PS point extraction method for navigation satellite DInSAR system

Abstract

The present invention discloses a PS point extraction method for a navigation satellite DInSAR system. After obtaining a pre-processed image of a scene, a theoretical PS point calculation function is used to calculate the theoretical PS point. A window is used to traverse all pixel points in the pre-processed image to obtain the center point of the candidate PS point. For each candidate PS point center point, all pixel points around it whose absolute value is greater than or equal to the absolute value of the center point minus 3dB are selected together with the center point of the candidate PS point as a candidate PS point. When different candidate PS points have common pixels to generate a common area, the gradient value and direction of the common area are calculated, and the pixel points with lower absolute values than the two adjacent points in the gradient direction are used as the boundary of the two candidate PS points. The theoretical PS point and the candidate PS point are subjected to correlation analysis, and the desired final PS point is screened. The method of the present invention separates different candidate PS points to ensure that the candidate PS points do not overlap and generate errors, thereby achieving a high-precision extraction effect.

Description

Technical Field

[0001] The present invention relates to the technical field of bistatic synthetic aperture radar, in particular to a PS point extraction method of a navigation satellite DInSAR system. Background Art

[0002] The DInSAR (Differential Interferometry Synthetic Aperture Radar) system based on navigation satellites is characterized by its short re-orbit period, ability to achieve three-dimensional monitoring, and low hardware cost in deformation monitoring. However, spatial and temporal decorrelation can severely affect the accuracy of the interferometric phase, and thus the results of deformation inversion.

[0003] PS-InSAR (Permanent Scatter Synthetic Aperture Radar Interferometry) technology is applied to navigation satellite systems. By processing the phase of PS (Permanent Scatterers), the error caused by decoherence can be reduced. However, in the DInSAR system of navigation satellites, due to the low two-dimensional resolution of the system, a single resolution unit contains multiple pixels. The timing processing of navigation satellites is to analyze the phase of the pixels in all resolution units to reduce noise interference. The traditional PS point selection method is based on pixel point processing and is not suitable for the DInSAR system of navigation satellites. Therefore, there is an urgent need for a PS point selection method that can be applied to the DInSAR system of navigation satellites to extract PS points. Summary of the Invention

[0004] In view of this, the present invention provides a PS point extraction method for a navigation satellite DInSAR system, which can extract PS points accurately and quickly.

[0005] To achieve the above-mentioned purpose of the invention, the technical solution of the present invention is as follows:

[0006] The PS point extraction method of the navigation satellite DInSAR system includes the following steps:

[0007] The global navigation satellite system (GNSS) is used to image the imaging scene, and a preprocessed image is obtained after preprocessing; the theoretical PS point calculation function is used to calculate the theoretical PS point.

[0008] A window is used to traverse all pixel points of the preprocessed image, and the point with the largest absolute value in the window is taken as the center point of the candidate PS point; the boundary range of the candidate PS point is determined according to the 3dB range of the center point of the candidate PS point and the gradient of the pixel point, and the candidate PS point is selected.

[0009] A correlation analysis is performed on the theoretical PS points and the candidate PS points to obtain the correlation coefficient; the candidate PS points with a correlation coefficient greater than the set threshold are extracted as the final PS points.

[0010] Furthermore, the boundary range of the candidate PS point is determined based on the 3dB range of the center point of the candidate PS point and the gradient of the pixel point, and the candidate PS point is selected. The specific method is as follows:

[0011] For each candidate PS point center point, select all the surrounding pixel points whose absolute values are greater than or equal to the absolute value of the center point minus 3dB together with the center point of the candidate PS point as a candidate PS point. When different candidate PS points have common pixels and generate a common area, calculate the gradient value and direction of the common area, and take the pixel point with a lower absolute value than the two adjacent points in the gradient direction as the boundary between the two candidate PS points.

[0012] Furthermore, the theoretical PS point calculation function is used to calculate the theoretical PS point. The specific method is:

[0013] For pixel A in the preprocessed image, when extracting the theoretical PS point of pixel A, randomly select pixel B around pixel A as the possible pixel point of the theoretical PS point, substitute the coordinates of pixel A, the coordinates of possible pixel B and the navigation satellite parameters into the theoretical PS point calculation formula to calculate the PSF value; judge whether the PSF value is within the 3dB range of the amplitude of pixel A. If so, pixel B may belong to the theoretical PS point of pixel A; otherwise, it does not belong to the theoretical PS point of pixel A; all pixels that meet the requirements constitute the theoretical PS point of pixel A.

