An interference suppression method based on distance-azimuth two-dimensional interception processing

Abstract

The application discloses a kind of interference suppression methods based on distance-azimuth two-dimensional intercept processing, comprising: the distance-azimuth two-dimensional intercept of whole SLC image containing interference is carried out, and the sub-image after intercepting is obtained;Wherein in the distance dimension intercept, on the basis of the preset distance dimension intercept point number, protection unit is set;Along distance dimension, Fourier transform is carried out to each sub-image, and the two-dimensional distance spectrum of sub-image is obtained and is detected outlying point, and the two-dimensional interference mask of sub-image is constructed based on outlying point;Two-dimensional interference mask is used to carry out frequency domain wave trap of sub-image, and two-dimensional interference mask and the two-dimensional distance spectrum of sub-image are multiplied with point, so that the frequency point where there is interference component is disposed zero, then the sub-image distance spectrum after interference suppression processing is obtained;Along distance dimension, inverse Fourier transform is done to the sub-image distance spectrum, and the sub-image after interference suppression is obtained;Based on the sub-image after interference suppression, the whole SLC image after interference suppression is constructed.

Description

Technical Field

[0001] The present invention relates to the field of radar signal processing, and in particular to an interference suppression method based on range-azimuth two-dimensional interception processing. Background Art

[0002] Radar remote sensing satellites can acquire high-resolution two-dimensional images around the clock, in all weather conditions. They offer unique advantages for both military and civilian applications and are a crucial component of my country's high-resolution Earth observation system. However, radar remote sensing satellites are highly susceptible to interference from other electromagnetic radiation sources in the same frequency band. Interference signals can create obscuring artifacts in imaging results, severely impacting image quality and potentially leading to missed targets and false alarms, significantly impacting the reliability of subsequent qualitative interpretation in remote sensing applications.

[0003] Many strategies have been proposed to mitigate both narrowband and broadband interference, but these methods are not necessarily applicable to complex interference scenarios where multiple signals with varying characteristics exist within the same scene. Analyzing measured data reveals that in complex interference scenarios, narrowband and broadband interference can coexist. Treating these separately is time-consuming and computationally expensive. Currently, there is no single method that can efficiently and quickly handle complex interference. Summary of the Invention

[0004] The purpose of the present invention is to provide an interference suppression method based on range-azimuth two-dimensional interception processing to overcome the problems existing in the prior art.

[0005] In order to achieve the above tasks, the present invention adopts the following technical solutions:

[0006] An interference suppression method based on range-azimuth two-dimensional interception processing, comprising:

[0007] Performing a range-azimuth two-dimensional interception on the entire SLC image containing interference to obtain a intercepted sub-image; wherein, when intercepting the range dimension, a protection unit is set based on a preset number of range dimension interception points to change the size of the sub-image when intercepted in the range dimension;

[0008] A Fourier transform is performed on each intercepted sub-image along the distance dimension to obtain a two-dimensional range spectrum of the sub-image. Then, outlier detection is performed on the two-dimensional range spectrum along the distance dimension. The detected outliers are the frequency points where interference components exist, and a two-dimensional interference mask of the sub-image is constructed based on the outliers.

[0009] The two-dimensional interference mask of the sub-image is used to perform frequency domain notching. The two-dimensional interference mask is then multiplied with the two-dimensional range spectrum of the sub-image to zero the frequencies of the interference components. The range spectrum of the sub-image after interference suppression is then obtained. The sub-image range spectrum is then inverse Fourier transformed along the range dimension to obtain the sub-image after interference suppression.

[0010] The entire SLC image after interference suppression is constructed based on the sub-image after interference suppression.

[0011] Furthermore, performing range-azimuth two-dimensional interception on the entire SLC image containing interference to obtain the intercepted sub-image includes:

[0012] For the entire SLC image x with interference of size Na×Nr img (t a ,t r ) to perform range-azimuth two-dimensional interception, where N r 、N a Respectively represent the number of sampling points of the SLC image in the distance dimension and the azimuth dimension, t a Indicates the azimuth sampling time, t r Indicates the distance sampling time, and sets the number of protection units in the distance dimension to N pro The number of interception points of the sub-image in the azimuth dimension is M, and the number of interception points of the sub-image in the distance dimension is N; the distance-azimuth two-dimensional interception is to perform sub-image interception operations along the distance dimension and the azimuth dimension on the SLC image, wherein setting the distance protection unit means taking N more points on both sides when intercepting in the distance dimension. pro units, that is, the number of interception points in the distance dimension between the first sub-image and the last sub-image is (N+N pro ), the distance dimension interception points of the remaining sub-images are (N+2*N pro ).

