Target adaptive synthetic aperture radar suppression jamming method and device

Abstract

The application relates to the technical field of radar electronic countermeasure, and provides a target-adaptive synthetic aperture radar suppression jamming method and device. The method comprises the following steps: firstly, a target SAR image including a target to be protected is acquired; a target SAR image is taken as a reference to generate an adaptive product matrix used for modulating an adaptive jamming signal; then, a SAR signal intercepted by a jammer is received; the adaptive product matrix is multiplied by the intercepted SAR signal to obtain the adaptive jamming signal; finally, the jammer transmits the adaptive jamming signal to the SAR, a jamming suppression block similar to the target to be protected is adaptively generated in the SAR image, the probability that the target to be protected in the jammed area is discovered is reduced, and a better jamming effect can be achieved under the condition of lower jamming power.

Description

Technical Field

[0001] This application relates to the field of radar electronic countermeasures technology, and in particular to a target-adaptive synthetic aperture radar (SAR) jamming suppression method and apparatus. Background Technology

[0002] Synthetic Aperture Radar (SAR) is an imaging radar that can acquire high-resolution images of ground targets regardless of lighting and weather conditions, making it valuable in fields such as environmental monitoring. To protect sensitive targets from detection, electronic jamming of SAR is necessary.

[0003] SAR jamming methods can be divided into deception jamming methods and suppression jamming methods. SAR suppression jamming involves transmitting high-power broadband jamming signals into the SAR system, causing targets in the SAR image to be submerged in noise or interference blocks, thereby protecting the target from detection. SAR suppression jamming is widely used due to its ease of implementation and low dependence on reconnaissance parameters.

[0004] Existing SAR jamming techniques, such as stepped frequency shift jamming, two-dimensional noise coherent jamming, and frequency modulation mismatch jamming, typically rely on high jamming power to achieve good jamming effects. However, high power increases the risk of the jammer being exposed and located. At lower jamming power, existing technologies can only achieve limited jamming effects and cannot completely mask the target to be protected. Some solutions increase the energy density of the jamming block in the SAR image by reducing the area of ​​the jamming block, but this sacrifices the area of ​​the jamming coverage. Summary of the Invention

[0005] In view of this, embodiments of this application provide a target-adaptive synthetic aperture radar (SAR) jamming suppression method and apparatus to solve the problem of poor jamming suppression effect under low jamming power limitations in the prior art.

[0006] A first aspect of this application provides a target-adaptive synthetic aperture radar (SAR) jamming suppression method, comprising:

[0007] Acquire synthetic aperture radar (SAR) images of the target; the target SAR images include the target to be covered;

[0008] An adaptive product matrix is ​​generated using the target SAR image as a reference; the adaptive product matrix is ​​used to modulate the adaptive jamming signal.

[0009] The intercepted SAR signal is received by the jammer, and the intercepted SAR signal is multiplied by the adaptive product matrix to obtain the adaptive jamming signal;

[0010] Adaptive jamming signals are transmitted to the SAR via a jammer.

[0011] A second aspect of this application provides a target-adaptive synthetic aperture radar (SAR) jamming device, comprising:

[0012] The acquisition module is configured to acquire a synthetic aperture radar (SAR) image of the target; the target SAR image includes the target to be covered.

[0013] The generation module is configured to generate an adaptive product matrix with reference to the target SAR image; the adaptive product matrix is ​​used to modulate the adaptive jamming signal.

[0014] The generation module is also configured to receive SAR signals intercepted by the jammer, multiply the intercepted SAR signals by an adaptive product matrix, and obtain an adaptive jamming signal.

[0015] The jamming module is configured to transmit adaptive jamming signals to the SAR via a jammer.

[0016] A third aspect of this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described method.

[0017] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described method.

[0018] The beneficial effects of the embodiments in this application compared with the prior art are:

[0019] This application embodiment first acquires a target SAR image including the target to be covered, generates an adaptive product matrix for modulating an adaptive jamming signal using the target SAR image as a reference, then receives the SAR signal intercepted by the jammer, multiplies the intercepted SAR signal by the adaptive product matrix to obtain the adaptive jamming signal, and finally transmits the adaptive jamming signal to the SAR by the jammer. By adaptively generating jamming suppression blocks with structures similar to the target to be covered in the SAR image, the probability of the target to be covered being detected in the jammed area is reduced, and a better jamming effect can be achieved under low jamming power conditions. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this application, 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.

[0021] Figure 1 This is a schematic flowchart of a target-adaptive synthetic aperture radar jamming suppression method provided in an embodiment of this application.

[0022] Figure 2 This is a flowchart illustrating the method for generating an adaptive product matrix using a target SAR image as a reference, as provided in an embodiment of this application.

[0023] Figure 3 This is a flowchart illustrating the method for thresholding a target SAR image provided in an embodiment of this application.

