A method and apparatus for suppressing azimuth radio frequency interference in the image domain

Abstract

This application discloses an image domain azimuth radio frequency interference suppression method and apparatus. First, the imaging matrix carrying interference signals is distinguished according to a detection threshold to obtain a set of sampling point intervals. Then, an interference signal set is extracted from the sampling point interval set according to a decision threshold. Next, strong scattering point targets overlapping with the interference signals are removed from the interference signal set according to a search threshold to obtain the strong scattering point interval to be removed. A coarse estimate of the degree of the strong scattering point interval is estimated, and the coarse estimate is refined to obtain the actual degree. Finally, the sampling point interval set is rotated, notch filtered, and rotated in reverse to complete the sampling point interval set. The method utilizes the difference in azimuth time domain to detect interference signals and separate them from strong scattering point targets. The rotation operation concentrates the interference signals in a narrower position, and the filtering quickly suppresses high-power interference, minimizing image distortion and reducing computational load.

Description

Technical Field

[0001] This application relates to the field of radar signal processing, and more specifically, to a method for suppressing radio frequency interference in the azimuth direction of the image domain. Background Technology

[0002] Radio frequency interference (RFI) is a challenging problem affecting the accuracy of synthetic aperture radar remote sensing. It can cause overlap between the RFI and the real echo signal in the time, frequency, or spatial domains, which can severely impact imaging quality and subsequent interpretation.

[0003] However, when performing pulse compression in synthetic aperture radar, a conjugate signal highly coherent with the transmitted signal is often selected as the filter coefficient for imaging. This process significantly improves the gain of the transmitted signal and can mitigate some incoherent radio frequency interference. Nevertheless, despite this mitigation effect, high-power RFI will inevitably still exist in the focused image after imaging processing.

[0004] In most existing high-power RFIs, the energy of the echo in the range-direction frequency domain is significantly higher than that of the useful signal in the same frequency band. This type of interference can be effectively identified and suppressed by setting adaptive thresholds in the range-direction frequency domain and the range-direction time-frequency domain. However, some high-power RFIs lack obvious characteristics in the range-direction variation domain of the echo, making them difficult to detect using traditional methods. Therefore, how to detect these high-power RFIs and simultaneously suppress radio frequency interference quickly has become a problem that researchers in this field need to consider. Summary of the Invention

[0005] The purpose of this application is to overcome the shortcomings of existing technologies and provide an image domain azimuth radio frequency interference suppression method and apparatus. By identifying high-power radio frequency interference from the image domain azimuth direction and rotating it to the change domain for filtering, the radio frequency interference is suppressed quickly. This effectively avoids the problem of signal loss caused by the filtering out of strong scattering point targets.

[0006] The objective of this application is achieved through the following technical solution:

[0007] Firstly, this application proposes an image domain azimuth radio frequency interference suppression method, comprising:

[0008] The set of sampling point intervals is obtained by distinguishing the imaging matrix carrying interference signals according to the detection threshold;

[0009] The set of interference signals is extracted from the set of sampling point intervals based on the decision threshold;

[0010] Based on the search threshold, strong scattering point targets that overlap with the interference signals are removed from the set of interference signals to obtain the interval for removing strong scattering points;

[0011] Estimate the coarse degree of the interval where strong scattering points are removed;

[0012] The coarsely estimated degree is refined to obtain the actual degree.

[0013] The sampling point interval set is rotated, notch filtered, and rotated in reverse according to the actual degree to complete the sampling point interval set.

[0014] In an optional implementation, the imaging matrix carrying the interference signal includes range cells, and the step of distinguishing the imaging matrix carrying the interference signal according to a detection threshold to obtain a set of sampling point intervals includes:

[0015] Calculate the average value μ and standard deviation σ of the range cells for the imaging matrix carrying the interference signal;

[0016] The detection threshold Th is obtained by using the mean μ and standard deviation σ according to Th = μ + 2σ;

[0017] The sampling point interval set is obtained by statistically analyzing the distance units that are higher than the detection threshold.

[0018] In an optional implementation, the imaging matrix carrying the interference signal further includes azimuth sampling points, and the step of extracting the interference signal set from the sampling point interval set according to a decision threshold includes:

[0019] Set 0.1% of the number of the azimuth sampling points as the decision threshold;

[0020] Within the set of sampling point intervals, signals above the decision threshold are extracted as interference signals to obtain a set of interference signals.