[0014] Furthermore, the global navigation satellite system GNSS is used to image the imaging scene, and a preprocessed image is obtained after preprocessing. The specific method is as follows:

[0015] The GNSS antenna receives the direct wave signal from the navigation satellite and the echo signal of the scene to be extracted, which is down-converted by the receiver and processed by BP imaging to obtain an image; the image is normalized and filtered to obtain a pre-processed image.

[0016] Furthermore, the formula for the theoretical PS point calculation function is:

[0017]

[0018] Where A is the coordinate of a pixel point in the scene area to be extracted, B is the coordinate of any pixel point, p(·) is the matched filter output of the ranging signal, and m A (·) is the inverse transform of the normalized received signal amplitude pattern, β is the bistatic angle, θ is the unit vector in the direction of the bisector, and ω E is the equivalent angular velocity, ρ is the equivalent motion direction, c is the speed of light, λ is the wavelength, and |X(A, B)| is the PSF value.

[0019] Furthermore, the correlation calculation formula is:

[0020]

[0021] Where γ is the correlation coefficient, M(i, j) is the amplitude of the theoretical PS point at coordinate (i, j), S(i, j) is the absolute value of the candidate PS point at coordinate (i, j); (·)* is the complex conjugate of (·), m is the number of horizontal pixels in the PS point, and n is the number of vertical pixels in the PS point.

[0022] Beneficial effects:

[0023] 1. The present invention proposes a PS point extraction method for a navigation satellite DInSAR system. After obtaining a preprocessed image of the scene, a theoretical PS point calculation function is used to obtain a theoretical PS point. A window is used to traverse all pixel points in the preprocessed image to obtain candidate PS points. Correlation analysis is performed on the theoretical PS points and the candidate PS points. All pixel points in the final desired PS point are screened, and the PS points can be extracted accurately and quickly.

[0024] 2. When selecting candidate PS points, the present invention selects all surrounding pixels with an absolute value greater than or equal to the center point's absolute value minus 3dB for each candidate PS point's center point as a single candidate PS point. When different candidate PS points share common pixels and form a common region, the gradient value and direction of the common region are calculated, and the pixel with a lower absolute value in the gradient direction than the two adjacent pixels is used as the boundary between the two candidate PS points. This method separates different candidate PS points, ensuring that they do not overlap and generate errors, thus achieving high-precision extraction results.

[0025] 3. The present invention substitutes the pixel coordinates and navigation satellite parameters into the theoretical PS point calculation function and determines whether the PSF value is within 3dB of the amplitude of pixel A. If it is, pixel B is likely to belong to the theoretical PS point of pixel A; otherwise, it does not belong to the theoretical PS point of pixel A. All pixels that meet the requirements constitute the theoretical PS point of pixel A. Based on the analysis of candidate PS points, the present method selects pixels that meet the requirements to form the theoretical PS point, achieving high-precision extraction results.

[0026] 4. The present invention uses the GNSS system to obtain images and performs normalization and filtering on the images, thereby reducing the amount of computation required for subsequent deformation inversion calculations and improving the computation speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a system configuration diagram of the present invention.

[0028] Figure 2 Flow chart of the method of the present invention.

[0029] Figure 3This is a statistical diagram of the correlation coefficients between the candidate PS points and the theoretical PS points according to the embodiment of the present invention. DETAILED DESCRIPTION

[0030] The present invention is described in detail below with reference to the accompanying drawings and embodiments.

[0031] like Figure 1 As shown, the present invention provides a method for extracting PS points of a navigation satellite DInSAR system, which specifically includes the following steps:

[0032] Step 1: Use the global navigation satellite system GNSS to image the imaging scene, and obtain a preprocessed image after preprocessing the image; and use the theoretical PS point calculation function to calculate the theoretical PS point.

[0033] The specific process of collecting images is as follows: The GNSS-DInSAR receiving system includes a direct wave antenna, an echo antenna, a data acquisition device, and a receiver. The direct wave antenna points to the satellite, and the echo antenna points to the imaging scene. The navigation satellite sends a ranging signal to the imaging scene, the direct wave antenna receives the navigation direct wave signal, and the echo antenna is responsible for receiving the echo signal after the scene is reflected. The two signals are received by the antenna and processed into normalized signals. After being down-converted by the receiver, they are collected by the data acquisition device. The collected data is processed by BP imaging to obtain an image. The configuration of the entire system is as follows Figure 1 Each point on the image is divided by the maximum value in the image to obtain a normalized result. Then, the threshold filter threshold is set and the normalized result is filtered to obtain the preliminary processed result.

