A unified geometric calibration method for wide-range spaceborne SAR images

Abstract

This invention relates to a unified geometric calibration method for large-scale spaceborne SAR images, comprising: collecting SAR image products and preprocessing them to obtain intensity data; constructing an RD geometric positioning model based on SAR image auxiliary files; acquiring the corresponding orthophoto and digital elevation model of the SAR image, generating a database of control points and checkpoints, thereby calculating the geometric positioning deviation of the initial RD model; determining the sources of ground geometric positioning errors based on the SAR imaging mechanism, thereby establishing error equations and a geometric calibration model; obtaining atmospheric parameters using a standard atmospheric model and combining it with the Saas-Tamonin and Krobuscher models to achieve near-real-time estimation of atmospheric path delay; calculating SAR satellite imaging error correction parameters based on the control point database and the geometric calibration model, and then updating the RD geometric positioning model. Compared with existing technologies, the unified geometric calibration method for large-scale spaceborne SAR images adopted in this invention does not require the support of a geometric calibration field and does not rely on reanalysis meteorological products, thus possessing better versatility.

Description

Technical Field

[0001] This invention relates to the field of SAR image calibration technology, and in particular to a unified geometric calibration method for large-scale spaceborne SAR images. Background Technology

[0002] During their operation in orbit, synthetic aperture radar (SAR) satellites are inevitably affected by factors such as platform stability, equipment aging, changes in the observation environment, and orbit control. Laboratory calibration parameters cannot meet the high-precision mapping requirements throughout the satellite's lifecycle. Eliminating systematic errors during SAR satellite operation and improving the positioning accuracy of SAR images is a crucial issue in the field of radar photogrammetry and plays a vital role in unlocking the application potential of SAR images.

[0003] Regular on-orbit geometric calibration helps eliminate accumulated systematic errors throughout a satellite's lifecycle and is the most economical and effective means of improving the accuracy of uncontrolled geometric positioning for spaceborne SAR. Currently, mainstream SAR geometric calibration models are all established using rigorous geometric positioning models based on SAR imaging principles.

[0004] Existing technologies suffer from the following drawbacks: numerical weather prediction products often produce unpredictable results; data generated by reanalysis systems is often derived from the assimilation of multi-source meteorological data, frequently resulting in a time lag of several months. Field measurements of atmospheric parameters require substantial human and material resources, making them virtually impossible for large-scale geometric calibration tasks. Another dependence of geometric calibration on external data lies in its reliance on high-precision ground control points, which often necessitates high-precision measurements using GNSS equipment in the field—an extremely challenging aspect for large-scale geometric calibration tasks.

[0005] Considering the positioning accuracy of domestically produced civilian SAR satellites, their geometric performance still needs to be further improved for most mapping tasks in order to fully realize the all-weather, all-day imaging advantages of SAR images. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the existing technology and provide a unified geometric calibration method for large-scale spaceborne SAR images. Based on the acquisition of ground control points using DOM and DEM, a standard atmospheric model combined with Saastamoinen and Klobuchar models is used to estimate atmospheric path delay, thereby realizing a unified geometric calibration method for large-scale spaceborne SAR images. The geometric calibration results of this unified geometric calibration method can reach the level of traditional SAR geometric calibration, thus improving the geometric positioning performance of domestic SAR satellite images.

[0007] The objective of this invention can be achieved through the following technical solutions:

[0008] A unified geometric calibration method for large-scale spaceborne SAR images includes the following steps:

[0009] S1: Collect SAR images and, after preprocessing, obtain intensity data reflecting the radiation characteristics of ground objects;

[0010] S2: Construct an RD geometric positioning model based on the auxiliary files attached to the SAR image to achieve geometric positioning of the SAR image on the ground;

[0011] S3: Obtain the orthophoto and digital elevation model of the area corresponding to the SAR image. Collect corresponding image points in the SAR image and orthophoto according to the RD geometric positioning model. Obtain the image-side coordinates of the corresponding target points in the SAR image and the object-side coordinates in the orthophoto, respectively. Obtain the elevation in the digital elevation model according to the object-side coordinates to form ground control points of corresponding point pairs and generate a database of control points and check points.