[0024] Figure 4 This is a flowchart illustrating the method for calculating the frequency domain signal after the first processing, as provided in an embodiment of this application.

[0025] Figure 5 This is a flowchart illustrating the method for determining a time-domain signal provided in an embodiment of this application.

[0026] Figure 6 This is a flowchart illustrating a method for interpolating and mapping the values ​​of a time-domain signal within a preset region to obtain a first matrix, as provided in an embodiment of this application.

[0027] Figure 7 This is a flowchart illustrating the method for obtaining adaptive interference signals provided in an embodiment of this application.

[0028] Figure 8 This is a spaceborne SAR image of the target area under interference-free conditions provided in the embodiments of this application.

[0029] Figure 9 It is a simulated SAR image after interference obtained using the technical solution provided in the embodiments of this application.

[0030] Figure 10 It is a simulated SAR image obtained by using existing technology to perform two-dimensional noise coherent interference.

[0031] Figure 11 It is a simulated SAR image obtained by using existing technology to perform frequency modulation mismatch interference.

[0032] Figure 12 This is a schematic diagram of a target-adaptive synthetic aperture radar jamming device provided in an embodiment of this application.

[0033] Figure 13 This is a schematic diagram of the electronic device provided in the embodiments of this application. Detailed Implementation

[0034] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0035] The following will describe in detail, with reference to the accompanying drawings, a target-adaptive synthetic aperture radar jamming method and apparatus according to embodiments of this application.

[0036] As mentioned above, existing SAR suppression jamming techniques, such as stepped frequency shift jamming, two-dimensional noise coherent jamming, and frequency modulation mismatch jamming, typically rely on high jamming power to achieve good jamming effects. However, high power increases the risk of the jammer being exposed and located. At lower jamming power, the jamming effect achievable by existing technologies is limited and cannot completely mask the target to be protected. Some solutions increase the energy density of the jamming block in the SAR image by reducing the area of ​​the jamming block, but this sacrifices the area of ​​the jamming coverage.

[0037] In view of this, embodiments of this application provide a target-adaptive synthetic aperture radar (SAR) suppression jamming method. The method first acquires a target SAR image including the target to be covered, generates an adaptive product matrix of structural features for modulating an adaptive jamming signal using the target SAR image as a reference, then receives the SAR signal intercepted by the jammer, multiplies the intercepted SAR signal by the adaptive product matrix to obtain the adaptive jamming signal, and finally transmits the adaptive jamming signal to the SAR by the jammer. By adaptively generating jamming suppression blocks with structures similar to the target to be covered in the SAR image, the probability of the target to be covered in the jammed area being detected is reduced, and a good jamming effect can be achieved under low jamming power conditions.

[0038] Figure 1 This is a schematic flowchart illustrating a target-adaptive synthetic aperture radar jamming suppression method provided in an embodiment of this application. Figure 1 As shown, the method includes the following steps:

[0039] In step S101, the target SAR image is acquired.

[0040] The target SAR image includes the target to be covered.

[0041] In step S102, an adaptive product matrix is ​​generated with reference to the target SAR image.

[0042] The adaptive product matrix is ​​used to modulate the adaptive interference signal.

[0043] In step S103, the SAR signal intercepted by the jammer is received, and the intercepted SAR signal is multiplied by the adaptive product matrix to obtain the adaptive jamming signal.

[0044] In step S104, an adaptive jamming signal is transmitted to the SAR via a jammer.

[0045] In some embodiments of this application, the method may be executed by a jammer or by other terminal devices that are communicatively connected to the jammer, and no limitation is made here.

[0046] In some embodiments of this application, a synthetic aperture radar (SAR) image of the target can be acquired first. This SAR image may include the target to be covered.

[0047] In some embodiments of this application, an adaptive product matrix can be generated using the target SAR image as a reference. This adaptive product matrix is ​​used to modulate an adaptive interference signal. The specific implementation method for generating the adaptive product matrix is ​​described in detail below and will not be repeated here.

[0048] In some embodiments of this application, SAR signals intercepted by a jammer can be received, and the intercepted SAR signals can be multiplied by an adaptive product matrix to obtain an adaptive jamming signal. Then, by transmitting the adaptive jamming signal to the SAR via the jammer, adaptive suppression and jamming of the SAR signal can be achieved.

[0049] In other words, the jammer can intercept SAR signals frame by frame. For each received SAR signal frame, it is scrambled by multiplying with an adaptive product matrix to obtain an adaptive jamming signal, and then used to jam the SAR signal frame, thereby achieving adaptive suppression and jamming of the SAR signal.

