An image domain based near-field anomaly scattering filtering method

Abstract

This invention relates to the field of RCS testing technology, specifically to an image-domain-based near-field anomalous scattering filtering method. The method first obtains a raw near-field image by near-field imaging of the acquired near-field swept data. Second, based on set anomalous scattering judgment conditions, the anomalous scattering centers are identified and extracted. Then, using a point target as a reference object, the scattering field distribution in the determined filtering area is simulated and reconstructed to generate a new near-field image. Finally, it is determined whether the new near-field image meets the anomalous scattering judgment conditions. If not, a filtered near-field image is generated. By identifying and removing scattering centers that do not belong to the test target from the two-dimensional image generated by the near-field imaging, near-field clutter suppression and higher-precision radar cross section testing are achieved.

Description

Technical Field

[0001] This invention relates to the field of RCS testing technology, and more specifically, to a near-field anomalous scattering filtering method based on the image domain. Background Technology

[0002] Stealth and anti-stealth technologies are important areas of modern electronic warfare. Their core indicator, radar cross section (RCS), is one of the most basic parameters for evaluating the scattering characteristics of a target and an important characteristic parameter reflecting the electromagnetic properties of a target.

[0003] Radar cross section (RCS) testing is the most direct and effective means of obtaining the radar scattering characteristics of weapons and equipment and studying their stealth performance. Depending on the testing method, testing methods can be divided into far-field testing, near-field testing, and compressed-field testing. Far-field testing is conducted outdoors, with stringent requirements for environmental factors (such as temperature, humidity, and climate conditions). Furthermore, to ensure the test target meets far-field conditions, a very large distance is required between the test radar and the target, thus the site size is extremely large. Compact-field testing is indoor testing. Compared to outdoor far-field testing, the site environment is stable and clean, but the target must be completely within the quiet zone to obtain accurate test results. However, the maximum quiet zone size that can be generated is limited by the size of the anechoic chamber, so the quiet zone size in a compact-field test is typically around a few meters. Near-field testing, compared to compact-field testing, can generate a larger quiet zone within the same site size. Compared to far-field testing, it requires less space and has a controllable site environment. Moreover, there are rigorous mathematical derivation formulas from near-field to far-field, therefore, near-field testing is increasingly becoming one of the key research directions.

[0004] However, in near-field testing, because the target meets the near-field conditions of the test radar, the test radar will receive more clutter interference compared to far-field and compact-field testing. This will significantly affect the reliability of the test results for test targets with low RCS. Summary of the Invention

[0005] This invention addresses the problem that existing near-field testing methods significantly affect the reliability of test results for targets with low RCS (Radar Cross Section). It proposes an image-domain-based near-field anomalous scattering filtering method. First, the acquired near-field swept data is used to create a near-field image. Second, based on predefined anomalous scattering criteria, anomalous scattering centers are identified and extracted. Then, using a point target as a reference, the scattering field distribution in the defined filtering area is simulated and reconstructed to generate a new near-field image. Finally, it is determined whether the new near-field image meets the anomalous scattering criteria. If not, a filtered near-field image is generated. By identifying and removing scattering centers that do not belong to the test target from the two-dimensional image generated by the near-field imaging, near-field clutter suppression and higher-precision radar cross section testing are achieved.

[0006] The specific implementation details of this invention are as follows:

[0007] A near-field anomalous scattering filtering method based on the image domain is disclosed. During the process of a support structure erecting an aircraft in the air, the following steps are taken: First, the acquired near-field swept data is used to create a raw near-field image. Second, based on predefined anomalous scattering criteria, it is determined whether an anomalous scattering center exists in a defined area to be filtered within the raw near-field image, and the identified anomalous scattering centers are extracted. Then, using a point target as a reference object, the scattering field distribution in the defined area to be filtered is simulated and reconstructed, and a new near-field image is generated based on the scattering field distribution. Finally, it is determined whether the new near-field image meets the anomalous scattering criteria; if not, a filtered near-field image is generated.

[0008] To better implement this invention, the image domain-based near-field anomalous scattering filtering method further includes the following steps:

[0009] Step S1: Obtain the raw near-field image by near-field imaging of the acquired near-field swept frequency data;

[0010] Step S2: Based on the set abnormal scattering determination conditions, determine whether there is an abnormal scattering center in the determined area of ​​the original near-field image; if so, extract the identified abnormal scattering center.