[0013] Furthermore, the azimuth-dimensional rectangular window function is used and distance-dimensional rectangular window function Perform distance-azimuth two-dimensional interception; the i-th sub-image x after interception sub_i (t a ,t r ),i=1,…,N a N r The mathematical expression of / MN is:

[0014]

[0015] Among them, the expression of the azimuth-dimensional rectangular window function is:

[0016]

[0017] The expression of the distance-dimensional rectangular window function is:

[0018]

[0019] After the distance-azimuth two-dimensional interception, we get (N a N r / MN-2*N a / M) of size M×(N+2*N pro ) and 2*N a / M of size M×(N+N pro ) xsub_i ( ta,tr ).

[0020] Furthermore, the pulse-by-pulse outlier detection on the two-dimensional range spectrum along the range dimension includes:

[0021] The judgment formula for outliers is:

[0022]

[0023] Where, Represents the sampling time in azimuth Distance frequency The two-dimensional distance spectrum of the sub-image when The energy value, Represents the two-dimensional distance spectrum X of the sub-image sub_i (t a ,f r ) in the tth a1 The spectrum of all distance frequencies corresponding to the azimuth sampling time, median represents the median operation, and c is a constant;

[0024] When the above formula is established, are outliers, that is, frequencies where interference may occur.

[0025] Furthermore, the constructing of a two-dimensional interference mask of a sub-image based on outliers includes:

[0026] After outlier detection along the distance dimension at all azimuth sampling times of the two-dimensional range spectrum of the sub-image, a two-dimensional interference mask of the sub-image is constructed. sub_i ; The azimuth sampling time Distance frequency The interference mask value at The calculation formula is:

[0027]

[0028] in, is the mask indicator, Indicates the sampling time in azimuth The two-dimensional range spectrum corresponding to all range frequencies.

[0029] Furthermore, the sub-image distance spectrum after the interference suppression process is specifically expressed as:

[0030] Sub-image distance spectrum X sub_i_after (t a ,f r ) is calculated as:

[0031] X sub_i_after (t a ,f r )=X sub_i (t a ,f r ).*(1-mask sub_i ).

[0032] Furthermore, constructing the entire SLC image after interference suppression based on the sub-image after interference suppression includes:

[0033] Sub-image x after interference suppression sub_i_after (t a ,t r ) cuts off the protection unit, that is, compares the distance-azimuth two-dimensional interception, and ( N a N r / MN - 2 * N a / M ) of size M×(N+2*N pro ) and the interference suppressed sub-image of ( 2 * N a / M ) of size M×(N+N pro ) The sub-image after interference suppression cuts off the corresponding protection unit along the distance dimension, and obtains (N a N r / MN) interference suppressed sub-images x' of size M×N sub_i_after (t a ,t r ); then the sub-images are reassembled in the order of interception to obtain the entire SLC image after interference suppression.

[0034] A terminal device includes a processor, a memory, and a computer program stored in the memory; when the processor executes the computer program, the interference suppression method based on range-azimuth two-dimensional interception processing is implemented.

[0035] A computer-readable storage medium stores a computer program; when the computer program is executed by a processor, the interference suppression method based on range-azimuth two-dimensional interception processing is implemented.