[0021] In an optional implementation, the step of removing strong scattering point targets overlapping with the interference signals from the set of interference signals according to a search threshold to obtain the interval for removing strong scattering points includes:

[0022] Calculate the average value μ of the interference signals in the set of interference signals. e and standard deviation σ e ;

[0023] Based on the average value μ e and standard deviation σ e According to Ths = μ e +3σ e Obtain the search threshold Ths;

[0024] Search for peak values ​​greater than the search threshold Ths, and obtain the peak position ma of the peak value;

[0025] Based on the peak position ma and the decision threshold Thr, a distance cell with a search interval of [ma-Thr, ma+Thr] is found.

[0026] If the number of distance cells exceeds the decision threshold and the peak value is less than the search threshold, the peak value is discarded as a strong scattering point target that overlaps with the interference signal, thus obtaining the interval for discarding strong scattering points.

[0027] In an optional implementation, the step of estimating the coarse degree of the region where strong scattering points are removed includes:

[0028] Perform a Fast Fourier Transform (FFT) on the interval where strong scattering points are removed, calculate the difference Δf between the highest and lowest frequencies of the azimuth spectrum, and combine this with the pulse repetition frequency (PRF) and the number of interfering signals (r) to... Obtain the slope k of the interval signal;

[0029] Combining the slope k of the interval signal, the coarse estimate θ0 is obtained by using θ0 = (90° - arctan(k)) - m·180°, where m is an integer and the range of the coarse estimate θ0 is [-90°, 90°].

[0030] In an optional implementation, the step of refining the coarsely estimated degree to obtain the actual degree includes:

[0031] Starting from a coarsely estimated degree, the set of interference signals is rotated with a search step size of 0.001°;

[0032] The actual degree is obtained when the peak value exceeds the search threshold and the number of distance cells is less than the decision threshold.

[0033] In an optional implementation, the step of performing rotation, notch filtering, and reverse rotation on the set of sampling point intervals based on the actual degrees to complete the set of sampling point intervals includes:

[0034] A rotation operation is performed on the set of sampling point intervals, wherein the rotation operation is as follows:

[0035]

[0036] Notch filtering is applied to the rotated set of sampling point intervals based on a notch threshold, where the notch threshold is Thn = μ. n +3σ n μ n σ is the average value of the rotated set of sampling point intervals. n The standard deviation of the rotated set of sampling point intervals;

[0037] A reverse rotation operation is performed on the set of sampling point intervals after notch filtering to complete the set of sampling point intervals. The reverse rotation operation is as follows:

[0038] Where n is the number of distance cells, PRF is the pulse repetition frequency, G is the variation function, θ is the actual degree, α is the independent variable in the domain of variation, and t is the distance cell.

[0039] Secondly, this application proposes an image domain azimuth radio frequency interference suppression device, characterized in that the device comprises:

[0040] The differentiation module is used to differentiate the imaging matrix carrying interference signals according to the detection threshold to obtain a set of sampling point intervals;

[0041] The extraction module is used to extract the set of interference signals from the set of sampling point intervals according to the decision threshold;

[0042] The elimination module is used to eliminate strong scattering point targets that overlap with the interference signals from the set of interference signals according to the search threshold, so as to obtain the interval of strong scattering points to be eliminated.

[0043] A coarse estimation module is used to estimate the coarse degree of the interval where strong scattering points are removed;

[0044] The refinement module is used to refine the coarsely estimated degree to obtain the actual degree.

[0045] The completion module is used to perform rotation, notch filtering, and reverse rotation on the set of sampling point intervals based on the actual degree, thereby completing the set of sampling point intervals.

[0046] Thirdly, this application also proposes a computer device comprising a processor and a memory, wherein the memory stores a computer program, which is loaded and executed by the processor to implement the image domain azimuth radio frequency interference suppression method as described in any of the first aspects.

[0047] Fourthly, this application also proposes a computer-readable storage medium storing a computer program that is loaded and executed by a processor to implement the image domain azimuth radio frequency interference suppression method as described in any of the first aspects.

[0048] The main solution and its various further alternatives described above can be freely combined to form multiple solutions, all of which are solutions that can be adopted and are claimed in this application; furthermore, the (non-conflicting alternatives) can also be freely combined with each other and with other alternatives. Those skilled in the art, after understanding the solution of this application, will realize from the prior art and common general knowledge that there are many combinations, all of which are technical solutions to be protected by this application, and will not be exhaustively listed here.