[0012] S4: Calculate the geometric positioning deviation of the RD geometric positioning model based on the control point and checkpoint database;

[0013] S5: Determine the sources of geometric positioning errors in SAR images, and thus establish error equations and geometric calibration models;

[0014] S6: Atmospheric parameters are obtained using a standard atmospheric model and combined with the Saastamonin model to estimate the tropospheric delay. The ionospheric delay is estimated using the Krobuscher model to achieve near real-time estimation of atmospheric path delay, thereby obtaining the atmospheric propagation parameters in the geometric calibration model.

[0015] S7: Calculate SAR satellite imaging error correction parameters based on the control point database and geometric calibration model, thereby updating the RD geometric positioning model.

[0016] Furthermore, in step S1, the preprocessing includes radiometric correction of the SAR image, and conversion of backscatter information and phase information into normalized intensity data reflecting the radiometric characteristics of ground features.

[0017] Further, in step S2, the construction process of the RD geometric positioning model includes:

[0018] The position and velocity during satellite imaging are fitted based on the ephemeris data in the auxiliary file:

[0019]

[0020] In the formula, ( a 0 ,a 1 ,a 2,a 3 ,b 0 ,b 1 ,b 2 ,b 3 ,c 0 ,c 1 ,c 2 ,c 3 ) represents the coefficients of the fitted position equation; For the SAR image, the first j The imaging time corresponding to a row of pixels, i.e., the azimuth imaging time; j The azimuth coordinates are the image coordinates, i.e., the row coordinates of the observed target in the SAR image; t a0 The azimuth start imaging time. f a Where is the pulse repetition frequency, ( X g , Y g , Z g ) represents the object coordinates of the ground target point, X s , Y s , Z s () represents the spatial rectangular coordinates of the sensor at the moment of imaging the ground target point. V x , V y , V z ) is the first j The velocity vector of the row pixels, R This refers to the slant distance measurement between the observed target and the sensor.

[0021] Based on the principles of SAR satellite imaging, a geometric model for Earth observation is constructed:

[0022]

[0023] In the formula, R 0 It is the initial slope distance. i These are the range-oriented image coordinates, i.e., the column coordinates of the observed target in the SAR image. P r This refers to the range slant range resolution. f dThe Doppler center frequency between the satellite platform and the observed target at the time of imaging. P sc and V sc These are the position and velocity vectors of the sensor, respectively. P gc and V gc These are the position and velocity vectors of the observed target, respectively. The radar wavelength; a and b These are the major and minor semi-axes of the WGS-84 reference ellipsoid, respectively. h The average elevation of the area where the Earth observation target is located;

[0024] List the conditional equations:

[0025]

[0026] In the formula, i Here are the image-side coordinates of the target point in the SAR image. c At the speed of light, f r The system's range sampling frequency;

[0027] The aforementioned geospatial observation geometric model is established for each image point of the SAR image, using the object space coordinates of the center point as the initial value. During the iteration, the partial derivatives of the object space coordinates of the ground target points are calculated according to the aforementioned condition equations, and the partial derivative matrix is ​​continuously updated. When the coordinate correction value is less than the threshold, the model is considered to have converged, and the iteration ends, thereby obtaining the object space coordinates of the ground points, thus realizing the mutual mapping between image space and object space.

[0028] Furthermore, in step S3, the process of constructing the control point and checkpoint database includes:

[0029] S11: Select point targets from SAR images and record the corresponding image coordinates;

[0030] S12: Based on the RD geometric positioning model, the image coordinates corresponding to the point target are mapped to the object space. The image point with the same name as the point target is located in the orthophoto and the corresponding object space coordinates are recorded. The elevation is obtained in the digital elevation model based on the object space coordinates to form ground control points for the same point pair.

[0031] S13: Repeat steps 11-12 until the control point collection is completed, forming a database of control points and checkpoints.

[0032] Furthermore, step S4 specifically includes:

[0033] Based on the RD geometric positioning model of each image and the corresponding checkpoints in the control point and checkpoint database, the positioning result of the RD geometric positioning model and the object coordinates of the checkpoints are calculated, and the difference is taken to obtain the geometric positioning deviation of the RD geometric positioning model.

[0034] Further, in step S5, the imaging parameters are assigned according to the constructed RD geometric positioning model. Xs, Ys, Zs The orbital coordinates of the SAR sensor at the imaging time, R 0 Distance to the starting slope distance, P r Range slant range resolution, f r System range sampling frequency and f a Pre-configured errors are added to the pulse repetition frequency to perform SAR image-to-ground geometric positioning error source analysis.

[0035] The main errors in the geometric positioning of SAR images to the ground are determined, and a geometric calibration model is constructed accordingly.