[0036] Compared with the prior art, the present invention has the following technical features:

[0037] Compared to previous image-domain interference suppression methods, this method performs sub-view decomposition of the entire SLC image along the range dimension, generating multiple sub-images. By analyzing the frequency characteristics of the useful and interfering signals within each sub-image at different distances and times, it can rapidly detect and suppress multiple interferences of varying energy intensities and sources within the same scene, restoring information about objects obscured by interference artifacts. This interference suppression method is highly efficient and easy to implement. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 1 is a schematic diagram of the implementation process of the method of the present invention;

[0039] Figure 2 is the original SLC image containing interference in the embodiment of the present invention, where the yellow area is the interference artifact;

[0040] Figure 3 In the embodiment of the present invention, Figure 2 After performing the range-azimuth two-dimensional interception process, some sub-images containing interference and the corresponding two-dimensional range spectrograms are obtained. Among them, (a), (c), and (e) are sub-images without interference, and (b), (d), and (f) are the two-dimensional range spectrograms corresponding to the sub-images containing interference;

[0041] Figure 4 is a sub-image after interference suppression processing according to an embodiment of the present invention, wherein: Figure 4 (a) is Figure 3 (a) corresponds to the interference suppression result, Figure 4 (b) is Figure 3 (c) corresponds to the interference suppression result, Figure 4 (c) is Figure 3 (e) The corresponding result after interference suppression;

[0042] Figure 5 This is the entire satellite-borne SLC image after interference suppression processing according to an embodiment of the present invention. DETAILED DESCRIPTION

[0043] The present invention provides an interference suppression method based on distance-azimuth two-dimensional interception processing. By performing distance-azimuth two-dimensional interception processing on the entire SLC image containing interference, the image is divided into multiple sub-image slices. The sub-image only reflects the image features within a certain distance time period. Similarly, the distance spectrum of the sub-image also reflects the local frequency characteristics within this distance time period. In the distance spectrum of this sub-image, the energy of the interference signal is more concentrated. The energy outliers in the sub-image distance spectrum are detected in combination with the outlier, and a zeroing operation is performed. Then, an inverse Fourier transform (IFFT) is performed along the distance dimension to obtain the sub-image after interference suppression. The sub-images after interference suppression processing are then spliced ​​in the original order to obtain the whole scene singular and plural images after interference suppression. The present invention enhances the characteristic differences between complex interference and useful signals by analyzing the distance frequency characteristics in different sub-images, thereby realizing effective interference detection and suppression. It is suitable for processing complex scenes where multiple interference signals coexist, and the processing is efficient and easy to implement in engineering. The specific implementation method of the present invention is as follows:

[0044] Step 1: For the entire SLC image x with interference of size Na×Nr img (t a ,t r ) to perform range-azimuth two-dimensional interception, where N r 、N a Respectively represent the number of sampling points of the SLC image in the distance dimension and the azimuth dimension, t a Indicates the azimuth sampling time, t r Indicates the distance sampling time, and sets the number of protection units in the distance dimension to N pro , the number of interception points of the sub-image in the orientation dimension is M, and the number of interception points of the sub-image in the distance dimension is N.

[0045] Range-azimuth two-dimensional interception is to intercept the sub-images of the SLC image along the range and azimuth dimensions. Setting the range protection unit means taking N more sub-images on both sides when intercepting in the range dimension. pro units, that is, the number of interception points in the distance dimension between the first sub-image and the last sub-image is (N+N pro ), the distance dimension interception points of the remaining sub-images are (N+2*N pro ); the azimuth-dimensional rectangular window function can be used and distance-dimensional rectangular window function Represents a two-dimensional interception of distance and orientation; the i-th sub-image x sub_i (t a ,t r ),i=1,…,N a N r The mathematical expression of / MN is:

[0046]

[0047] Among them, the expression of the azimuth-dimensional rectangular window function is:

[0048]

[0049] Because a protection unit is set in the distance dimension, the expression of the distance dimension rectangular window function is divided into three cases:

[0050]

[0051] After the distance-azimuth two-dimensional interception, we get (N a N r / MN-2*N a / M) of size M×(N+2*N pro ) and 2*N a / M of size M×(N+N pro ) xsub_i ( ta,tr ).

[0052] Step 2: For each sub-image x sub_i (t a ,t r ) Perform Fourier transform along the distance dimension to obtain the two-dimensional distance spectrum X of the sub-image sub_i (t a ,f r ); Then the two-dimensional distance spectrum X sub_i (t a ,f r ) Detect outliers pulse by pulse along the distance dimension. The detected outliers are the frequency points where interference components exist, and construct a two-dimensional interference mask of the sub-image based on the outliers. sub_i .

[0053] The calculation formula for Fourier transform in the distance dimension is:

[0054]

[0055] Among them, f r represents the distance frequency, e represents the natural constant, and j is the imaginary unit.