[0049] This application discloses an image domain azimuth radio frequency interference suppression method and apparatus. First, the imaging matrix carrying interference signals is distinguished according to a detection threshold to obtain a set of sampling point intervals. Then, an interference signal set is extracted from the sampling point interval set according to a decision threshold. Next, strong scattering point targets overlapping with the interference signals are removed from the interference signal set according to a search threshold to obtain the strong scattering point interval to be removed. A coarse estimate of the degree of the strong scattering point interval is estimated, and the coarse estimate is refined to obtain the actual degree. Finally, the sampling point interval set is rotated, notch filtered, and rotated in reverse to complete the sampling point interval set. The method utilizes the difference in azimuth time domain to detect interference signals and separate them from strong scattering point targets. The rotation operation concentrates the interference signals in a narrower position, and the filtering quickly suppresses high-power interference, minimizing image distortion and reducing computational load. Attached Figure Description

[0050] Figure 1 A flowchart illustrating the image domain azimuth radio frequency interference suppression method provided in an embodiment of this application is shown.

[0051] Figure 2 This paper illustrates another flowchart of the image domain azimuth radio frequency interference suppression method according to an embodiment of this application.

[0052] Figure 3 This is the temporal domain feature of the 1412th distance unit in the measured data image domain in the embodiments of this application.

[0053] Figure 4 This is the time-frequency domain feature of the 1412th distance unit in the image domain in this embodiment of the application.

[0054] Figure 5 This is the change domain α feature of the 1412th distance unit in the image domain after rotation by θ in the embodiments of this application.

[0055] Figure 6 This refers to the α-β spectrum feature of the change domain after rotating the 1412th distance unit in the image domain by θ in the embodiments of this application.

[0056] Figure 7 This is the result of performing notch filtering on the 1412th distance unit in the image domain in the variation domain α in the embodiments of this application.

[0057] Figure 8 In this embodiment of the application, the 1412th distance unit in the image domain is rotated by -θ in the change domain and then restored. Figure 3 Temporal characteristics of the scattering point of a medium-intensity target.

[0058] Figure 9 It is the time-frequency domain feature of the 1412th distance unit in the image domain after interference suppression in the embodiments of this application.

[0059] Figure 10a This is the result before the interference suppression processing of the measured data image by the method of this application.

[0060] Figure 10b The image is the result of applying interference suppression to all distance cells using the measured data image of the method in this application. Detailed Implementation

[0061] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. This application can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, unless otherwise specified, the following embodiments and features in the embodiments can be combined with each other.

[0062] Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0063] In existing technologies, some high-power radio frequency interferences lack obvious characteristics in the range-varying domain of the echo, making them difficult to detect using traditional methods. Considering that this type of interference often presents as a bright straight line parallel to the azimuth direction in the imaging result, this problem can be solved by addressing it from the perspective of the image domain azimuth direction. Therefore, to solve the above problem, this application proposes an image domain azimuth-varying radio frequency interference suppression method. By identifying high-power radio frequency interference from the image domain azimuth direction and rotating it to the range-varying domain for filtering, the method achieves rapid suppression of radio frequency interference. This effectively avoids the problem of signal loss caused by the filtering out of strong scattering point targets. The following is a detailed description of this method.

[0064] Please refer to Figure 1 , Figure 1 The flowchart of the image domain azimuth radio frequency interference suppression method provided in this application embodiment is shown, including the following steps:

[0065] S110. Based on the detection threshold, the imaging matrix carrying the interference signal is distinguished to obtain the set of sampling point intervals.

[0066] The imaging matrix carrying the interference signal is X(τ,t), where τ represents the range cell and t represents the azimuth sampling point. The average value μ and standard deviation σ of the range cell are calculated for the imaging matrix carrying the interference signal. The detection threshold Th is obtained according to the average value μ and standard deviation σ according to Th=μ+2σ. The sampling point interval set is obtained by statistically analyzing the range cells that are higher than the detection threshold.

[0067] For the imaging matrix along the range direction, the detection threshold is calculated according to Th = μ + 2σ. The distance cells in the imaging matrix that are higher than the detection threshold are counted to obtain the set of sampling point intervals G = [t1, t2, t3, ..., t n ].

[0068] S120. Extract the set of interference signals from the set of sampling point intervals according to the decision threshold.

