A method for verifying precision of a far-near wave position combined baseline calibration model of a SAR satellite

Abstract

The application discloses a method for verifying precision of a far-near wave position joint baseline calibration model of a SAR satellite, and is based on a distributed InSAR terrain three-dimensional reconstruction model. The method uses the satellite antenna phase center position, velocity, ground target three-dimensional coordinates, slant range and baseline at the image center time of the far-near wave position image to obtain the simulation phase at the image center of the far-near wave position image. After adding errors to the baseline, the height error value at the image center of the far-near wave position image is obtained. Then, the baseline error is calculated based on the far-near wave position joint baseline calibration model. Finally, the difference between the added baseline error and the baseline error calculated through the far-near wave position joint baseline calibration model is obtained to obtain the precision of the far-near wave position joint baseline calibration model. Compared with the prior art of evaluating the baseline calibration precision through a DEM product, the application can quantitatively verify the precision of the far-near wave position joint baseline calibration model of the SAR satellite.

Description

Technical Field

[0001] This invention relates to spaceborne synthetic aperture radar data processing technology, and in particular to a method for verifying the accuracy of a SAR satellite near-far wave position joint baseline calibration model. Background Technology

[0002] Synthetic Aperture Radar (SAR) operates in the microwave band. It utilizes the relative motion between the observed target and the radar to transform a small, real antenna aperture into a larger one through data processing, making it an advanced imaging system. Because microwaves have a certain degree of penetrability, SAR systems can operate in adverse conditions such as clouds, rain, and fog, offering all-weather, all-day imaging capabilities and the ability to image large areas. Interferometric Synthetic Aperture Radar (InSAR) combines SAR and interferometric techniques, acquiring the three-dimensional coordinates of ground targets through interferometric processing of single-view complex image pairs.

[0003] Distributed SAR satellite systems utilize SAR antennas mounted on low-Earth orbit satellites with specific formation configurations to perform high-precision measurement tasks through the coordinated operation of the SAR antennas and the satellites. Spaceborne distributed InSAR, with its advantages of high echo coherence, variable baseline length, and high product accuracy, represents the development trend of spaceborne InSAR.

[0004] In spaceborne distributed InSAR topographic mapping, baseline error is one of the main sources of elevation error. High-precision baseline data is the foundation for operational DEM production; therefore, baseline error calibration is crucial. Currently, InSAR baseline calibration methods mainly fall into three categories: range-migration-based, spectral-migration-based, and control-data-based methods. Research indicates that control-data-based baseline calibration methods offer the highest accuracy. However, many proposed baseline calibration models lack verification of their calibration accuracy; instead, they evaluate the calibration effect indirectly through the quality of the final DEM product, which lacks persuasiveness. Summary of the Invention

[0005] The technical problem solved by this invention is to overcome the shortcomings of the prior art by providing a method for verifying the accuracy of the SAR satellite near and far wave position joint baseline calibration model, which can verify the calibration accuracy of the baseline calibration model and directly evaluate the calibration effect.

[0006] The technical solution of this invention is: a method for verifying the accuracy of a SAR satellite near-far wave position joint baseline calibration model, comprising:

[0007] Constructing a distributed InSAR terrain 3D reconstruction model;

[0008] Calculate the satellite antenna phase center position and velocity at the time of the near and far wavefront image center; obtain the three-dimensional coordinates and slant range of the ground target at the near and far wavefront image center based on external DEM data and antenna phase center position, and obtain the baseline at the time of the near and far wavefront image center; calculate the phase of the near and far wavefront image center position.

[0009] Add errors to the baseline and obtain the elevation error value at the center of the near and far position images; calculate the baseline error based on the near and far position joint baseline calibration model.

[0010] The accuracy of the near-far wavelength joint baseline calibration model is obtained by comparing the added baseline error with the baseline error calculated using the near-far wavelength joint baseline calibration model.

[0011] The present invention is further improved as follows:

[0012] To add errors to the baseline, firstly, based on geometric relationships, the baselines at the center time of the near and far wave positions images are transformed from the geocentric rectangular coordinate system to the TCN coordinate system, and then transformed into parallel and vertical baselines; then, using the baseline deviation as a constant value as a benchmark, errors are added to the parallel and vertical baselines at the center time of the near and far wave positions images respectively.

[0013] The parallel and vertical baselines are achieved using the following formulas.