[0056] Then, the two-dimensional range spectrum is pulse-by-pulse detected along the range dimension. The detected outliers are the frequency points where interference components exist. The judgment formula for outliers is:

[0057]

[0058] Where, Represents the sampling time in azimuth Distance frequency The two-dimensional distance spectrum of the sub-image when The energy value, Represents the two-dimensional distance spectrum X of the sub-image sub_i (t a ,f r ) The spectrum of all distance frequencies corresponding to the azimuth sampling time, median represents the median operation, and c is a constant; in this embodiment, the empirical value c=1.4826 is used.

[0059] When the above formula is established, are outliers, that is, frequencies where interference may occur.

[0060] After outlier detection along the distance dimension at all azimuth sampling times of the two-dimensional range spectrum of the sub-image, a two-dimensional interference mask of the sub-image is constructed. sub_i ; The azimuth sampling time Distance frequency The interference mask value at The calculation formula is:

[0061]

[0062] in, is the mask indicator, Indicates the sampling time in azimuth The two-dimensional range spectrum corresponding to all range frequencies.

[0063] Step 3: Use the two-dimensional interference mask of the sub-image sub_i Perform frequency domain notching and separate the two-dimensional interference mask masksub_i from the two-dimensional distance spectrum X of the sub-image sub_i (t a ,f r ) to perform a point multiplication operation to make the frequency points with interference components zero, and then obtain the sub-image distance spectrum X after interference suppression processing sub_i_after (t a ,f r );For the sub-image distance spectrum X sub_i_after (t a ,f r ) Perform inverse Fourier transform along the distance dimension to obtain the interference suppressed sub-image x sub_i_after (t a ,f r ).

[0064] Among them, the sub-image distance spectrum X sub_i_after (t a ,f r ) is calculated as:

[0065] Xsub_i_after (t a ,f r )=X sub_i (t a ,f r ).*(1-mask sub_i );

[0066] Then the sub-image distance spectrum X after interference suppression is i_after (t a ,f r ) and perform inverse Fourier transform along the distance dimension to obtain ( N a N r / MN - 2*N a / M ) of size M×(N+2*N pro )'s interference suppressed sub-image and ( 2*N a / M ) of size M×(N+N pro ) after interference suppression.

[0067] The formula for inverse distance dimension transformation is:

[0068]

[0069] Step 4: Sub-image x after interference suppression sub_i_after (t a ,t r ) to remove the protection unit, that is, compare step 1 with ( N a N r / MN - 2 * N a / M ) of size M×(N+2*N pro ) and the interference suppressed sub-image of ( 2 * N a / M ) of size M×(N+N pro ) The sub-image after interference suppression cuts off the corresponding protection unit along the distance dimension, and obtains (N a N r / MN) interference suppressed sub-images x' of size M×N sub_i_after (t a,t r ); then, the sub-images are reassembled in the order of interception in step 1 to obtain the entire SLC image after interference suppression.

[0070] Example:

[0071] In one embodiment of the present invention, see Figures 2 to 4 , set distance protection unit N pro = 10, the number of interception points in the azimuth dimension is M = 500, the number of interception points in the distance dimension is N = 500, and the interference-containing SLC image x(t a ,t r ) performs distance-azimuth two-dimensional interception processing to obtain 16 sub-images of size 500×510 and 352 sub-images of size 500×520 x sub_i (t a ,t r ) ， Where i = 1,…,368; finally, after interference suppression, 358 sub-images x' of size 500×500 are obtained sub_i_after (t a ,t r ); then reassemble the sub-images according to the slicing order in step 1 to obtain the SLC image after interference suppression, such as Figure 5 shown.