[0050] According to the technical solution provided in the embodiments of this application, firstly, a target SAR image including the target to be covered is acquired. Using the target SAR image as a reference, a structural feature adaptive product matrix for modulating the adaptive jamming signal is generated. Then, the SAR signal intercepted by the jammer is received, and the intercepted SAR signal is multiplied by the adaptive product matrix to obtain the adaptive jamming signal. Finally, the jammer transmits the adaptive jamming signal to the SAR. By adaptively generating jamming suppression blocks with structures similar to the target to be covered in the SAR image, the probability of the target to be covered in the jammed area being detected is reduced, and a better jamming effect can be achieved under low jamming power conditions.

[0051] Figure 2 This is a flowchart illustrating a method for generating an adaptive product matrix using a target SAR image as a reference, as provided in an embodiment of this application. Figure 2 As shown, the method includes the following steps:

[0052] In step S201, the target SAR image is thresholded to obtain the segmented SAR image.

[0053] In step S202, the two-dimensional spectrum of the segmented SAR image is calculated.

[0054] In step S203, the frequency domain signal after the first processing is calculated based on the two-dimensional spectrum and the two-dimensional random sparse composite signal of the segmented SAR image.

[0055] In step S204, the frequency domain signal after the first processing is subjected to additional random phase processing to obtain the frequency domain signal after the second processing, and the frequency domain signal after the second processing is converted into a time domain signal.

[0056] In step S205, the values ​​of the time-domain signal within a preset region are interpolated to obtain a first matrix, and zeros are padded around the first matrix according to a preset number of rows and columns to obtain a second matrix.

[0057] In step S206, an inverse fast Fourier transform is performed on each column of the second matrix to obtain an adaptive product matrix.

[0058] In some embodiments of this application, when generating an adaptive product matrix with the target SAR image as a reference, the target SAR image can first be thresholded to obtain a segmented SAR image. Then, the two-dimensional spectrum of the segmented SAR image is determined, and the frequency domain signal after the first processing is calculated based on the two-dimensional spectrum of the segmented SAR image and the two-dimensional random sparse composite signal.

[0059] Next, additional random phase processing can be applied to the frequency domain signal after the first processing to obtain the frequency domain signal after the second processing. This second-processed frequency domain signal is then converted into a time domain signal. The values ​​of the time domain signal within a preset region are then interpolated to obtain a first matrix. Zeros are then padded around the first matrix according to a preset number of rows and columns to obtain a second matrix.

[0060] Finally, by performing an inverse fast Fourier transform on each column of the second matrix, the adaptive product matrix can be obtained.

[0061] Figure 3 This is a flowchart illustrating a method for thresholding a target SAR image according to an embodiment of this application. Figure 3 As shown, the method includes the following steps:

[0062] In step S301, a two-dimensional coordinate system is established in the target SAR image.

[0063] In this system, the origin of the two-dimensional coordinate system is the center point of the target to be covered, the horizontal axis is the SAR range direction, and the vertical axis is the SAR azimuth direction.

[0064] In step S302, the amplitude values ​​of each coordinate point are used to represent the target SAR image.

[0065] In step S303, a preset segmentation threshold is determined.

[0066] In step S304, the values ​​of coordinate points in the target SAR image whose amplitude values ​​are less than the preset segmentation threshold are set to zero, thus obtaining the segmented SAR image.

[0067] In some embodiments of this application, threshold segmentation of the target SAR image may be performed by first establishing a two-dimensional coordinate system in the target SAR image, where the origin of the two-dimensional coordinate system is the center point of the target to be covered, the horizontal axis is the SAR range direction, and the vertical axis is the SAR azimuth direction.

[0068] After establishing a two-dimensional coordinate system, the target SAR image can be represented using the amplitude values ​​of each coordinate point. In other words, the target SAR image can be represented using the established two-dimensional coordinate system. ,in It is a distance coordinate. It is the azimuth coordinate.

[0069] Simultaneously, a preset segmentation threshold can be determined, and the target SAR image can be segmented based on this preset segmentation threshold. The values ​​of coordinate points in the target SAR image whose amplitude values ​​are less than the preset segmentation threshold are set to zero, thereby obtaining the segmented SAR image.

[0070] In other words, it can make ,in, The segmented SAR image, It is a preset segmentation threshold.

[0071] Figure 4 This is a flowchart illustrating the method for calculating the frequency domain signal after the first processing, as provided in an embodiment of this application. Figure 4 As shown, the method includes the following steps:

[0072] In step S401, a two-dimensional fast Fourier transform is performed on the segmented SAR image to obtain the two-dimensional spectrum of the segmented SAR image.

[0073] In step S402, the two-dimensional spectrum is multiplied with a preset two-dimensional random sparse composite signal to obtain the frequency domain signal after the first processing.

[0074] In some embodiments of this application, a two-dimensional fast Fourier transform can be performed on the segmented SAR image to obtain the two-dimensional spectrum of the segmented SAR image. ;in, The two-dimensional spectrum of the segmented SAR image. This represents a two-dimensional Fast Fourier Transform. It is the range frequency. It is the azimuth frequency.