[0036] Furthermore, the main errors in the geometric positioning of SAR images to the ground were determined to be the internal electronic delay of the system, the time synchronization error between the SAR payload and the GNSS payload, and the errors in radar sampling frequency and pulse repetition frequency.

[0037] The expression for the geometric calibration model is:

[0038]

[0039] The condition equations corresponding to the geometric calibration model are:

[0040]

[0041] In the formula, f r , f a The range sampling frequency and pulse repetition frequency are used. t r , t a For distance and azimuth time, t r0 , t a0 For the start time in the distance and azimuth directions, t delay ∆t is the atmospheric propagation delay value. r It is the internal electronic delay of the system. ∆t a This refers to the synchronization error between the SAR payload and the GNSS payload.

[0042] The calibration parameters are expanded to the first-order term using Taylor series, and then the optimal estimate of the error parameters can be achieved by using Newton's iteration method based on the least squares principle.

[0043] Furthermore, in step S6, the calculation expression for atmospheric parameters obtained using the standard atmospheric model is as follows:

[0044]

[0045] In the formula, Press Atmospheric pressure Temp Kelvin temperature h It refers to altitude. w It refers to relative humidity. W press It is the partial pressure of water vapor.

[0046] Furthermore, the calculation expression for the Sastamourn model is as follows:

[0047]

[0048] In the formula, θ It is the incident angle of the SAR satellite. ϕ It is the satellite elevation angle. D h It's a dry delay. D w It's a wet delay. ZTD It is the total tropospheric delay;

[0049] The calculation expression for the Krobcher model is as follows:

[0050]

[0051] In the formula, TEC It refers to the electron concentration in the ionosphere; f It is the radar center frequency; ZID It is ionospheric delay.

[0052] Furthermore, based on the RD geometric positioning model of each image and the control point data it contains, the SAR satellite imaging error correction parameters are estimated according to the geometric calibration model, and the RD geometric positioning model of the SAR image is updated.

[0053] Compared with the prior art, the present invention has the following advantages:

[0054] This invention considers using orthophotos (DOM) and digital elevation models (DEM) to acquire ground control information, employing a standard atmospheric model to obtain atmospheric parameters, combining the Saastamoinen model to estimate tropospheric atmospheric delay, and using the Klobuchar model to estimate ionospheric delay, achieving near real-time estimation of atmospheric path delay. This eliminates dependence on ground geometric calibration fields and external meteorological data, thus constructing a unified geometric calibration method applicable to large-scale spaceborne SAR imagery. The effectiveness and reliability of the model are evaluated by assessing the range of estimated SAR satellite imaging system bias parameters and by selecting ground checkpoints.

[0055] Taking the fine strip 2 mode imagery of the Gaofen-3 SAR satellite in the Yangtze River Delta region as an example, the geometric calibration results of the unified geometric calibration method for large-scale spaceborne SAR images can reach the level of traditional SAR geometric calibration, thereby improving the geometric positioning performance of domestic SAR satellite images and contributing to large-scale and even global geometric calibration. Attached Figure Description

[0056] Figure 1 This is a flowchart illustrating a unified geometric calibration method for large-scale spaceborne SAR images provided in an embodiment of the present invention.

[0057] Figure 2 This is a deviation comparison diagram of a trajectory fitted using second-order and third-order polynomials, provided in an embodiment of the present invention.

[0058] Figure 3 This is a schematic diagram illustrating the positioning accuracy of a SAR image under different combinations of conditions, as provided in an embodiment of the present invention. Detailed Implementation

[0059] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0060] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0061] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0062] Example 1

[0063] like Figure 1 As shown, this embodiment provides a unified geometric calibration method for large-scale spaceborne SAR images, including the following steps:

[0064] S1: Collect SAR images and, after preprocessing, obtain intensity data reflecting the radiation characteristics of ground objects;

[0065] S2: Construct an RD geometric positioning model based on the auxiliary files attached to the SAR image to achieve geometric positioning of the SAR image on the ground;

[0066] S3: Obtain orthophotos and digital elevation models of the area corresponding to the SAR image. Collect corresponding image points in the SAR image and orthophoto based on the RD geometric positioning model. Obtain the image-side coordinates of the corresponding target points in the SAR image and the object-side coordinates in the orthophoto, respectively. Obtain the elevation in the digital elevation model based on the object-side coordinates to form ground control points for corresponding point pairs. Generate a database of control points and check points.