[0069] Setting 0.1% of the number of azimuth sampling points as the decision threshold, signals exceeding the decision threshold within the sampling point interval set are extracted as interference signals, resulting in the interference signal set G. r =[t1,t2,t3...,t r If, within the set of sampling points, a signal not exceeding the decision threshold indicates the presence of a strong scattering point target.

[0070] S130. Based on the search threshold, remove strong scattering point targets that overlap with the interference signals from the set of interference signals to obtain the interval for removing strong scattering points.

[0071] First, calculate the average value μ of the interference signals in the interference signal set. e and standard deviation σ e According to the average value μ e and standard deviation σ e According to Ths = μ e +3σ e The search threshold Ths is obtained, and then the peak value greater than the search threshold Ths is searched to obtain the peak position ma. Based on the peak position ma and the decision threshold Thr, the range of distance cells in the range [ma-Thr, ma+Thr] is searched. If the number of distance cells exceeds the decision threshold and the peak value is less than the search threshold, the peak value is removed as a strong scattering point target that overlaps with the interference signal, and the range of strong scattering points to be removed is obtained.

[0072] S140. Estimate the coarse degree of the interval after removing strong scattering points.

[0073] Perform a Fast Fourier Transform (FFT) on the interval where strong scattering points are removed, calculate the difference Δf between the highest and lowest frequencies of the azimuth spectrum, and combine this with the pulse repetition frequency (PRF) and the number of interfering signals (r) to... The interval signal slope k is obtained. At the same time, combined with the interval signal slope k, the coarse estimate of degree θ0 is obtained by using θ0=(90°-arctan(k))-m·180°, where m is an integer and the range of the coarse estimate of degree θ0 is [-90°, 90°].

[0074] S150. Refine the coarsely estimated degree to obtain the actual degree.

[0075] Starting with a rough estimate of the degree, the interference signal set is rotated with a search step of 0.001°. The actual degree is obtained when the peak value exceeds the search threshold and the number of distance cells is less than the decision threshold.

[0076] When rotating the interference region, and obtaining the actual degree when the peak value exceeds the search threshold and the number of distance cells is less than the decision threshold, it can be considered as... Stop searching;

[0077] S160. Perform rotation, notch filtering, and reverse rotation on the sample point interval set according to the actual degree to complete the sample point interval set.

[0078] The set of sampling point intervals is rotated. The rotation operation is as follows:

[0079]

[0080] Notch filtering is applied to the rotated set of sampling point intervals based on the notch threshold, which is Thn = μ. n +3σ n μ n σ is the average value of the rotated set of sampling point intervals. n The standard deviation of the rotated set of sampling point intervals;

[0081] A reverse rotation operation is performed on the set of sampling point intervals after notch filtering to complete the set of sampling point intervals. The reverse rotation operation is as follows: Where n is the number of distance cells, PRF is the pulse repetition frequency, G is the variation function, θ is the actual degree, α is the independent variable in the domain of variation, and t is the distance cell.

[0082] Step S160 is to reconstruct the previously removed strong scattering point targets back into the recovered range cell signal.

[0083] Please refer to the following. Figure 2 , Figure 2 The diagram illustrates another flowchart of the image domain azimuth radio frequency interference suppression method according to an embodiment of this application, including the following steps:

[0084] Step 1: Determine the distance cell with higher energy.

[0085] Step 2: Determine the location of the interference pulse for the range cells with strong targets and interference. After all the range cells with strong targets and interference have rotated, proceed to step 6.

[0086] Step 3: Remove target information that overlaps with interference from the range cell.

[0087] Step 4: Perform FFT on the interference interval to estimate θ.

[0088] Step 5: Fine-grained search for θ.

[0089] Step 6: Perform an θ-order rotation between each range cell containing interference and a target.

[0090] Step 7: Notch filter the data that exceeds the detection threshold.

[0091] Step 8: Perform a -θ rotation to fill in the target position.

