Method for detecting interference from SAR (Synthetic Aperture Radar) single-view complex image

Abstract

The invention provides a method for detecting interference from an SAR (Synthetic Aperture Radar) single-view complex image. The method comprises the following steps: carrying out range Fourier transform on an SAR image to be processed; carrying out equalization processing on the range-direction frequency spectrum of the SAR image; dividing the range-direction frequency spectrum into a plurality of sub-bands at equal intervals; performing range inverse Fourier transform on each sub-band frequency spectrum to obtain a plurality of sub-band images; calculating the contrast ratio of each pixel in the sub-band domain; and comparing the contrast obtained by calculation with a threshold value, and if the contrast exceeds the threshold value, detecting the pixel as an interference pixel. According to the method, the intermittent sampling forwarding interference and the common unintentional interference can be effectively detected from the SAR image.

Description

Technical Field

[0001] The invention belongs to the technical field of radar signal processing, and in particular relates to a method for detecting interference from a SAR single-view complex image. Background Art

[0002] With its all-day, all-weather, high-resolution imaging capabilities, synthetic aperture radar (SAR) has become an indispensable observation payload for combat units such as satellites, missiles, and various aircraft. However, SAR also faces serious threats from electronic countermeasures: the enemy can interfere with SAR in a variety of ways, blinding SAR or producing unreal images, thereby weakening the role of SAR. The technologies for interfering with SAR mainly include passive and active. Among them, active interference poses a greater threat to SAR. Typical active interference includes: noise interference, frequency shift interference, sweep interference, convolution deception interference, intermittent sampling forwarding interference, scattered wave interference, motion modulation interference, etc. Among them, intermittent sampling forwarding interference requires fewer parameters to be detected, and the jammer is easy to implement. The above interferences all belong to the category of intentional interference. In addition to these intentional interferences, SAR also faces a lot of unintentional interference caused by spectrum sharing. The premise of suppressing these interferences is that the interference is detected in the SAR data. In recent years, scholars have conducted some research on the problem of SAR interference detection, but these research works are mainly aimed at unintentional interference, and there are few studies on the detection of intentional interference. Summary of the invention

[0003] The present invention proposes a method for detecting interference from a SAR single-view complex image, which can effectively detect intermittent sampling forwarding interference and common unintentional interference, and the detection result can be used for adaptive interference suppression.

[0004] The technical solution to achieve the purpose of the present invention is: a method for detecting interference from a SAR single-view complex image, comprising:

[0005] Step 1: Perform range Fourier transform on the SAR image to be processed to obtain the range spectrum matrix;

[0006] Step 2: Equalize the range spectrum of the SAR image;

[0007] Step 3: Divide the distance spectrum after equalization into multiple sub-bands at equal intervals;

[0008] Step 4: Perform inverse Fourier transform on each sub-band spectrum to obtain multiple sub-band images.

[0009] Step 5: Calculate the contrast of each pixel in the sub-band domain.

[0010] Step 6: Compare the calculated sub-band contrast of each pixel with the threshold. If the contrast is greater than the threshold, it is determined to be an interference pixel.

[0011] Preferably, the specific method of step 1 is:

[0012] The SAR single-view complex image is represented by a matrix I, and the image size is N a ×N r , perform distance to N on this matrix r Point Fourier transform is performed to obtain the distance spectrum matrix S.

[0013] Preferably, the specific method of performing equalization processing on the range spectrum of the SAR image in step 2 is:

[0014] The second dimension of the distance spectrum matrix S is multiplied by the inverse of the distance window function, so that the distance spectrum is a rectangular window. If there is oversampling in the distance, the invalid data outside the data bandwidth is set to 0. The data after equalization is recorded as S eq .

[0015] Preferably, in step 3, the range spectrum after equalization is divided into K sub-matrices at equal intervals within the range bandwidth, and the kth sub-matrix is ​​recorded as S eq,k .

[0016] Preferably, the sub-band contrast C[n,m] of pixel [n,m] is calculated, and the specific formula is:

[0017]

[0018] Where K is the total number of offspring images, I k [n,m] is the kth subband image.

[0019] Compared with the prior art, the present invention has the following significant advantages: the present invention can effectively distinguish the interference area from the non-interference area, and the calculation is simple and easy to implement.

[0020] The present invention is described in further detail below in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 is the range spectrum amplitude before equalization.

[0022] Figure 2 is the range spectrum amplitude after equalization.

[0023] Figure 3 There are 10 sub-band images.

