.

[0173] The factor determination unit is used to determine the coherence factor of the imaging point based on the pairwise correlation between the weighted scattering responses of each aperture.

[0174] The weighting unit is used to weight the initial reflection intensity using a coherence factor to determine the reflection intensity of the imaging point.

[0175] In one embodiment, the energy enhancement submodule includes:

[0176] The sequence determination unit is used to determine the effective echo sequence of the middle aperture among all apertures as the reference sequence;

[0177] The coefficient calculation unit is used to calculate the correlation coefficient between the effective echo sequence and the reference sequence for each aperture, and uses the correlation coefficient between the effective echo sequence and the reference sequence for each aperture as the correlation coefficient for that aperture.

[0178] In one embodiment, the scattering determination submodule includes:

[0179] The time delay calculation unit is used to calculate the time delay vector of each aperture based on the coordinates of the imaging point and the coordinates of each aperture.

[0180] A signal determination unit is used to determine the A-type scan signal received by each aperture based on the time delay vector of each aperture;

[0181] The scattering generation unit is used to generate the scattering response corresponding to each aperture based on the A-type scan signal received by each aperture.

[0182] The division of modules in the above-described electrical concealed facility detection device is merely illustrative. In other embodiments, the electrical concealed facility detection device can be divided into different modules as needed to complete all or part of its functions. Each module in the above-described electrical concealed facility detection device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0183] In one embodiment, this application also provides a storage medium storing computer-readable instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of the electrical concealment facility detection method as described in any of the above embodiments.

[0184] In one embodiment, this application also provides a computer device storing computer-readable instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of the electrical concealment facility detection method as described in any of the above embodiments.

[0185] Indicatively, such as Figure 7 As shown, Figure 7 This is a schematic diagram of the internal structure of a computer device 500 provided in an embodiment of this application. The computer device 500 can be provided as a server. (Refer to...) Figure 7 The computer device 500 includes a processing component 502, which further includes one or more processors, and memory resources represented by memory 501 for storing instructions, such as application programs, that can be executed by the processing component 502. The application programs stored in memory 501 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processing component 502 is configured to execute instructions to perform the electrical concealment facility detection method of any of the above embodiments.

[0186] The computer device 500 may also include a power supply component 503 configured to perform power management of the computer device 500, a wired or wireless network interface 504 configured to connect the computer device 500 to a network, and an input / output (I / O) interface 505. The computer device 500 may operate on an operating system stored in memory 501, such as Windows Server™, Mac OS X™, Unix™, Linux™, Free BSD™, or similar.

[0187] Those skilled in the art will understand that Figure 7 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0188] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising a…" does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element. In this document, the singular forms "a," "an," and "the" may also include the plural forms unless the context clearly indicates otherwise. It should also be understood that the terms “comprising / including” or “having” specify the presence of the stated features, wholes, steps, operations, components, parts or combinations thereof, but do not exclude the possibility of the presence or addition of one or more other features, wholes, steps, operations, components, parts or combinations thereof. Meanwhile, the term “and / or” as used in this specification includes any and all combinations of the associated listed items.

[0189] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can be referred to each other.

[0190] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for detecting concealed electrical facilities, characterized in that, The method includes: The radar signal is acquired and decomposed to obtain the clutter matrix and the target matrix; The clutter matrix is ​​decomposed into a first matrix and a second matrix, and a target optimization function is constructed based on the first matrix, the second matrix, and the target matrix; wherein, the target optimization function aims to constrain the sparsity of the target matrix as much as possible and extract the effective signal components in the clutter matrix. Solve the objective optimization function to determine the target matrix that enables the objective optimization function to achieve the optimization objective; The target radar signal is reconstructed based on the target matrix that makes the target optimization function reach the optimization target. Back projection imaging is performed based on the target radar signal to detect concealed power facilities.