[0092] Step 1 identifies range cells with high upward energy. These high-energy range cells can be classified into three types: interfering targets, strong signal targets, and a combination of both. Step 2 processes one of these random range cells. On the azimuth sampling cell, the difference in length occupied by the interference and the target determines whether the target extracted in Step 1 is interference, a combination of interference and a strong signal target, or a signal target. If it is a signal target, no processing is performed, and the process returns to Step 1. Otherwise, Step 3 is executed for that range cell. Step 3 again uses the difference in length occupied by the target and the interference to remove the target. Then, Steps 4 and 5 are executed to calculate the optimal rotation angle for suppressing interference. In Step 6, all range cells that meet the criteria of Step 1 are rotated by an angle into the variation domain α. In Step 7, the interference is suppressed. Finally, in Step 8, the range cells are rotated by -θ to reconstruct the original data.

[0093] The following section uses the 1412th distance cell as an example to further illustrate an image domain azimuth radio frequency interference suppression method in this application. Figure 3 This is the temporal domain feature of the 1412th range cell in the measured data image domain of this application embodiment. The higher peaks in the figure are strong target scattering points, and the signals occupying a certain width around them are interference. Figure 4 This is the time-frequency domain feature of the 1412th distance cell in the image domain in this embodiment of the application, where the line parallel to the azimuth Doppler domain corresponds to... Figure 3 The sharp peaks in the middle, the sloping lines correspond to Figure 3 Interference in.

[0094] Step 1: Calculate the detection threshold Th along the range direction on the imaging matrix. The mean and standard deviation of the 1412th range cell are 7.54 and 10.84, respectively. Set the detection threshold Th to 7.54 + 2 × 10.84 = 29.22. Calculate the set G = [t1, t2, t3, ..., t] of the sampling points in each range cell that exceed the detection threshold. n ].

[0095] Step 2: The number of azimuth sampling points is 16384, and the decision threshold Thr is 16 (0.1% of the 16384 azimuth sampling points). Sampling point intervals higher than the decision threshold of 16 are considered interference signals, and the interval G = [t1, t2, t3, ..., t n If the value is not higher than the decision threshold, it indicates the presence of a strong scattering point target rather than interference, and we directly jump back to step 1;

[0096] Step 3: The average value and standard deviation of the interference signals in the interference signal set are 24.34 and 32.76, respectively. The search threshold is set to 122.62 = 24.34 + 3 × 32.76. The search is performed on the peak value 430.078 that is greater than the search threshold, and the position of the peak value 7032 is recorded. At the same time, the search range is [7016, 7048] of the range cells. If 16 range cells exceed the decision threshold and the peak value is less than the search threshold, then the peak value 430.078 is considered to be a strong scattering point target that overlaps with the interference. The peak value 430.078 and the position [7016, 7048] of this point and the surrounding points that are greater than the search threshold are recorded, and they are removed from the interference signal set G. r =[t1,t2,t3...,t r After removing the strong scattering points, the interval G is obtained. l =[t1,t2,t3...,t l ];

[0097] Step 4: Roughly estimate the degree θ0 of the rotation operation, perform FFT operation on the interval where strong scattering points are removed, and calculate the difference between the highest and lowest frequencies of its azimuth spectrum Δf = 1400.54 Hz. Then the slope k = -4488.58 Hz / s, where PRF = 3535 Hz.

[0098] The order θ0 of the FRFT operation satisfies:

[0099]

[0100] Step 5: Based on the coarse estimation result, use the binary search method to finely estimate the actual degree θ. When the interference interval is rotated by θ = 8.640°, the search stops when the length of the peak value in the transform domain and the surrounding points exceeding the transform domain search threshold of 122.62 is less than 16. Figure 5This is the change domain α feature of the 1412th range cell in the image domain after rotation by θ in this embodiment of the application. Several higher peaks in the figure are interferences, while the strong target scattering points have been removed in step 3. Figure 6 This is the spectral feature of the change domain α-change domain β after rotating the 1412th distance unit in the image domain by θ in the embodiments of this application, wherein the line parallel to the change domain β corresponds to Figure 5 The peak in the middle.

[0101] Step 6: Apply the interference signal set G from step 2 r =[t1,t2,t3...,t r Perform a rotation operation;

[0102] Step 7: Perform notch filtering on the rotated signal. The notch threshold is 27.79 = 6.80 + 3 × 9.76, where 6.80 and 9.76 are the mean and standard deviation of the signal in the variation domain, respectively. Figure 7 This is the result of performing notch filtering on the 1412th distance cell in the image domain in the variation domain α in the embodiments of this application;

[0103] Step 8: Rotate the rotated signal in the reverse direction by 8.64°, and reconstruct the previously removed strong scattering point targets back into the recovered range cell signal. Figure 8 In this embodiment of the application, the 1412th distance unit in the image domain is rotated by -θ in the change domain and then restored. Figure 3 Temporal characteristics of the scattering point from a medium-intensity target. Figure 9 This is the time-frequency domain feature of the 1412th range cell in the image domain after interference suppression in the embodiments of this application, wherein the line parallel to the azimuth Doppler domain corresponds to... Figure 3 and Figure 7 The peak in the middle, and Figure 10a This is the result of the measured data image before interference suppression processing using the method of this application. The white area on the left represents the interference. Figure 10b The image is the result of applying interference suppression to all distance cells using the measured data image of the method in this application.