[0067] S4: Calculate the geometric positioning deviation of the RD geometric positioning model based on the control point and checkpoint database;

[0068] S5: Determine the sources of geometric positioning errors in SAR images, and thus establish error equations and geometric calibration models;

[0069] S6: Atmospheric parameters are obtained using the standard atmospheric model and estimated by combining the Saastamonin model with the tropospheric delay. The ionospheric delay is estimated by the Krobuscher model, achieving near real-time estimation of atmospheric path delay and obtaining atmospheric propagation parameters in the geometric calibration model.

[0070] S7: Calculate SAR satellite imaging error correction parameters based on the control point database and geometric calibration model, thereby updating the RD geometric positioning model.

[0071] Specifically,

[0072] In step S1, preprocessing includes radiometric correction of the SAR image, and conversion of backscatter information and phase information into normalized intensity data that reflects the radiometric characteristics of ground features.

[0073] In step S2, the construction process of the RD geometric positioning model includes:

[0074] The satellite's position and velocity during imaging were fitted based on ephemeris data from the auxiliary file:

[0075]

[0076] In the formula, ( a 0 ,a 1 ,a 2 ,a 3 ,b 0 ,b 1 ,b 2 ,b 3 ,c 0 ,c 1 ,c 2 ,c 3 ) represents the coefficients of the fitted position equation; For the SAR image, the first j The imaging time corresponding to a row of pixels, i.e., the azimuth imaging time; j The azimuth coordinates are the image coordinates, i.e., the row coordinates of the observed target in the SAR image; t a0 The azimuth start imaging time. f a Where is the pulse repetition frequency, ( X g , Y g , Z g ) represents the object coordinates of the ground target point, X s , Y s , Z s () represents the spatial rectangular coordinates of the sensor at the moment of imaging the ground target point. V x , V y , V z ) is the first j The velocity vector of the row pixels, R This refers to the slant distance measurement between the observed target and the sensor.

[0077] Based on the principles of SAR satellite imaging, a geometric model for Earth observation is constructed:

[0078]

[0079] In the formula, R 0 It is the initial slope distance. i These are the range-oriented image coordinates, i.e., the column coordinates of the observed target in the SAR image. P r This refers to the range slant range resolution. f d The Doppler center frequency between the satellite platform and the observed target at the time of imaging. P sc and V sc These are the position and velocity vectors of the sensor, respectively. P gc and V gc These are the position and velocity vectors of the observed target, respectively. The radar wavelength; a and b These are the major and minor semi-axes of the WGS-84 reference ellipsoid, respectively. h The average elevation of the area where the Earth observation target is located;

[0080] The conditional equations for determining the geometric positioning model based on SAR imaging geometric features are listed below:

[0081]

[0082] In the formula, For distance to start time, c At the speed of light, f r This refers to the range sampling frequency of the radar system. , For range imaging time;

[0083] A ground observation geometric model is established for each image point of the SAR image. The object space coordinates of the center point are used as the initial value. During the iteration, the partial derivatives of the object space coordinates of the ground target points are calculated according to the condition equation. The partial derivative matrix is ​​continuously updated. When the coordinate correction value is less than the preset threshold, the model is considered to have converged and the iteration ends. The object space coordinates of the ground points can then be obtained, thus constructing the RD geometric positioning model.

[0084] In step S3, the process of constructing the control point and checkpoint database includes:

[0085] S11: Select point targets (road or river intersections) with obvious geometric features from SAR images and record the corresponding image coordinates;

[0086] S12: Based on the RD geometric positioning model, map the image coordinates of the point target to the object space, locate the corresponding image point in the orthophoto and record the corresponding object space coordinates, obtain the elevation in the digital elevation model based on the object space coordinates, and form ground control points for the corresponding point pair.

[0087] S13: Repeat steps 11-12 until the control point acquisition is completed. According to the spatial distribution of control points, ensure that each image has no less than 5 control points and 5 check points to form a database of control points and check points.

[0088] Step S4 is as follows:

[0089] Based on the RD geometric positioning model of each image and the corresponding checkpoints in the control point and checkpoint database, the positioning result of the RD geometric positioning model and the object coordinates of the checkpoints are calculated, and the difference is taken to obtain the geometric positioning deviation of the RD geometric positioning model.