[0011] Step S3: Using the point target as a reference object, simulate and reconstruct the scattered field distribution in the defined area, and cancel the electromagnetic field distribution in the defined area with the scattered field distribution vector to obtain a new electromagnetic field distribution, and generate a new near-field image based on the new electromagnetic field distribution;

[0012] Step S4: Determine whether the new near-field image meets the anomalous scattering determination condition. If it does not meet the condition, generate the filtered near-field image. If it does meet the condition, repeat steps S2-S3 until the new near-field image does not meet the anomalous scattering determination condition, then generate the filtered near-field image.

[0013] To better realize the present invention, the specific operation of step S1 is as follows: calling the ISAR imaging algorithm to process the acquired near-field sweep data, and obtaining the original near-field imaging from the near-field sweep data after Fourier transform processing.

[0014] To better realize the present invention, the acquired near-field sweep data is further processed to include distance-compressed near-field sweep data, motion-compensated near-field sweep data, and rotation-compensated near-field sweep data.

[0015] To better realize the present invention, step S2 further includes the following steps:

[0016] Step S21: Determine the area to be filtered out based on the original near-field imaging and the actual physical position of the scaffold obtained;

[0017] Step S22: Adjust the acceptable dynamic range of the image according to the actual needs of the experiment to determine the location of the scattering point, and combine it with the physical location of the aircraft under test to determine whether the location of the scattering point is on the target under test;

[0018] Step S23: Read the pixel information of the original near-field image and the corresponding scattering intensity value of the original near-field image, identify and extract the strongest scattering source of the region to be filtered;

[0019] Step S24: Compare the scattering intensity value of the strongest scattering source with the scattering intensity values ​​of the other scattering sources. If the scattering intensity value of the strongest scattering source is higher than that of the other scattering sources, it is determined that the scattering intensity exceeds the standard, and the strongest scattering source is output as an abnormal scattering center.

[0020] To better realize the present invention, further, the specific operation of determining the area to be filtered in step S21 is as follows: based on the minimum circular envelope radius r0 of the contact range between the fully covered support and the target projected on the horizontal plane, and the distance Δr from which the support scattering intensity decreases by 20dB from the support edge, the radius R of the area to be filtered is determined, and the area to be filtered is determined based on the radius R of the area to be filtered.

[0021] To better implement the present invention, the specific operation of step S24 is as follows: compare the scattering intensity value pmax of the strongest scattering source with the scattering intensity value p0 of the other scattering sources. If pmax-p0≥1dB, it is determined that the scattering intensity exceeds the standard, and the strongest scattering source is output as an abnormal scattering center.

[0022] To better realize the present invention, step S3 further includes the following steps:

[0023] Step S31: Using the point target as a reference object, the scattering field distribution of the region to be filtered is obtained by simulation reconstruction.

[0024] Step S32: Cancel the electromagnetic field distribution of the region to be filtered out and the scattered field distribution vector to obtain a new electromagnetic field distribution, and generate a new near-field image based on the new electromagnetic field distribution.

[0025] To better implement the present invention, the specific operation of step S4 is as follows: determine whether the new near-field image meets the abnormal scattering determination condition. If it does not meet the condition, generate the filtered near-field image. If it does meet the condition, repeat steps S2-S3 until no abnormal scattering center can be identified in the area to be filtered, and pmax-p0 < 1dB. Then the filtering is completed, and the last filtered near-field image and the pixel information of the near-field image are output as the final result of the filtering.

[0026] The present invention has the following beneficial effects:

[0027] (1) This invention combines existing large-size near-field testing systems and indoor target setup methods, and achieves near-field clutter suppression by identifying and removing scattering centers that do not belong to the test target in the two-dimensional image generated by near-field imaging, thereby obtaining the objective radar scattering characteristics of the target under test.

[0028] (2) The present invention can effectively filter out near-field clutter that cannot be completely filtered out by existing cancellation techniques, and obtain test accuracy comparable to that of far-field and compact field tests. At the same time, compared with far-field and near-field, the requirements for the scattering intensity of the mounting device are more relaxed, thus leaving a larger design margin for the mounting device, enabling radar cross section testing of larger size targets, larger weight targets, more attitude requirements, and higher accuracy requirements. Attached Figure Description

[0029] Figure 1 This is a schematic diagram illustrating the implementation process of the filtration method provided by the present invention.