[0024] Figure 4 is the sub-band contrast calculation result.

[0025] Figure 5 Intermittent sampling interference detection results. DETAILED DESCRIPTION

[0026] The present invention, namely a method for detecting interference from a SAR single-view complex image, is further described below with reference to the accompanying drawings and examples.

[0027] A method for detecting interference from a SAR single-view complex image, performing a range Fourier transform on the SAR image to be processed; performing equalization on the range spectrum of the SAR image; dividing the range spectrum into multiple sub-bands at equal intervals; performing a range inverse Fourier transform on each sub-band spectrum to obtain multiple sub-band images; calculating the contrast of each pixel in the sub-band domain; comparing the calculated contrast with a threshold, and detecting an interference pixel if the contrast exceeds the threshold. The specific steps are:

[0028] Step 1: Perform range Fourier transform on the SAR image to be processed. The SAR single-view complex image is represented by a matrix I, and the image size is N a ×N r (azimuth x distance). Perform N distance operations on this matrix r Point Fourier transform is performed to obtain the distance spectrum matrix S.

[0029] Step 2: Equalize the range spectrum of the SAR image. Multiply the second dimension of the matrix S by the inverse of the range window function to make the range spectrum a rectangular window. If there is oversampling in the range, invalid data outside the data bandwidth must be set to 0. The data after equalization is recorded as S eq . Figure 1 The range spectrum amplitude before equalization is given. Figure 2 The range spectrum amplitude after equalization is given.

[0030] Step 3: Divide the range spectrum into multiple sub-bands at equal intervals. eq The distance bandwidth is divided into K sub-matrices at equal intervals, and the kth sub-matrix is ​​recorded as S eq,k . These matrices are the subband spectral matrices.

[0031] Step 4: Substitute each subband spectrum matrix S eq,k Distance to N r Point inverse Fourier transform is performed to obtain K sub-band images, and the kth sub-band image is recorded as I k . Figure 3 Ten examples of generated sub-band images are given, which contain a series of false targets caused by intermittent sampling and forwarding interference.

[0032] Step 5: Calculate the contrast of each pixel in the subband domain. Let the subband contrast of the [n,m]th pixel be C[n,m], and its calculation expression is

[0033]

[0034] Figure 4 This is an example of the sub-band contrast calculation results. The high contrast area corresponds to intermittent sampling forwarding interference.

[0035] Step 6: Compare the calculated sub-band contrast of each pixel with the threshold. If the contrast is greater than the threshold, it is determined to be an interference pixel. Let the threshold be ξ. If C[n,m]>ξ, the [n,m]th pixel has interference; otherwise, there is no interference. Figure 5 An example of intermittent sampling interference detection results is given.

Claims

1. A method for detecting interference from a SAR single-view complex image, characterized in that: include: Step 1: Perform range Fourier transform on the SAR image to be processed to obtain the range spectrum matrix; Step 2: Equalize the range spectrum of the SAR image; Step 3: Divide the distance spectrum after equalization into multiple sub-bands at equal intervals; Step 4: Perform inverse Fourier transform on each sub-band spectrum to obtain multiple sub-band images. Step 5: Calculate the contrast of each pixel in the sub-band domain. Step 6: Compare the calculated sub-band contrast of each pixel with the threshold. If the contrast is greater than the threshold, it is determined to be an interference pixel.

2. The method for detecting interference from a SAR single-view complex image according to claim 1, characterized in that: The specific steps of step 1 are: The SAR single-view complex image is represented by a matrix I, and the image size is N a ×N r , perform distance to N on this matrix r Point Fourier transform is performed to obtain the distance spectrum matrix S.

3. The method for detecting interference from a SAR single-view complex image according to claim 1, characterized in that: The specific method of step 2 for equalizing the range spectrum of the SAR image is: The second dimension of the distance spectrum matrix S is multiplied by the inverse of the distance window function, so that the distance spectrum is a rectangular window. If there is oversampling in the distance, the invalid data outside the data bandwidth is set to 0. The data after equalization is recorded as S eq .

4. The method for detecting interference from a SAR single-view complex image according to claim 1, characterized in that: Step 3: Divide the range spectrum after equalization into K sub-matrices at equal intervals within the range bandwidth, and the kth sub-matrix is ​​recorded as S eq,k .

5. The method for detecting interference from a SAR single-view complex image according to claim 1, characterized in that: Calculate the subband contrast C[n,m] of pixel [n,m], the specific formula is: Where K is the total number of offspring images, I k [n,m] is the kth subband image.

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