[0075] In some embodiments of this application, a two-dimensional spectrum can be multiplied by a preset two-dimensional random sparse composite signal to obtain the frequency domain signal after the first processing. ;in, This is the frequency domain signal after the first processing. The preset two-dimensional random sparse composite signal is composed of multiple discrete point frequency signals.

[0076] In some implementations, the preset two-dimensional random sparse composite signal can be defined by the following formula: ;in, yes The number of midpoint frequency signals, It is the sequence number of the point frequency signal. and It is the first Range frequency coefficient and azimuth frequency coefficient of a point frequency signal greater than or equal to 1 and less than or equal to 1 positive integers, It is the summation symbol. Represents an exponential function. It is the imaginary unit. It is pi (π).

[0077] Figure 5 This is a flowchart illustrating the method for determining a time-domain signal provided in an embodiment of this application. Figure 5 As shown, the method includes the following steps:

[0078] In step S501, the frequency domain signal after the first processing is subjected to additional random phase processing to obtain the frequency domain signal after the second processing.

[0079] In step S502, a two-dimensional fast Fourier inverse transform is performed on the frequency domain signal after the second processing to obtain the time domain signal.

[0080] In some embodiments of this application, the frequency domain signal after the first processing can be subjected to additional random phase processing to obtain the frequency domain signal after the second processing.

[0081] In one example, a formula can be used. The frequency domain signal after the first processing is subjected to additional random phase processing, wherein... This is the frequency domain signal after the first processing. This is the frequency domain signal after the second processing. It is a random phase, following an interval Uniform distribution within.

[0082] In some embodiments of this application, a two-dimensional inverse fast Fourier transform can also be performed on the frequency domain signal after the second processing to obtain the time domain signal.

[0083] In one example, the time-domain signal can be represented as ,in, For time-domain signals, This represents the two-dimensional inverse fast Fourier transform.

[0084] Figure 6 This is a flowchart illustrating a method for interpolating and mapping the values ​​of a time-domain signal within a preset region to obtain a first matrix, as provided in an embodiment of this application. Figure 6 As shown, the method includes the following steps:

[0085] In step S601, the range width and azimuth width of the interference region are determined, and the target rectangular region of the time domain signal is determined based on the range width and azimuth width of the interference region.

[0086] In step S602, a blank first matrix is ​​constructed, and the number of rows and columns of the blank first matrix is ​​determined.

[0087] In step S603, the time-domain signal corresponding to the lower left vertex of the target rectangular region is mapped to the first row and first column element of the blank first matrix, and the time-domain signal corresponding to the upper right vertex of the target rectangular region is mapped to the last row and last column element of the blank first matrix.

[0088] In step S604, the time-domain signals corresponding to other points in the target rectangular region are interpolated and mapped to the blank first matrix through spatial linear relationship to obtain the first matrix.

[0089] In some embodiments of this application, when determining the first matrix, the range width and azimuth width of the interference region can be determined first. The range width and azimuth width of the interference region can be determined according to actual needs, and typically need to be several times, or even tens of times, larger than the target to be covered; no limitation is made here. In one example, the determined range width of the interference region can be denoted as... The azimuth width of the interference area can be denoted as... .

[0090] In some embodiments of this application, the target rectangular region of the time domain signal can be determined based on the range width and azimuth width of the interference region, and the target rectangular region is the aforementioned preset region.

[0091] In other words, a distance-oriented region with a width of [missing information] can be defined in a two-dimensional coordinate system. , azimuth width is A rectangular region is defined, and this rectangular region is used as the target rectangular region. In one example, the target rectangular region can be defined by coordinate points. , , and Sure.

[0092] Simultaneously, a blank first matrix can be constructed, and the number of rows and columns of the blank first matrix can be determined. In one example, if the number of rows of the blank first matrix is ​​denoted as... The number of columns in the blank first matrix is ​​denoted as . ,but The following formula can be used to determine it: , The following formula can be used to determine it: .

[0093] in, It is the floor function. It is the azimuth modulation frequency of the target SAR signal. It is the frequency modulation of the target SAR signal. It is the equivalent radar velocity. It is the pulse repetition frequency. It is the sampling rate of the jammer. It is the preset number of rows in the adaptive product matrix. It is the preset number of columns in the adaptive product matrix. It's the speed of light.

[0094] In some embodiments of this application, the time-domain signal corresponding to the lower left vertex of the target rectangular region can be mapped to the first row and first column element of the blank first matrix, the time-domain signal corresponding to the upper right vertex of the target rectangular region can be mapped to the last row and last column element of the blank first matrix, and the time-domain signal values ​​corresponding to other points of the target rectangular region can be interpolated and mapped to the blank first matrix through spatial linear relationship to obtain the first matrix.