[0034] The specific preprocessing method is to normalize the image and then perform threshold filtering on the resulting normalized image. The specific method for normalizing the image is to normalize the image based on the maximum value within the image. The preprocessed image contains pixels, each of which corresponds to an absolute value that can be obtained from the GNSS system.

[0035] The method for calculating the theoretical PS point is as follows: when extracting the theoretical PS point of pixel A, substitute the coordinates of pixel A, the coordinates of the surrounding possible pixel B, and the navigation satellite parameters into the theoretical PS point calculation function; determine whether the PSF value is within the 3dB range of the amplitude of pixel A. If it is, then pixel B may belong to the theoretical PS point of pixel A; otherwise, it does not belong to the theoretical PS point of pixel A; all pixels that meet the requirements constitute the theoretical PS point of pixel A. The specific method is:

[0036] Find all pixel points B that satisfy the 3dB range of equation (1) to form the theoretical PS points. The theoretical PS point calculation function can be expressed as:

[0037]

[0038] Where A is the pixel point of the target in the scene area, B is any pixel point randomly selected around A, p(·) is the matched filter output of the ranging signal sent by the navigation satellite to the scene, and m A (·) is the inverse transform of the amplitude pattern of the normalized received signal (the direct wave signal and the echo signal received by the receiver), β is the bistatic angle (receiver-target-navigation satellite), θ is the unit vector in the direction of the bistatic angle bisector; ω E and ρ are the equivalent angular velocity and equivalent motion direction of the navigation satellite relative to the receiver; c is the speed of light, λ is the wavelength, and |X(A, B)| is the PSF value.

[0039] Step 2: Extract candidate PS points. Due to the unique characteristics of navigation satellite systems, the center of a PS point has the largest amplitude. Therefore, this method uses a window to traverse all pixels in the preprocessed image and selects the point with the largest absolute value within the window as the center of the candidate PS point. The window is elliptical, with the minor axis representing the azimuth resolution and the major axis representing the range resolution. The window size is the same as the theoretical PS point size.

[0040] For each candidate PS point center point, select all the surrounding pixel points whose absolute values are greater than or equal to the absolute value of the center point minus 3dB together with the center point of the candidate PS point as a candidate PS point. When different candidate PS points have common pixels and generate a common area, calculate the gradient value and direction of the common area, and take the pixel point with a lower absolute value than the two adjacent points in the gradient direction as the boundary between the two candidate PS points.

[0041]

[0042]

[0043] Among them, α(·) is the gradient direction of the preprocessed image, M(·) is the gradient size of the preprocessed image, and are the horizontal and vertical changes in the preprocessed image at the pixel point (x, y), respectively. Each non-zero point in the gradient magnitude M is detected. If the pixel point has a lower value than the two adjacent points in the gradient direction, the pixel point is considered as the boundary point of the candidate PS point, and different candidate PS points are separated.

[0044] Step 3: Perform correlation analysis on the theoretical PS points and candidate PS points to obtain the correlation coefficient; extract the candidate PS points whose correlation coefficient is greater than the set threshold as the final PS points. The specific method is: substitute the complex values of all pixels in the theoretical PS points in the window and the complex values of all pixels in the candidate PS points into the correlation calculation formula to obtain the correlation coefficient; determine whether the correlation coefficient is greater than the set threshold. If it is greater than the set threshold, it belongs to the PS point; otherwise, it does not belong to the PS point. All pixel points that meet the requirements constitute the desired PS point. In this embodiment of the present invention, the threshold is set to 0.7.

[0045] The candidate PS points and theoretical PS points are used for correlation analysis. The larger the correlation coefficient, the more accurate the selected candidate PS points. The correlation coefficient can be expressed as:

[0046]

[0047] Where γ is the correlation coefficient, M(i, j) is the complex value of the theoretical PS point at coordinates (i, j), and S(i, j) is the complex value of the candidate PS point at coordinates (i, j); (·)* is the complex conjugate of (·), m is the number of horizontal pixels in the PS point, and n is the number of vertical pixels in the PS point.

[0048] In this embodiment, a receiving system is built in an eco-park somewhere. The eco-park has a flat terrain, and there are targets with different scattering characteristics such as man-made buildings, paths, lakes, and vegetation in the scene. The coverage of different targets is quite distinct, so this scene is very suitable for PS point selection experiments. The specific parameters of the receiving equipment in the experiment are shown in Table 1. After the experiment on May 3, 2021, the imaging results of the scene were obtained. The value of each pixel point was divided by the maximum value in the image, and then the logarithm of each pixel point was taken, and then threshold filtering was performed. The threshold was set to 180dB to obtain the preliminary processing results. Combining it with the satellite optical image of the scene, the imaging interpretation result of the eco-park can be obtained. The results show that there are no scattering points distributed in the lake and vegetation areas in the scene. The scattering points are mostly distributed on the lakeside path, the small building next to the lake, and the antenna at the origin, which is consistent with the distribution of strong and weak scattering characteristics of the scene.