[0090] Step S5 specifically involves:

[0091] S51: Based on the constructed RD geometric positioning model, assign imaging parameters respectively ( Xs, Ys, Zs The orbital coordinates of the SAR sensor at the imaging time, R 0 Distance to the starting slope distance, P r Range slant range resolution, f r System range sampling frequency and f a Pre-configured errors are added to the pulse repetition frequency to perform SAR image-to-ground geometric positioning error source analysis.

[0092] S52: Based on the analysis in step 51), the main errors in the geometric positioning of SAR images to the ground can be determined to be the internal electronic delay of the system, the time synchronization error between the SAR payload and the GNSS payload, and the errors in radar sampling frequency and pulse repetition frequency.

[0093] The expression for the geometric calibration model is:

[0094]

[0095] The condition equations corresponding to the geometric calibration model are:

[0096]

[0097] In the formula, f r , f a The range sampling frequency and pulse repetition frequency are used. t r, t a For distance and azimuth time, t r0 , t a0 For the start time in the distance and azimuth directions, t delay ∆t is the atmospheric propagation delay value. r It is the internal electronic delay of the system. ∆t a This refers to the synchronization error between the SAR payload and the GNSS payload.

[0098] The calibration parameters are expanded to the first-order term using Taylor series, and then the optimal estimate of the error parameters can be achieved by using Newton's iteration method based on the least squares principle.

[0099] Step S6 is as follows:

[0100] S61: Estimate atmospheric parameters for any location and time based on the standard atmospheric model, as follows:

[0101]

[0102] In the formula, Press Atmospheric pressure Temp Kelvin temperature h It refers to altitude. w It refers to relative humidity. W press It is the partial pressure of water vapor;

[0103] S62: Based on the atmospheric parameters calculated in step S61, the tropospheric atmospheric path delay is calculated using the Saastamoinen model, as follows:

[0104]

[0105] In the formula, θ It is the incident angle of the SAR satellite. ϕ It is the satellite elevation angle. D h It's a dry delay. D w It's a wet delay. ZTD It is the total tropospheric delay;

[0106] The ionospheric path delay is estimated using the Klobuchar model, as follows:

[0107]

[0108] In the formula, TEC It refers to the electron concentration in the ionosphere; f It is the radar center frequency; ZID It is ionospheric delay.

[0109] Step 7) specifically refers to:

[0110] S71: Based on the RD geometric positioning model of each image and the control point data it contains, and using the geometric calibration method constructed in the above steps, estimate the system deviation parameters of the SAR satellite imaging system, and update the initial RD geometric positioning model of the SAR image.

[0111] Finally, the positioning deviation at each checkpoint was evaluated using checkpoints for both the initial and updated RD geometric positioning models. Statistical indicators such as the minimum, maximum, mean, and root mean square error of the deviation at all checkpoints included in each image were calculated.

[0112] This invention considers using orthophotos (DOM) and digital elevation models (DEM) to acquire ground control information, employing a standard atmospheric model to obtain atmospheric parameters, combining the Saastamoinen model to estimate tropospheric atmospheric delay, and the Klobuchar model to estimate ionospheric delay, achieving near real-time estimation of atmospheric path delay. This eliminates reliance on ground geometric calibration fields and external meteorological data, thus constructing a unified geometric calibration method applicable to large-scale spaceborne SAR images. The effectiveness and reliability of the model are evaluated by assessing the range of estimated SAR satellite imaging system bias parameters and selecting ground checkpoints. Taking the imagery of the Gaofen-3 SAR satellite in the Yangtze River Delta region in fine strip 2 mode as an example, the geometric calibration results of the unified geometric calibration method for large-scale spaceborne SAR images can reach the level of traditional SAR geometric calibration, improving the geometric positioning performance of domestic SAR satellite images and contributing to large-scale and even global geometric calibration.

[0113] Taking the Yangtze River Delta region of China as a case study, this paper verifies the effectiveness of a unified geometric calibration method for large-scale spaceborne SAR imagery. The case study focuses on Gaofen-3 SAR images from July 2018 to May 2019. Near-real-time atmospheric path delay estimation is achieved using the standard atmospheric model, Saastamoinen, and Klobuchar models. Ground control points are acquired using DOM and DEM, resulting in a unified geometric calibration method for large-scale spaceborne SAR imagery. The results show that this method achieves good correction effects and effectively improves the uncontrolled positioning accuracy of SAR images. The unified geometric calibration method for large-scale spaceborne SAR imagery includes the following steps:

[0114] 1) First, radiometric correction was performed on Gaofen-3 SAR images of the Yangtze River Delta region from July 2018 to May 2019. Table 1 shows the basic information of the SAR images used.