[0104] Compared with the prior art, the embodiments of this application have the following beneficial effects:

[0105] First, the interference is detected in the azimuth and time domain and separated from the strong scattering point target.

[0106] Second, by performing a rotation operation, the original interference from the wide-pulse occupation is concentrated in a narrower position, and high-power interference is quickly suppressed by filtering.

[0107] Third, compared with the traditional notch filter method, the distortion of the recovered image can be minimized. Compared with the traditional time-frequency notch filter method, which directly performs short-time Fourier transform to calculate eigenvalues ​​row by row, this invention greatly reduces the amount of computation.

[0108] The following provides a possible implementation of an image domain azimuth radio frequency interference suppression device, which performs the various steps and corresponding technical effects of the image domain azimuth radio frequency interference suppression method shown in the above embodiments and possible implementations. The device includes:

[0109] The differentiation module is used to differentiate the imaging matrix carrying interference signals according to the detection threshold to obtain a set of sampling point intervals;

[0110] The extraction module is used to extract the set of interference signals from the set of sampling point intervals based on the decision threshold;

[0111] The elimination module is used to eliminate strong scattering point targets that overlap with the interference signals from the set of interference signals according to the search threshold, so as to obtain the interval of strong scattering points to be eliminated.

[0112] The coarse estimation module is used to estimate the coarse degree of the interval after removing strong scattering points;

[0113] The refinement module is used to refine the coarsely estimated degree to obtain the actual degree.

[0114] The completion module is used to perform rotation, notch filtering, and reverse rotation on the set of sampling point intervals based on the actual degree, thereby completing the set of sampling point intervals.

[0115] This preferred embodiment provides a computer device that can implement the steps of any embodiment of the image domain azimuth radio frequency interference suppression method provided in this application. Therefore, it can achieve the beneficial effects of the image domain azimuth radio frequency interference suppression method provided in this application. For details, please refer to the previous embodiments, which will not be repeated here.

[0116] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by instructions, or by instructions controlling related hardware. These instructions can be stored in a computer-readable storage medium and loaded and executed by a processor. Therefore, embodiments of this application provide a storage medium storing multiple instructions that can be loaded by a processor to execute the steps of any embodiment of the image domain azimuth radio frequency interference suppression method provided in this application.

[0117] The storage medium may include: read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0118] Since the instructions stored in the storage medium can execute the steps in any of the image domain azimuth radio frequency interference suppression method embodiments provided in this application, the beneficial effects that any of the image domain azimuth radio frequency interference suppression methods provided in this application can achieve can be realized. For details, please refer to the previous embodiments, which will not be repeated here.

[0119] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for suppressing azimuth radio frequency interference in the image domain, characterized in that, include: The set of sampling point intervals is obtained by distinguishing the imaging matrix carrying interference signals according to the detection threshold; The set of interference signals is extracted from the set of sampling point intervals based on the decision threshold; Based on the search threshold, strong scattering point targets that overlap with the interference signals are removed from the set of interference signals to obtain the interval for removing strong scattering points; Estimate the coarse degree of the interval where strong scattering points are removed; The coarsely estimated degree is refined to obtain the actual degree. The sampling point interval set is rotated, notch filtered, and rotated in reverse according to the actual degree to complete the sampling point interval set.

2. The image domain azimuth radio frequency interference suppression method as described in claim 1, characterized in that, The imaging matrix carrying interference signals includes range cells, and the step of distinguishing the imaging matrix carrying interference signals according to a detection threshold to obtain a set of sampling point intervals includes: Calculate the average value μ and standard deviation σ of the range cells for the imaging matrix carrying the interference signal; The detection threshold Th is obtained by using the mean μ and standard deviation σ according to Th = μ + 2σ; The sampling point interval set is obtained by statistically analyzing the distance units that are higher than the detection threshold.