[0095] In other words, it can The value is mapped to the element in the first row and first column of the blank first matrix, and then... The values ​​are mapped to the elements in the last row and last column of the blank first matrix, and the values ​​of the other elements in the blank first matrix are mapped to the elements through a spatial linear relationship. The remaining target time-domain signal is interpolated. Among them, Coordinates The time-domain signal at that location, Coordinates The time-domain signal at that location.

[0096] The blank first matrix after value mapping can be called the first matrix. .

[0097] In some embodiments of this application, the first matrix can be... Padding zeros around the four sides to get OK The second matrix of columns Then for the second matrix Perform an inverse fast Fourier transform on each column to obtain an adaptive product matrix. .

[0098] Figure 7 This is a flowchart illustrating the method for obtaining adaptive interference signals provided in an embodiment of this application. Figure 7 As shown, the method includes the following steps:

[0099] In step S701, the jammer performs down-conversion processing on the intercepted SAR signal to obtain the baseband SAR signal.

[0100] In step S702, the target row is obtained from the adaptive product matrix.

[0101] The row index of the target row matches the current loop count of the program.

[0102] In step S703, the target line is multiplied with the baseband SAR signal to obtain the baseband interference signal.

[0103] In step S704, the baseband interference signal is up-converted to obtain an adaptive interference signal.

[0104] In some embodiments of this application, determining the adaptive jamming signal (i.e., step S103) may involve first down-converting the intercepted SAR signal to obtain a baseband SAR signal using a jammer. Then, a target row is obtained from the adaptive product matrix, the row index of which matches the current loop count of the program. The target row can be multiplied by the baseband SAR signal to obtain the baseband jamming signal. Finally, the baseband jamming signal is up-converted to obtain the adaptive jamming signal.

[0105] In some implementations, the adaptive jamming signal can be transmitted to the SAR by a jammer to achieve SAR suppression jamming.

[0106] In some embodiments of this application, step S103 may be executed sequentially and cyclically until a preset maximum number of iterations is reached. This preset maximum number of iterations may be related to an adaptive product matrix. The number of rows is the same.

[0107] In other words, step S103 can be executed once for each frame of captured SAR signal. Therefore, the row index of the target row obtained from the adaptive product matrix can be matched with the current loop count of the program.

[0108] For example, if this is the first execution of step S103, the target row could be an adaptive product matrix. The first row in the matrix. If the current execution is the m-th step S103, then the target row can be an adaptive product matrix. The m-th line in the array is a positive integer greater than 1 and less than or equal to the preset maximum number of loops.

[0109] After acquiring the target line, it can be multiplied by the baseband SAR signal to obtain the baseband jamming signal. Then, the baseband jamming signal is up-converted to obtain the adaptive jamming signal.

[0110] The technical solution provided in this application embodiment utilizes the structural information of the target to adaptively modulate the interference signal and form an interference suppression block with a structure similar to the target. This can solve the problem of poor interference suppression effect under low interference power limitation in the prior art, without sacrificing the interference cover area.

[0111] This application provides examples of interference results obtained from computer simulation interference experiments on spaceborne SAR using the method provided in this application. Furthermore, to compare the interference effects of the method provided in this application with existing technologies, this application also provides simulation interference experiment results using existing technologies for two-dimensional noise coherent interference and frequency modulation mismatch interference.

[0112] Figure 8 This is a spaceborne SAR image of the target area under interference-free conditions provided in the embodiments of this application. Figure 9 It is a simulated SAR image after interference obtained using the technical solution provided in the embodiments of this application.

[0113] like Figure 8 As shown, there is a clearly visible rectangular building in the SAR image before the jamming, namely the building within the white dashed box. This building is the target to be covered.

[0114] The computer simulation interference was conducted using the method provided in this application. The interference-to-signal ratio (the power ratio of the interference signal to the ground object echo signal) used in the experiment was 5 dB. Figure 9 The image shows the corresponding interference effect. (From...) Figure 8 As can be seen, the method provided in this application can form a suppression interference block around the target, and the structure of the interference block is similar to the structure of the target, making the target difficult to identify.

[0115] On the other hand, computer simulation interference was conducted using existing two-dimensional noise coherent interference and frequency modulation mismatch interference, with the interference-to-signal ratio used in the experiment being 5dB. Figure 10 It is a simulated SAR image obtained by using existing technology to perform two-dimensional noise coherent interference. Figure 11These are simulated SAR images obtained after frequency modulation mismatch interference using existing techniques. The coverage area of ​​the interference blocks formed by these two existing techniques is the same as that obtained using the method provided in this application. Figure 10 and Figure 11 As can be seen, at lower interference power, neither of the two existing technologies can effectively mask the target to be protected.

[0116] As can be seen from the comparison, this method can form adaptive interference to the target, and the interference effect is better under low interference power conditions, without sacrificing the interference cover area.