[0115] 2) Based on the auxiliary files of SAR image products, construct a physically meaningful RD geometric positioning model and establish the mapping relationship between image coordinates and object coordinates;

[0116] 3) Collect corresponding points in SAR images and DOM and DEM respectively to form a database of control points and checkpoints;

[0117] 4) Calculate the geometric positioning deviation of the SAR image based on the initial RD geometric positioning model;

[0118] 5) Analyze the sources of SAR ground geometric positioning error and establish a geometric calibration model. Figure 2 The fitting bias is shown when using quadratic and cubic polynomials;

[0119] 6) Near-real-time atmospheric path delay estimation was achieved using the standard atmospheric model, the Saastamoinen model, and the Klobuchar model. Table 2 shows the difference between the tropospheric delay estimated using the Saastamoinen model and the reference value provided by the international GNSS service.

[0120] 7) Calculate the satellite imaging system error correction value based on the control points and geometric calibration model to obtain the updated RD geometric positioning model;

[0121] 8) The geometric performance of the RD geometric positioning model before and after the update was verified using checkpoints. Table 3 shows the geometric calibration results obtained using two calibration strategies. Figure 3 The calibration accuracy of geometric positioning obtained by different image combinations is shown.

[0122] Table 1 Basic Image Information

[0123]

[0124] Table 2 Comparison of Tropospheric Delay Estimation Biases

[0125]

[0126] Table 3 Geometric calibration results for the two calibration strategies

[0127]

[0128] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. A unified geometric calibration method for large-scale spaceborne SAR images, characterized in that, Includes the following steps: S1: Collect SAR images and, after preprocessing, obtain intensity data reflecting the radiation characteristics of ground objects; S2: Construct an RD geometric positioning model based on the auxiliary files attached to the SAR image to achieve geometric positioning of the SAR image on the ground; S3: Obtain the orthophoto and digital elevation model of the area corresponding to the SAR image. Collect corresponding image points in the SAR image and orthophoto according to the RD geometric positioning model. Obtain the image-side coordinates of the corresponding target points in the SAR image and the object-side coordinates in the orthophoto, respectively. Obtain the elevation in the digital elevation model according to the object-side coordinates to form ground control points of corresponding point pairs and generate a database of control points and check points. S4: Calculate the geometric positioning deviation of the RD geometric positioning model based on the control point and checkpoint database; S5: Determine the sources of geometric positioning errors in SAR images, and thus establish error equations and geometric calibration models; S6: Atmospheric parameters are obtained using a standard atmospheric model and estimated using the Saastamonin model. The tropospheric delay is estimated using the Krobuscher model, thereby achieving near real-time estimation of atmospheric path delay and obtaining the atmospheric propagation parameters in the geometric calibration model. S7: Calculate SAR satellite imaging error correction parameters based on the control point database and geometric calibration model, thereby updating the RD geometric positioning model; In step S2, the construction process of the RD geometric positioning model includes: The position and velocity during satellite imaging are fitted based on the ephemeris data in the auxiliary file: In the formula, ( a 0 ,a 1 ,a 2 ,a 3 ,b 0 ,b 1 ,b 2 ,b 3 ,c 0 ,c 1 ,c 2 ,c 3 ) represents the coefficients of the fitted position equation; For the SAR image, the first j The imaging time corresponding to a row of pixels, i.e., the azimuth imaging time; j The azimuth coordinates are the image coordinates, i.e., the row coordinates of the observed target in the SAR image; t a0 The azimuth start imaging time. f a Where is the pulse repetition frequency, ( X g , Y g , Z g ) represents the object coordinates of the ground target point, X s , Y s , Z s () represents the spatial rectangular coordinates of the sensor at the moment of imaging the ground target point. V x , V y , V z ) is the first j The velocity vector of the row pixels, R This refers to the slant distance measurement between the observed target and the sensor. Based on the principles of SAR satellite imaging, a geometric model for Earth observation is constructed: In the formula, R 0 It is the initial slant distance. i These are the range-oriented image coordinates, i.e., the column coordinates of the observed target in the SAR image. P r This refers to the range slant range resolution. f d The Doppler center frequency between the satellite platform and the observed target at the time of imaging. P sc and V sc These are the position and velocity vectors of the sensor, respectively. P gc and V gc These are the position and velocity vectors of the observed target, respectively. The radar wavelength; a and b These are the major and minor semi-axes of the WGS-84 reference ellipsoid, respectively. h The average elevation of the area where the Earth observation target is located; List the conditional equations: In the formula, x For SAR image column number, c At the speed of light, f r The system range sampling frequency, , For range imaging time; For each image point of the SAR image, the ground observation geometric model is established. The object space coordinates of the center point are used as the initial value. During the iteration, the partial derivatives of the object space coordinates of the ground target point are calculated according to the condition equation. The partial derivative matrix is ​​continuously updated. When the coordinate correction value is less than the threshold, the model is considered to have converged and the iteration ends. The object space coordinates of the ground point can be obtained, thereby constructing the RD geometric positioning model. In step S3, the process of constructing the control point and checkpoint database includes: S11: Select point targets from SAR images and record the corresponding image coordinates; S12: Based on the RD geometric positioning model, the image coordinates corresponding to the point target are mapped to the object space. The image point with the same name as the point target is located in the orthophoto and the corresponding object space coordinates are recorded. The elevation is obtained in the digital elevation model based on the object space coordinates to form ground control points for the same point pair. S13: Repeat steps 11-12 until the control point collection is completed and a control point and checkpoint database is formed; In step S5, the imaging parameters are assigned according to the constructed RD geometric positioning model. Xs, Ys, Zs The orbital coordinates of the SAR sensor at the imaging time, R 0 Distance to the starting slope distance, P r Range slant range resolution, f r System range sampling frequency and f a Pre-configured errors are added to the pulse repetition frequency to perform SAR image-to-ground geometric positioning error analysis. The main errors in the geometric positioning of SAR images to the ground are determined, and a geometric calibration model is constructed accordingly. The main errors in the geometric positioning of SAR images to the ground were determined to be the internal electronic delay of the system, the time synchronization error between the SAR payload and the GNSS payload, and the errors in radar sampling frequency and pulse repetition frequency. The expression for the geometric calibration model is: The condition equations corresponding to the geometric calibration model are: In the formula, f r , f a The range sampling frequency and pulse repetition frequency are used. t r , t a For distance and azimuth time, t r0 , t a0 For the start time in the distance and azimuth directions, t delay ∆t is the atmospheric propagation delay value. r It is the internal electronic delay of the system. ∆t a This refers to the synchronization error between the SAR payload and the GNSS payload. The calibration parameters are expanded to the first-order term using Taylor series, and then the optimal estimate of the error parameters can be achieved by using Newton's iteration method based on the least squares principle.