[0072] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. An interference suppression method based on range-azimuth two-dimensional interception processing, characterized in that: include: Perform range-azimuth two-dimensional interception on the entire SLC image containing interference to obtain the intercepted sub-image; When performing distance dimension interception, a protection unit is set based on a preset number of distance dimension interception points to change the size of the sub-image when intercepted in the distance dimension; A Fourier transform is performed on each intercepted sub-image along the distance dimension to obtain a two-dimensional range spectrum of the sub-image. Then, outlier detection is performed on the two-dimensional range spectrum along the distance dimension. The detected outliers are the frequency points where interference components exist, and a two-dimensional interference mask of the sub-image is constructed based on the outliers. The two-dimensional interference mask of the sub-image is used to perform frequency domain notching. The two-dimensional interference mask is then multiplied with the two-dimensional range spectrum of the sub-image to zero the frequencies of the interference components. The range spectrum of the sub-image after interference suppression is then obtained. The sub-image range spectrum is then inverse Fourier transformed along the range dimension to obtain the sub-image after interference suppression. constructing the entire SLC image after interference suppression based on the sub-image after interference suppression; Perform range-azimuth two-dimensional interception on the entire SLC image containing interference to obtain intercepted sub-images, including: For size The entire SLC image with interference Perform a range-azimuth two-dimensional intercept, where Respectively represent the number of sampling points of the SLC image in the distance dimension and the azimuth dimension, represents the azimuth sampling time, Indicates the distance sampling time, and sets the number of protection units in the distance dimension to , the number of interception points of the sub-image in the orientation dimension is , the number of interception points of the distance dimension of the sub-image is ; Range-azimuth two-dimensional interception is to intercept the sub-image of the SLC image along the range dimension and the azimuth dimension, wherein setting the distance protection unit means taking multiple sub-images on both sides when intercepting in the range dimension. units, that is, the number of interception points in the distance dimension between the first sub-image and the last sub-image is , the distance dimension interception points of the remaining sub-images are .

2. The interference suppression method based on range-azimuth two-dimensional interception processing according to claim 1, characterized in that: Use azimuth-dimensional rectangular window function and distance-dimensional rectangular window function Perform distance-azimuth two-dimensional interception; Zhang Zi Image The mathematical expression is: ； Among them, the expression of the azimuth-dimensional rectangular window function is: ； The expression of the distance-dimensional rectangular window function is: ； After two-dimensional interception of distance and azimuth, we get The size is as well as The size is Sub-image .

3. The interference suppression method based on range-azimuth two-dimensional interception processing according to claim 1, characterized in that: The step of detecting outliers pulse by pulse on the two-dimensional range spectrum along the range dimension includes: The judgment formula for outliers is: ； Where, Represents the sampling time in azimuth , distance frequency The two-dimensional distance spectrum of the sub-image when The energy value, Representing the 2D distance spectrum of the sub-image In the The spectrum of all distance frequencies corresponding to the azimuth sampling time, Represents the median operation, is a constant; When the above formula is established, are outliers, that is, frequencies where interference may occur.

4. The interference suppression method based on range-azimuth two-dimensional interception processing according to claim 3, characterized in that: The two-dimensional interference mask of the sub-image constructed based on the outliers includes: After outlier detection along the distance dimension at all azimuth sampling times of the two-dimensional range spectrum of the sub-image, a two-dimensional interference mask of the sub-image is constructed. ; The azimuth sampling time , distance frequency The interference mask value at The calculation formula is: ； in, is the mask indicator, Indicates the sampling time in azimuth The two-dimensional range spectrum corresponding to all range frequencies.

5. The interference suppression method based on range-azimuth two-dimensional interception processing according to claim 4, characterized in that: The sub-image distance spectrum after the interference suppression process is specifically expressed as: Sub-image distance spectrum The calculation formula is: 。 6. The interference suppression method based on range-azimuth two-dimensional interception processing according to claim 5, characterized in that: The constructing the entire SLC image after interference suppression based on the sub-image after interference suppression includes: Sub-image after interference suppression Cut off the protection unit, that is, compare the distance-azimuth two-dimensional interception, The size is The interference suppressed sub-image and The size is The sub-image after interference suppression cuts off the corresponding protection unit along the distance dimension, and obtains The size is The interference suppressed sub-image ; Then the sub-images are reassembled in the order of interception to obtain the entire SLC image after interference suppression.

7. A terminal device comprising a processor, a memory, and a computer program stored in the memory; characterized in that: When the processor executes the computer program, the interference suppression method based on range-azimuth two-dimensional interception processing according to any one of claims 1 to 6 is implemented.

8. A computer-readable storage medium storing a computer program; wherein: When the computer program is executed by a processor, the interference suppression method based on range-azimuth two-dimensional interception processing according to any one of claims 1 to 6 is implemented.

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