[0117] All of the above-mentioned optional technical solutions can be combined in any way to form the optional embodiments of this application, and will not be described in detail here.

[0118] The following are embodiments of the apparatus described in this application, which can be used to execute the embodiments of the method described in this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the method described in this application.

[0119] Figure 12 This is a schematic diagram of a target-adaptive synthetic aperture radar jamming device provided in an embodiment of this application. Figure 12 As shown, the device includes:

[0120] The acquisition module 1201 is configured to acquire a synthetic aperture radar (SAR) image of the target; the target SAR image includes the target to be covered.

[0121] The generation module 1202 is configured to generate an adaptive product matrix with reference to the target SAR image; the adaptive product matrix is ​​used to modulate the adaptive jamming signal.

[0122] The generation module 1202 is also configured to receive the SAR signal intercepted by the jammer, multiply the intercepted SAR signal by the adaptive product matrix to obtain the adaptive jamming signal.

[0123] The jamming module 1203 is configured to transmit adaptive jamming signals to the SAR via a jammer.

[0124] According to the technical solution provided in the embodiments of this application, firstly, a target SAR image including the target to be covered is acquired. Using the target SAR image as a reference, a structural feature adaptive product matrix for modulating the adaptive jamming signal is generated. Then, the SAR signal intercepted by the jammer is received, and the intercepted SAR signal is multiplied by the adaptive product matrix to obtain the adaptive jamming signal. Finally, the jammer transmits the adaptive jamming signal to the SAR. By adaptively generating jamming suppression blocks with structures similar to the target to be covered in the SAR image, the probability of the target to be covered in the jammed area being detected is reduced, and a better jamming effect can be achieved under low jamming power conditions.

[0125] In some implementations, generating an adaptive product matrix with a target SAR image as a reference includes: performing threshold segmentation on the target SAR image to obtain a segmented SAR image; calculating the two-dimensional spectrum of the segmented SAR image; calculating the frequency domain signal after the first processing based on the two-dimensional spectrum of the segmented SAR image and the two-dimensional random sparse composite signal; performing additional random phase processing on the frequency domain signal after the first processing to obtain a frequency domain signal after the second processing, and converting the frequency domain signal after the second processing into a time domain signal; interpolating and mapping the values ​​of the time domain signal within a preset region to obtain a first matrix, and padding the first matrix with zeros around its perimeter according to a preset number of rows and columns to obtain a second matrix; and performing an inverse fast Fourier transform on each column of the second matrix to obtain an adaptive product matrix.

[0126] In some implementations, threshold segmentation of the target SAR image includes: establishing a two-dimensional coordinate system in the target SAR image; wherein the origin of the two-dimensional coordinate system is the center point of the target to be covered, the horizontal axis is the SAR range direction, and the vertical axis is the SAR azimuth direction; using the amplitude value of each coordinate point to represent the target SAR image; determining a preset segmentation threshold; setting the values ​​of coordinate points in the target SAR image whose amplitude values ​​are less than the preset segmentation threshold to zero, thereby obtaining the segmented SAR image.

[0127] In some implementations, the frequency domain signal after the first processing is calculated as follows: a two-dimensional fast Fourier transform is performed on the segmented SAR image to obtain the two-dimensional spectrum of the segmented SAR image; the two-dimensional spectrum is multiplied by a preset two-dimensional random sparse composite signal to obtain the frequency domain signal after the first processing; wherein, the preset two-dimensional random sparse composite signal is... , The preset two-dimensional random sparse composite signal is composed of multiple discrete point frequency signals; It is the number of point frequency signals. It is the sequence number of the point frequency signal. and It is the first Range frequency and azimuth frequency of a point frequency signal It is the range frequency coefficient. It is the azimuth frequency coefficient. It is the summation symbol. Represents an exponential function. It is the imaginary unit. It is pi (π).

[0128] In some implementations, the time-domain signal is determined using the following method: [using formula] The frequency domain signal after the first processing is subjected to additional random phase processing to obtain the frequency domain signal after the second processing; where... This is the frequency domain signal after the first processing. This is the frequency domain signal after the second processing. It is a random phase, following an interval The signal is uniformly distributed within the frequency domain; a two-dimensional inverse fast Fourier transform is performed on the frequency domain signal after the second processing to obtain the time domain signal. ;in, For time-domain signals, This represents the two-dimensional inverse fast Fourier transform.

[0129] In some implementations, the first matrix is ​​obtained by interpolating and mapping the values ​​of the time-domain signal within a preset region, including: determining the range width and azimuth width of the interference region, and determining the target rectangular region of the time-domain signal based on the range width and azimuth width of the interference region; constructing a blank first matrix and determining the number of rows and columns of the blank first matrix; mapping the time-domain signal corresponding to the lower left vertex of the target rectangular region to the first row and first column element of the blank first matrix, and mapping the time-domain signal corresponding to the upper right vertex of the target rectangular region to the last row and last column element of the blank first matrix; and interpolating the time-domain signals corresponding to other points in the target rectangular region to the blank first matrix through spatial linear relationships to obtain the first matrix.