[0049] Table 1 Parameters of receiving equipment

[0050]

[0051]

[0052] Substituting the experimental parameters into the theoretical PS point calculation function yields the theoretical PS point. The results obtained from the preliminary processing are traversed using a window of the same size as the theoretical PS point, and the point with the largest absolute value within the window is selected as the center point of the candidate PS. The pixels within a 3dB range of the center point of each candidate PS point and the center point are selected as the candidate PS point. When different candidate PS points have common pixels and a common area, the gradient value and direction of the common area are calculated, and the pixel with a lower absolute value than the two adjacent points in the gradient direction is used as the boundary between the two candidate PS points. This can separate the connected areas between different candidate PS points and yield preliminary results.

[0053] Perform correlation analysis on each candidate PS point and the theoretical PS point, and substitute the correlation calculation formula to obtain the correlation coefficient of each candidate PS point. The statistical results are as follows: Figure 3 So far, the result of this method can be obtained.

[0054] In summary, the above are only preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A PS point extraction method for a navigation satellite DInSAR system, characterized in that: The specific steps include: Use the global navigation satellite system GNSS to image the imaging scene and obtain a preprocessed image after preprocessing; use the theoretical PS point calculation function to calculate the theoretical PS point; A sliding window is used to traverse all pixels of the preprocessed image, and the point with the largest absolute value in the sliding window is taken as the center point of the candidate PS point; the boundary range of the candidate PS point is determined according to the 3dB range of the center point of the candidate PS point and the gradient of the pixel point, and the candidate PS point is selected; Perform correlation analysis on the theoretical PS points and candidate PS points to obtain the correlation coefficient; extract the candidate PS points with correlation coefficient greater than the set threshold as the final PS points; The boundary range of the candidate PS point is determined based on the 3dB range of the center point of the candidate PS point and the gradient of the pixel point, and the candidate PS point is selected. The specific method is: For each candidate PS point center point, select all the surrounding pixel points whose absolute values are greater than or equal to the absolute value of the center point minus 3dB together with the center point of the candidate PS point as a candidate PS point. When different candidate PS points have common pixels and generate a common area, calculate the gradient value and direction of the common area, and take the pixel point with a lower absolute value than the two adjacent points in the gradient direction as the boundary between the two candidate PS points.

2. The method according to claim 1, wherein The theoretical PS point calculation function is used to calculate the theoretical PS point, and the specific method is: For pixel A in the preprocessed image, when extracting the theoretical PS point of pixel A, randomly select pixel B around pixel A as the possible pixel point of the theoretical PS point, substitute the coordinates of pixel A, the coordinates of possible pixel B and the navigation satellite parameters into the theoretical PS point calculation formula to calculate the PSF value; judge whether the PSF value is within the 3dB range of the amplitude of pixel A. If so, pixel B may belong to the theoretical PS point of pixel A; otherwise, it does not belong to the theoretical PS point of pixel A; all pixels that meet the requirements constitute the theoretical PS point of pixel A.

3. The method according to claim 1, wherein The imaging scene is imaged using the global navigation satellite system GNSS, and a preprocessed image is obtained after preprocessing. The specific method is as follows: The GNSS antenna receives the direct wave signal from the navigation satellite and the echo signal of the scene to be extracted, which is down-converted by the receiver and processed by BP imaging to obtain an image; the image is normalized and filtered to obtain a pre-processed image.

4. The method according to claim 1 or 2, wherein: The formula of the theoretical PS point calculation function is: Where A is the coordinate of a pixel point in the scene area to be extracted, B is the coordinate of any pixel point, p(·) is the matched filter output of the ranging signal, and m A (·) is the inverse transform of the normalized received signal amplitude pattern, β is the bistatic angle, θ is the unit vector in the direction of the bisector, and ω E is the equivalent angular velocity, ρ is the equivalent motion direction, c is the speed of light, λ is the wavelength, and |X(A,B)| is the PSF value.

5. The method according to claim 1, wherein The correlation coefficient calculation formula is: Where γ is the correlation coefficient, M(i, j) is the amplitude of the theoretical PS point at coordinate (i, j), S(i, j) is the absolute value of the candidate PS point at coordinate (i, j); (·)* is the complex conjugate of (·), m is the number of horizontal pixels in the PS point, and n is the number of vertical pixels in the PS point.

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