[0030] Figure 2 This is a schematic diagram of the abnormal scattering center identification and determination process provided by the present invention. Detailed Implementation

[0031] To more clearly illustrate the technical solutions of the embodiments of the present invention, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments, and therefore should not be regarded as a limitation on the scope of protection. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0032] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "set up," "connected," and "linked" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0033] Example 1:

[0034] This embodiment proposes an image-domain-based near-field anomalous scattering filtering method. During the process of the support structure erecting the aircraft in the air, the method first obtains a raw near-field image by near-field imaging of the collected near-field swept frequency data. Then, based on the set anomalous scattering judgment conditions, it is determined whether there are anomalous scattering centers in the original near-field image within a defined area to be filtered, and the identified anomalous scattering centers are extracted. Next, the scattering field distribution in the defined area to be filtered is simulated and reconstructed using a point target as a reference object, and a new near-field image is generated based on the scattering field distribution. Finally, it is determined whether the new near-field image meets the anomalous scattering judgment conditions. If it does not meet the conditions, a filtered near-field image is generated.

[0035] Furthermore, the image-domain-based near-field anomalous scattering filtering method specifically includes the following steps:

[0036] Step S1: Obtain the raw near-field image by near-field imaging of the acquired near-field swept frequency data.

[0037] The specific operation of step S1 is as follows: call the ISAR imaging algorithm to process the acquired near-field sweep data, and obtain the original near-field image from the near-field sweep data after Fourier transform processing.

[0038] The acquired near-field sweep data is processed and includes range-compressed near-field sweep data, motion-compensated near-field sweep data, and rotation-compensated near-field sweep data.

[0039] Step S2: Based on the set abnormal scattering determination conditions, determine whether there is an abnormal scattering center in the determined area of ​​the original near-field image. If there is, extract the identified abnormal scattering center.

[0040] Step S2 specifically includes the following steps:

[0041] Step S21: Determine the area to be filtered out based on the original near-field imaging and the actual physical position of the scaffold.

[0042] Further, the specific operation of determining the area to be filtered in step S21 is as follows: based on the radius r0 of the minimum circular envelope of the contact range between the fully covered support and the target projected on the horizontal plane and the distance Δr from which the support scattering intensity decreases by 20dB from the edge of the support, the radius R of the area to be filtered is determined, and the area to be filtered is determined based on the radius R of the area to be filtered.

[0043] Step S22: Adjust the acceptable dynamic range of the image according to the actual needs of the experiment to determine the location of the scattering point, and combine it with the physical location of the aircraft under test to determine whether the location of the scattering point is on the target under test.

[0044] Step S23: Read the pixel information of the original near-field image and the corresponding scattering intensity value of the original near-field image, and identify and extract the strongest scattering source of the region to be filtered.

[0045] Step S24: Compare the scattering intensity value of the strongest scattering source with the scattering intensity values ​​of the other scattering sources. If the scattering intensity value of the strongest scattering source is higher than that of the other scattering sources, it is determined that the scattering intensity exceeds the standard, and the strongest scattering source is output as an abnormal scattering center.

[0046] Further, the specific operation of step S24 is as follows: compare the scattering intensity value pmax of the strongest scattering source with the scattering intensity value p0 of the other scattering sources. If pmax-p0≥1dB, it is determined that the scattering intensity exceeds the standard, and the strongest scattering source is output as an abnormal scattering center.

[0047] Step S3: Using the point target as a reference object, simulate and reconstruct the scattering field distribution in the defined area, and cancel the electromagnetic field distribution in the defined area with the scattering field distribution vector to obtain a new electromagnetic field distribution, and generate a new near-field image based on the new electromagnetic field distribution.

[0048] Furthermore, step S3 specifically includes the following steps:

[0049] Step S31: Using the point target as a reference object, the scattering field distribution of the region to be filtered is obtained by simulation reconstruction.

[0050] Step S32: Cancel the electromagnetic field distribution of the region to be filtered out and the scattered field distribution vector to obtain a new electromagnetic field distribution, and generate a new near-field image based on the new electromagnetic field distribution.