[0130] In some implementations, the target rectangular region, determined by the distance width and azimuth width of the interference region, is defined by coordinate points. , , and The enclosed rectangular area; within which, The distance width of the interference area. The azimuth width of the interference area.

[0131] In some implementations, the number of rows in the blank first matrix is ​​determined by a formula. The number of columns in the blank first matrix is ​​determined by the formula. Determined; among them, The row number of the first blank matrix. The number of columns in the blank first matrix. It is the floor function. It is the azimuth modulation frequency of the target SAR signal. It is the frequency modulation of the target SAR signal. It is the equivalent radar velocity. It is the pulse repetition frequency. It is the sampling rate of the jammer. It is the preset number of rows in the adaptive product matrix. It is the preset number of columns in the adaptive product matrix. It's the speed of light.

[0132] In some implementations, the adaptive jamming signal is obtained as follows: the jammer down-converts the intercepted SAR signal to obtain a baseband SAR signal; the target row is obtained from the adaptive product matrix; the row index of the target row is matched with the current loop count of the program; the target row is multiplied by the baseband SAR signal to obtain the baseband jamming signal; the baseband jamming signal is up-converted to obtain the adaptive jamming signal.

[0133] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0134] Figure 13 This is a schematic diagram of an electronic device provided in an embodiment of this application. For example... Figure 13 As shown, the electronic device 13 of this embodiment includes: a processor 1301, a memory 1302, and a computer program 1303 stored in the memory 1302 and executable on the processor 1301. When the processor 1301 executes the computer program 1303, it implements the steps in the various method embodiments described above. Alternatively, when the processor 1301 executes the computer program 1303, it implements the functions of each module / unit in the various device embodiments described above.

[0135] Electronic device 13 may be a desktop computer, laptop, handheld computer, cloud server, or other electronic device. Electronic device 13 may include, but is not limited to, processor 1301 and memory 1302. Those skilled in the art will understand that... Figure 13 This is merely an example of electronic device 13 and does not constitute a limitation on electronic device 13. It may include more or fewer components than shown, or different components.

[0136] The processor 1301 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0137] The memory 1302 can be an internal storage unit of the electronic device 13, such as a hard disk or RAM of the electronic device 13. The memory 1302 can also be an external storage device of the electronic device 13, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, FlashCard, etc., equipped on the electronic device 13. The memory 1302 can also include both internal and external storage units of the electronic device 13. The memory 1302 is used to store computer programs and other programs and data required by the electronic device.

[0138] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0139] If an integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program may include computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. A computer-readable medium may include: any entity or device capable of carrying computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0140] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A target-adaptive synthetic aperture radar jamming suppression method, characterized in that, include: Acquire synthetic aperture radar (SAR) images of the target; The target SAR image includes the target to be covered; An adaptive product matrix is ​​generated using the target SAR image as a reference; The adaptive product matrix is ​​used to modulate the adaptive interference signal; The SAR signal intercepted by the jammer is received, and the intercepted SAR signal is multiplied by the adaptive product matrix to obtain the adaptive jamming signal; The adaptive jamming signal is transmitted to the SAR via a jammer; The process of generating an adaptive product matrix using the target SAR image as a reference includes: The target SAR image is subjected to threshold segmentation to obtain the segmented SAR image; Calculate the two-dimensional spectrum of the segmented SAR image; Based on the two-dimensional spectrum and two-dimensional random sparse composite signal of the segmented SAR image, the frequency domain signal after the first processing is calculated; The frequency domain signal after the first processing is subjected to additional random phase processing to obtain the frequency domain signal after the second processing, and the frequency domain signal after the second processing is converted into a time domain signal. The first matrix is ​​obtained by interpolating and mapping the values ​​of the time-domain signal within a preset region. The second matrix is ​​obtained by padding the first matrix with zeros around its perimeter according to a preset number of rows and columns. Perform an inverse fast Fourier transform on each column of the second matrix to obtain the adaptive product matrix.

2. The method according to claim 1, characterized in that, Threshold segmentation of the target SAR image includes: A two-dimensional coordinate system is established in the target SAR image; wherein the origin of the two-dimensional coordinate system is the center point of the target to be covered, the horizontal axis is the SAR range direction, and the vertical axis is the SAR azimuth direction. The target SAR image is represented by the amplitude values ​​at each coordinate point; Determine the preset segmentation threshold; The values ​​of coordinate points in the target SAR image whose amplitude values ​​are less than the preset segmentation threshold are set to zero to obtain the segmented SAR image.