2. The unified geometric calibration method for large-scale spaceborne SAR images according to claim 1, characterized in that, In step S1, the preprocessing includes radiometric correction of the SAR image, and conversion of backscatter information and phase information into normalized intensity data that reflects the radiometric characteristics of ground features.

3. The unified geometric calibration method for large-scale spaceborne SAR images according to claim 1, characterized in that, Step S4 is as follows: Based on the RD geometric positioning model of each image and the difference between the object coordinates of the initial RD geometric positioning model and the corresponding checkpoints in the control point and checkpoint database, the geometric positioning deviation of the RD geometric positioning model is obtained.

4. The unified geometric calibration method for large-scale spaceborne SAR images according to claim 1, characterized in that, In step S6, the calculation expression for atmospheric parameters obtained using the standard atmospheric model is as follows: In the formula, Press Atmospheric pressure Temp Kelvin temperature h It refers to altitude. w It refers to relative humidity. W press It is the partial pressure of water vapor.

5. A unified geometric calibration method for large-scale spaceborne SAR images according to claim 4, characterized in that, The calculation expression for the Sastamonen model is as follows: In the formula, θ It is the incident angle of the SAR satellite. ϕ It is the satellite elevation angle. D h It's a dry delay. D w It's a wet delay. ZTD It is the total tropospheric delay; The calculation expression for the Krobcher model is as follows: In the formula, TEC It refers to the electron concentration in the ionosphere; f It is the radar center frequency; ZID It is ionospheric delay.

6. The unified geometric calibration method for large-scale spaceborne SAR images according to claim 1, characterized in that, Based on the RD geometric positioning model of each image and the control point data it contains, the SAR satellite imaging error correction parameters are estimated according to the geometric calibration model, and the RD geometric positioning model of the SAR image is updated.

Images