3. The image domain azimuth radio frequency interference suppression method as described in claim 1, characterized in that, The imaging matrix carrying the interference signal further includes azimuth sampling points, and the step of extracting the interference signal set from the sampling point interval set according to a decision threshold includes: Set 0.1% of the number of the azimuth sampling points as the decision threshold; Within the set of sampling point intervals, signals above the decision threshold are extracted as interference signals to obtain a set of interference signals.

4. The image domain azimuth radio frequency interference suppression method as described in claim 1, characterized in that, The step of removing strong scattering point targets that overlap with the interference signals from the set of interference signals according to a search threshold to obtain the interval for removing strong scattering points includes: Calculate the average value μ of the interference signals in the set of interference signals. e and standard deviation σ e ; Based on the average value μ e and standard deviation σ e According to Ths = μ e +3σ e Obtain the search threshold Ths; Search for peak values ​​greater than the search threshold Ths, and obtain the peak position ma of the peak value; Based on the peak position ma and the decision threshold Thr, a distance cell with a search interval of [ma-Thr, ma+Thr] is found. If the number of distance cells exceeds the decision threshold and the peak value is less than the search threshold, the peak value is discarded as a strong scattering point target that overlaps with the interference signal, thus obtaining the interval for discarding strong scattering points.

5. The image domain azimuth radio frequency interference suppression method as described in claim 1, characterized in that, The step of estimating the coarse degree of the region where strong scattering points are removed includes: Perform a Fast Fourier Transform (FFT) on the interval where strong scattering points are removed, calculate the difference Δf between the highest and lowest frequencies of the azimuth spectrum, and combine this with the pulse repetition frequency (PRF) and the number of interfering signals (r) to... Obtain the slope k of the interval signal; Combining the slope k of the interval signal, the coarse estimate θ0 is obtained by using θ0 = (90° - arctan(k)) - m·180°, where m is an integer and the range of the coarse estimate θ0 is [-90°, 90°].

6. The image domain azimuth radio frequency interference suppression method as described in claim 1, characterized in that, The step of refining the coarsely estimated degree to obtain the actual degree includes: Starting from a coarsely estimated degree, the set of interference signals is rotated with a search step size of 0.001°; The actual degree is obtained when the peak value exceeds the search threshold and the number of distance cells is less than the decision threshold.

7. The image domain azimuth radio frequency interference suppression method as described in claim 1, characterized in that, The steps of performing rotation, notch filtering, and reverse rotation on the set of sampling point intervals based on the actual degrees to complete the set of sampling point intervals include: A rotation operation is performed on the set of sampling point intervals, wherein the rotation operation is as follows: Notch filtering is applied to the rotated set of sampling point intervals based on a notch threshold, where the notch threshold is Thn = μ. n +3σ n μ n σ is the average value of the rotated set of sampling point intervals. n The standard deviation of the rotated set of sampling point intervals; A reverse rotation operation is performed on the set of sampling point intervals after notch filtering to complete the set of sampling point intervals. The reverse rotation operation is as follows: Where n is the number of distance cells, PRF is the pulse repetition frequency, G is the variation function, θ is the actual degree, α is the independent variable in the domain of variation, and t is the distance cell.

8. An image domain azimuth radio frequency interference suppression device, characterized in that, The device includes: The differentiation module is used to differentiate the imaging matrix carrying interference signals according to the detection threshold to obtain a set of sampling point intervals; The extraction module is used to extract the set of interference signals from the set of sampling point intervals according to the decision threshold; The elimination module is used to eliminate strong scattering point targets that overlap with the interference signals from the set of interference signals according to the search threshold, so as to obtain the interval of strong scattering points to be eliminated. A coarse estimation module is used to estimate the coarse degree of the interval where strong scattering points are removed; The refinement module is used to refine the coarsely estimated degree to obtain the actual degree. The completion module is used to perform rotation, notch filtering, and reverse rotation on the set of sampling point intervals based on the actual degree, thereby completing the set of sampling point intervals.

9. A computer device, characterized in that, The computer device includes a processor and a memory, the memory storing a computer program, which is loaded and executed by the processor to implement the image domain azimuth radio frequency interference suppression method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which is loaded and executed by a processor to implement the image domain azimuth radio frequency interference suppression method as described in any one of claims 1-7.

Images