[0051] Step S4: Determine whether the new near-field image meets the anomalous scattering determination condition. If it does not meet the condition, generate the filtered near-field image. If it does meet the condition, repeat steps S2-S3 until the new near-field image does not meet the anomalous scattering determination condition, then generate the filtered near-field image.

[0052] The specific operation of step S4 is as follows: determine whether the new near-field image meets the abnormal scattering judgment condition. If it does not meet the condition, generate the filtered near-field image. If it does meet the condition, repeat steps S2-S3 until no abnormal scattering center can be identified in the area to be filtered and pmax-p0 < 1dB. Then the filtering is completed, and the last filtered near-field image and the pixel information of the near-field image are output as the final result of the filtering.

[0053] Working principle: This embodiment first obtains the original near-field image by near-field imaging of the acquired near-field swept data; secondly, according to the set abnormal scattering judgment conditions, it determines whether there are abnormal scattering centers in the determined area to be filtered in the original near-field image and extracts the identified abnormal scattering centers; then, using the point target as a reference object, it simulates and reconstructs the scattering field distribution in the determined area to be filtered, and generates a new near-field image based on the scattering field distribution; finally, it determines whether the new near-field image meets the abnormal scattering judgment conditions. If it does not meet the conditions, a filtered near-field image is generated. By identifying and removing scattering centers that do not belong to the test target in the two-dimensional image generated by the near-field imaging, the suppression of near-field clutter and the radar cross section test with higher precision requirements are achieved.

[0054] Example 2:

[0055] This embodiment is based on the above embodiment 1, such as... Figure 1 , Figure 2 As shown, a specific embodiment will be described in detail.

[0056] This embodiment achieves near-field clutter suppression by performing near-field imaging on near-field swept frequency data and identifying and filtering out abnormal scattering sources in the image, thus restoring the true radar scattering characteristics of the target under test. Then, through inverse operations, the image is restored to swept frequency data for other forms of data processing and analysis. Finally, the processed swept frequency data undergoes near-field to far-field transformation to obtain the far-field radar scattering characteristics and RCS results of the target under test. This embodiment has been successfully applied to the near-field RCS test data processing and analysis of various manned / unmanned aerial vehicles, successfully realizing the identification, scattering model construction, and filtering of various types of mounting devices and fixtures in the image domain, obtaining overall RCS test results that conform to theoretical designs.

[0057] A near-field anomalous scattering filtering method based on the image domain includes five parts: near-field imaging, anomalous scattering center identification, scattering center scattering field simulation reconstruction, and scattering center filtering.

[0058] Specifically, this method includes the following steps:

[0059] Step 1: Perform near-field imaging on the acquired near-field swept data to obtain the raw near-field image.

[0060] Step 2: Based on the actual test site conditions, select the area where abnormal scattering identification and filtering are required. Generally, the selection of this area should take into account the site environment, objects other than the target being tested (such as installation equipment) in the darkroom.

[0061] Step 3, during the abnormal scattering identification and judgment process, the judgment criteria are formulated according to the actual filtering requirements. For example, the scattering intensity of the surface skin of an aircraft or the background scattering intensity of a dark room can be used as the judgment criteria.

[0062] Step 4: When the scattering center appears outside the physical size range of the target being measured or exceeds the standard within the physical range, after comparing with the theoretical design scheme to confirm that it is indeed abnormal, it is output as the abnormal scattering center.

[0063] Step 5: Extract the identified abnormal scattering centers and simulate their scattering field distribution within the selected area using the point target as a reference object.

[0064] Step 6: Perform vector cancellation on the electromagnetic field distribution in the region and the simulated scattering field distribution to obtain the filtered electromagnetic field distribution and generate a new near-field image.

[0065] Step 7: Repeat steps 2 to 6 for the new near-field image obtained in step 6 until the overall scattering intensity of the region no longer meets the abnormal scattering judgment criteria described in step 3, and generate the filtered near-field image.

[0066] Subsequently, inverse operations are performed based on the filtered near-field images to obtain the filtered near-field test results. Then, the far-field RCS results of the target are obtained through near-far field transformation for analysis of the scattering characteristics of the target.

[0067] This embodiment can effectively filter out near-field clutter that cannot be completely removed by background cancellation techniques, achieving test accuracy comparable to far-field and compact-field tests. Furthermore, compared to far-field and near-field tests, the proposed method has more lenient requirements on the scattering intensity of the mounting device, thus allowing for a greater design margin for the device. This enables radar cross section (RCS) testing of larger targets, heavier targets, targets with more attitude requirements, and targets with higher accuracy requirements, demonstrating significant application and promotion value in near-field RCS testing and data processing within the industry.