2. The method for detecting concealed electrical facilities according to claim 1, characterized in that, The objective optimization function is expressed as: In the formula, For the first matrix, For the second matrix, This represents the product of the first and second matrices, i.e., the clutter matrix. For the target matrix, For the noise matrix, Indicates radar signal, and For regularization parameters, This represents summing the absolute values ​​of the 2-norms of the column vectors of the first matrix. This represents summing the absolute values ​​of the 2-norms of the column vectors of the transpose of the second matrix. This represents the sum of the absolute values ​​of all elements in the transpose of the target matrix.

3. The method for detecting concealed electrical facilities according to claim 1, characterized in that, The step of decomposing the clutter matrix into a first matrix and a second matrix includes: The clutter matrix is ​​grouped using factor group sparsity regularization to determine a first matrix and a second matrix, wherein the product of the first matrix and the second matrix is ​​the clutter matrix.

4. The method for detecting concealed electrical facilities according to any one of claims 1 to 3, characterized in that, The step of performing back projection imaging based on the target radar signal includes: For each imaging point in the target radar signal, determine the scattering response of multiple apertures corresponding to that imaging point; The effective echo sequence for each aperture is determined based on the scattering response of each aperture. Based on the effective echo sequence of each aperture, the correlation coefficient of each aperture is determined, and the scattering response of each aperture is weighted based on the correlation coefficient of each aperture to enhance the reflection energy of the target region in the target radar signal. Cross-correlation processing is performed on the weighted scattering responses of each aperture to reduce the reflection energy of non-target regions in the target radar signal and determine the reflection intensity of the imaging point. When the reflection intensity of each imaging point in the target radar signal is determined, a radar image is generated based on the reflection intensity of each imaging point.

5. The method for detecting concealed electrical facilities according to claim 4, characterized in that, The step of cross-correlation processing of the weighted scattering responses of each aperture includes: Determine the pairwise correlations between the weighted scattering responses of each aperture, and sum the pairwise correlations between the weighted scattering responses of each aperture to obtain the initial reflection intensity of the imaging point. The coherence factor of the imaging point is determined based on the pairwise correlation between the weighted scattering responses of each aperture. The initial reflection intensity is weighted using the coherence factor to determine the reflection intensity of the imaging point.

6. The method for detecting concealed electrical facilities according to claim 4, characterized in that, The step of determining the correlation coefficient of each aperture based on the effective echo sequence of each aperture includes: The effective echo sequence of the middle aperture among all apertures is determined as the reference sequence; Calculate the correlation coefficient between the effective echo sequence and the reference sequence for each aperture, and use the correlation coefficient between the effective echo sequence and the reference sequence for each aperture as the correlation coefficient for that aperture.

7. The method for detecting concealed electrical facilities according to claim 4, characterized in that, The step of determining the scattering response of multiple apertures corresponding to the imaging point includes: Based on the coordinates of the imaging point and the coordinates of each aperture, calculate the time delay vector for each aperture. Based on the time delay vector of each aperture, determine the A-type scan signal received by each aperture; Based on the A-type scan signals received from each aperture, the scattering response corresponding to each aperture is generated.

8. A device for detecting concealed electrical facilities, characterized in that, The device includes: The signal acquisition module is used to acquire radar signals and decompose the radar signals to obtain clutter matrix and target matrix; A matrix decomposition module is used to decompose the clutter matrix into a first matrix and a second matrix, and to construct a target optimization function based on the first matrix, the second matrix, and the target matrix; wherein the target optimization function aims to constrain the sparsity of the target matrix as much as possible and extract the effective signal components in the clutter matrix. The function solving module is used to solve the objective optimization function to determine the target matrix that makes the objective optimization function achieve the optimization objective; The signal reconstruction module is used to reconstruct the signal based on the target matrix determined when the target optimization function reaches the optimization target, so as to obtain the target radar signal; An imaging detection module is used to perform rear projection imaging based on the target radar signal to perform imaging detection of concealed power facilities.

9. A storage medium, characterized in that: The storage medium stores computer-readable instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of the electrical concealment detection method as described in any one of claims 1 to 7.

10. A computer device, characterized in that, include: One or more processors, and memory; The memory stores computer-readable instructions, which, when executed by the one or more processors, perform the steps of the electrical concealment facility detection method as described in any one of claims 1 to 7.

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