3. The method according to claim 1, characterized in that, The frequency domain signal after the first processing is calculated in the following way: A two-dimensional fast Fourier transform is performed on the segmented SAR image to obtain the two-dimensional spectrum of the segmented SAR image; The two-dimensional spectrum is multiplied by a preset two-dimensional random sparse composite signal to obtain the frequency domain signal after the first processing. Wherein, the preset two-dimensional random sparse composite signal is , The preset two-dimensional random sparse composite signal is composed of multiple discrete point frequency signals; It is the number of point frequency signals. It is the sequence number of the point frequency signal. and It is the first Range frequency coefficient and azimuth frequency coefficient of a point frequency signal It is the range frequency. It is the azimuth frequency. It is the summation symbol. Represents an exponential function. It is the imaginary unit. It is pi (π).

4. The method according to claim 3, characterized in that, The time-domain signal is determined in the following manner: Use formula The frequency domain signal after the first processing is subjected to additional random phase processing to obtain the frequency domain signal after the second processing; wherein, This refers to the frequency domain signal after the first processing. This refers to the frequency domain signal after the second processing. It is a random phase, following an interval Uniform distribution within; The time-domain signal is obtained by performing a two-dimensional inverse fast Fourier transform on the frequency domain signal after the second processing. ;in, The time-domain signal, This represents the two-dimensional inverse fast Fourier transform. For distance coordinates, These are the azimuth coordinates.

5. The method according to claim 1, characterized in that, The first matrix is ​​obtained by interpolating and mapping the values ​​of the time-domain signal within a preset region, including: Determine the range width and azimuth width of the interference region, and determine the target rectangular region of the time domain signal based on the range width and azimuth width of the interference region; Construct a blank first matrix and determine the number of rows and columns of the blank first matrix; The time-domain signal corresponding to the lower left vertex of the target rectangular region is mapped to the first row and first column element of the blank first matrix, and the time-domain signal corresponding to the upper right vertex of the target rectangular region is mapped to the last row and last column element of the blank first matrix. The time-domain signals corresponding to other points in the target rectangular region are interpolated into the blank first matrix using spatial linear relationships to obtain the first matrix.

6. The method according to claim 5, characterized in that, The target rectangular area, determined by the range width and azimuth width of the interference area, is defined by coordinate points. , , and The enclosed rectangular area; in, The distance-direction width of the interference region. The azimuth width of the interference region.

7. The method according to claim 6, characterized in that, The number of rows in the blank first matrix is ​​determined by the formula. The number of columns in the blank first matrix is ​​determined by the formula. Sure; in, The row number of the blank first matrix. The number of columns in the blank first matrix. It is the floor function. It is the azimuth modulation frequency of the SAR signal. It is the range-modulated frequency of the SAR signal. It is the equivalent radar velocity. It is the pulse repetition frequency. It is the sampling rate of the jammer. It is the preset number of rows in the adaptive product matrix. It is the preset number of columns in the adaptive product matrix. It's the speed of light.

8. The method according to claim 1, characterized in that, The adaptive interference signal is obtained in the following way: The jammer down-converts the intercepted SAR signal to obtain a baseband SAR signal; the target row is obtained from the adaptive product matrix; the row index of the target row matches the current loop count of the program; Multiply the target row by the baseband SAR signal to obtain the baseband interference signal; The baseband interference signal is up-converted to obtain the adaptive interference signal.

9. A target-adaptive synthetic aperture radar jamming device, characterized in that, include: The acquisition module is configured to acquire synthetic aperture radar (SAR) images of the target. The target SAR image includes the target to be covered; The generation module is configured to generate an adaptive product matrix with reference to the target SAR image; the adaptive product matrix is ​​used to modulate an adaptive jamming signal. The generation module is also configured to receive SAR signals intercepted by the jammer, multiply the intercepted SAR signals by the adaptive product matrix to obtain an adaptive jamming signal; The jamming module is configured to transmit the adaptive jamming signal to the SAR via a jammer; The process of generating an adaptive product matrix using the target SAR image as a reference includes: The target SAR image is subjected to threshold segmentation to obtain the segmented SAR image; Calculate the two-dimensional spectrum of the segmented SAR image; Based on the two-dimensional spectrum and two-dimensional random sparse composite signal of the segmented SAR image, the frequency domain signal after the first processing is calculated; The frequency domain signal after the first processing is subjected to additional random phase processing to obtain the frequency domain signal after the second processing, and the frequency domain signal after the second processing is converted into a time domain signal. The first matrix is ​​obtained by interpolating and mapping the values ​​of the time-domain signal within a preset region. The second matrix is ​​obtained by padding the first matrix with zeros around its perimeter according to a preset number of rows and columns. Perform an inverse fast Fourier transform on each column of the second matrix to obtain the adaptive product matrix.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 8.

11. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 8.

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