[0068] like Figure 1 and Figure 2 As shown, after the near-field receiving radar receives the frequency sweep signal scattered by the target under test, in the data processing process after the aircraft is erected in the air using a support to complete the near-field test, the near-field frequency sweep data is first imaged using the ISAR imaging algorithm to complete the near-field imaging.

[0069] The specific operation of the near-field ISAR imaging algorithm involved in this embodiment is as follows: the acquired near-field echo data is processed sequentially by distance compression, motion compensation, and rotation compensation, and then the near-field ISAR image is obtained by Fourier transform.

[0070] Then, based on the near-field imaging results and the actual physical location of the support, the radius R of the filtering area is selected;

[0071] R=r0+Δr

[0072] Where r0 represents the radius of the smallest circular envelope that can completely cover the contact area between the support and the target projected on the horizontal plane, and Δr represents the distance from which the scattering intensity of the support decreases by 20dB from the edge of the support. The basic position of the scattering point is determined by adjusting the acceptable dynamic range of the image according to actual needs, and combined with the physical position of the aircraft under test, it is determined whether the scattering point is on the target under test.

[0073] By reading the pixel information and corresponding scattering intensity values ​​of near-field imaging, the strongest scattering source in the region is identified and extracted. The scattering intensity value pmax of the identified strongest scattering source is compared with the scattering value p0 of its surroundings. When the scattering source value is 1dB higher than the surrounding scattering value, i.e. pmax-p0≥1dB, the scattering intensity is determined to be excessive and it is output as an abnormal scattering center.

[0074] The formula for calculating the scattered field distribution of a point source within a given range is as follows:

[0075] P(x,y,B,Δθ)=sinc[y(kmax-kmin) / 2]*sinc[xk0sin(Δθ / 2)];

[0076] x represents the polar coordinate transformation, x = rcosφ.

[0077] y represents polar coordinate transformation, y=rsinφ.

[0078] B represents bandwidth.

[0079] k max Indicates: k min =2f min / c,f min Minimum frequency, c is the speed of light.

[0080] k min Indicates: k max =2f max / c,f max Maximum frequency, c is the speed of light.

[0081] Δθ represents the target rotation angle in the imaging, where Δθ << 1.

[0082] The simulation and reconstruction of the scattering field of the anomalous scattering center are completed, and the field distribution of the selected filtering region is vector-canceled with the simulated and reconstructed scattering field of the anomalous scattering center to achieve one-time filtering.

[0083] The above steps are repeated until no abnormal scattering center pmax-p0 < 1dB can be identified in the selected filtering area. The filtering is then complete, and the near-field image after the last filtering and its pixel information are output as the final result of the filtering.

[0084] This embodiment is based on a near-field environment where clutter is more complex, and simple extraction and reconstruction of the scattering center cannot reproduce the true state of the target. Based on the strongest scattering point and its physical location, a point spread function centered on this point is established, and the scattering field distribution in its two-dimensional space is obtained. The scattering field distribution in the area to be determined is filtered and canceled using the scattering field distribution obtained by the point spread function from the original near-field imaging results. After extracting the scattering center through near-field imaging, anomaly identification of the scattering center is added, and the value of the scattering center in the image is processed, changing the image. Then, the image result is inversely processed to the data domain, realizing the joint operation of the data domain and the image domain.

[0085] The other parts of this embodiment are the same as those in Embodiment 1 above, so they will not be described again.

[0086] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Any simple modifications or equivalent changes made to the above embodiments based on the technical essence of the present invention shall fall within the protection scope of the present invention.

Claims

1. A near-field anomalous scattering filtering method based on the image domain, during the process of a support structure erecting an aircraft into the air; characterized in that, First, the acquired near-field swept data is used to obtain the original near-field image. Second, based on the set abnormal scattering judgment conditions, it is determined whether there are abnormal scattering centers in the determined area to be filtered in the original near-field image, and the identified abnormal scattering centers are extracted. Then, the scattering field distribution in the determined area to be filtered is simulated and reconstructed using the point target as a reference object, and a new near-field image is generated based on the scattering field distribution. Finally, it is determined whether the new near-field image meets the abnormal scattering judgment conditions. If it does not meet the conditions, a filtered near-field image is generated. The image-domain-based near-field anomalous scattering filtering method specifically includes the following steps: Step S1: Obtain the raw near-field image by near-field imaging of the acquired near-field swept frequency data; Step S2: Based on the set abnormal scattering judgment conditions, determine whether there is an abnormal scattering center in the determined area of ​​the original near-field image. If there is, extract the identified abnormal scattering center. Step S3: Using the point target as a reference object, simulate and reconstruct the scattered field distribution in the defined area, and cancel the electromagnetic field distribution in the defined area with the scattered field distribution vector to obtain a new electromagnetic field distribution, and generate a new near-field image based on the new electromagnetic field distribution; Step S4: Determine whether the new near-field image meets the anomalous scattering determination condition. If it does not meet the condition, generate the filtered near-field image. If it does meet the condition, repeat steps S2-S3 until the new near-field image does not meet the anomalous scattering determination condition, then generate the filtered near-field image.

2. The near-field anomalous scattering filtering method based on the image domain according to claim 1, characterized in that, The specific operation of step S1 is as follows: call the ISAR imaging algorithm to process the acquired near-field sweep data, and obtain the original near-field image from the near-field sweep data processed by the Fourier transform ISAR imaging algorithm.

3. The near-field anomalous scattering filtering method based on the image domain according to claim 2, characterized in that, The acquired near-field sweep data is processed and includes range-compressed near-field sweep data, motion-compensated near-field sweep data, and rotation-compensated near-field sweep data.

4. The near-field anomalous scattering filtering method based on the image domain according to claim 1, characterized in that, Step S2 specifically includes the following steps: Step S21: Determine the area to be filtered out based on the original near-field imaging and the actual physical position of the scaffold obtained; Step S22: Adjust the acceptable dynamic range of the image according to the actual needs of the experiment to determine the location of the scattering point, and combine it with the physical location of the aircraft under test to determine whether the location of the scattering point is on the target under test; Step S23: Read the pixel information of the original near-field image and the corresponding scattering intensity value of the original near-field image, identify and extract the strongest scattering source of the region to be filtered; Step S24: Compare the scattering intensity value of the strongest scattering source with the scattering intensity values ​​of the other scattering sources. If the scattering intensity value of the strongest scattering source is higher than that of the other scattering sources, it is determined that the scattering intensity exceeds the standard, and the strongest scattering source is output as an abnormal scattering center.

5. The near-field anomalous scattering filtering method based on the image domain according to claim 4, characterized in that, The specific operation of determining the area to be filtered in step S21 is as follows: Based on the minimum circular envelope radius r0 of the contact range between the fully covered support and the target projected on the horizontal plane, and the distance Δr from which the support scattering intensity decreases by 20dB from the support edge, the radius R of the area to be filtered is determined, and the area to be filtered is determined based on the radius R of the area to be filtered.

6. The near-field anomalous scattering filtering method based on the image domain according to claim 4, characterized in that, The specific operation of step S24 is as follows: compare the scattering intensity value pmax of the strongest scattering source with the scattering intensity value p0 of the other scattering sources. If pmax-p0≥1dB, it is determined that the scattering intensity exceeds the standard, and the strongest scattering source is output as an abnormal scattering center.

7. The near-field anomalous scattering filtering method based on the image domain according to claim 3, characterized in that, Step S3 specifically includes the following steps: Step S31: Using the point target as a reference object, simulate and reconstruct the scattering field distribution of the region to be filtered; Step S32: Cancel the electromagnetic field distribution of the region to be filtered out and the scattered field distribution vector to obtain a new electromagnetic field distribution, and generate a new near-field image based on the new electromagnetic field distribution.

8. The near-field anomalous scattering filtering method based on the image domain according to claim 6, characterized in that, The specific operation of step S4 is as follows: determine whether the new near-field image meets the abnormal scattering judgment condition. If it does not meet the condition, generate the filtered near-field image. If it does meet the condition, repeat steps S2-S3 until no abnormal scattering center can be identified in the area to be filtered and pmax-p0 < 1dB. Then the filtering is completed, and the last filtered near-field image and the pixel information of the near-field image are output as the final result of the filtering.

Images