[0014] B / / =B c sinθ+B n cosθ

[0015] B ⊥ =B c cosθ-B n sinθ

[0016] Among them, B / / B ⊥ They are parallel and vertical baselines, respectively, B c B n θ represents the c-axis and n-axis components of the baseline in the TCN coordinate system, and θ is the incident angle of the corresponding main image.

[0017] The parallel and vertical baselines at the center time of near and far position images after adding errors are achieved using the following formulas.

[0018] B / / ne =B / / n +B / / n_err

[0019] B ⊥ne =B ⊥n +B ⊥n_err

[0020] B / / fe =B / / f +B / / f_err

[0021]

[0022] Among them, B / / ne B ⊥ne To add errors to the near-position parallel and vertical baselines, B / / n B ⊥n For near-wavelength parallel and vertical baselines, B / / f B ⊥f For the far-wave parallel baseline and vertical baseline, B / / fe B ⊥fe To add errors to the far-wave parallel baseline and vertical baseline values, B / / n_err B ⊥n_err For the added near-position parallel baseline error and vertical baseline error, B / / f_err This is for the added far-wave parallel baseline error.

[0023] The elevation error value at the center of the near and far wavefront images is calculated by the following steps: inputting the baseline, satellite antenna phase center position, velocity, slant range, and phase after adding the error into the 3D reconstruction model to obtain the 3D coordinates of the ground target at the center of the near and far wavefront images; converting the coordinates into latitude and longitude coordinates to obtain the elevation value at the center of the near and far wavefront images; and obtaining the elevation error value by comparing it with the elevation at the center of the near and far wavefront images in the external DEM.

[0024] The parallel baseline error calculated based on the joint near-far wavelength baseline calibration model is achieved using the following formula.

[0025]

[0026] Among them, B / / err The parallel baseline error is given by λ, where λ is the wavelength and h is the wavelength. err For elevation error, h amb For fuzzy high.

[0027] The vertical baseline error calculated based on the joint near-far wavelength baseline calibration model is achieved using the following formula.

[0028]

[0029] in, For the baseline error vector, This is the near-wave parallel baseline error vector. For the far-wave parallel baseline error vector, This is the near-wave vertical baseline error vector. Vertical baseline error vector at far-wave position.

[0030] The accuracy of the near-far wavefront joint baseline calibration model is B. / / Δ B ⊥Δ To conduct an evaluation,

[0031]

[0032]

[0033] Among them, B / / n_err1 For near-wave parallel baseline error, B / / n_err To add near-position parallel baseline error, B / / f_err1 For the far-wave parallel baseline error, B / / f_err To add the parallel baseline error at the far-wave position, For near-wave vertical baseline error, B ⊥n_err This is for the added near-wave vertical baseline error.

[0034] The distributed InSAR terrain 3D reconstruction model is implemented using the following formula.

[0035]

[0036] in, The vector pointing from the Earth's center to the ground target. R1 is the vector pointing from the Earth's center to the phase center of the primary satellite antenna, R1 is the slant range from the phase center of the primary satellite antenna to the ground target, and B is the baseline pointing from the primary satellite to the secondary satellite. These are three orthogonal bases on the V, P, and Q axes. The main star's velocity vector, The interference phase is λ, the wavelength is r p for Projection on the P-axis In VPQ coordinate system The unit vector.

[0037] The calculation of the three-dimensional coordinates of the ground target at the center of the near and far wavefront images is achieved through the following steps: First, the external DEM is oversampled. Then, based on the oversampled external DEM and the range-Doppler model, a SAR image with a grid size that meets the preset conditions is simulated and the actual SAR image is simulated. Finally, the simulated SAR image is registered with the actual SAR image, a transformation table is established, the latitude and longitude coordinates of the center of the actual SAR image are obtained according to the transformation table, and then they are converted into geocentric rectangular three-dimensional coordinates.

[0038] The advantages of this invention compared to the prior art are as follows: Compared to the prior art method of evaluating baseline calibration accuracy from the perspective of DEM products, this invention can directly and quantitatively verify the accuracy of the SAR satellite near-far position joint baseline calibration model by obtaining the difference between the added baseline error and the baseline error calculated by the near-far position joint baseline calibration model. Attached Figure Description

[0039] Figure 1 This is a schematic diagram of the geometric relationships in the distributed InSAR terrain 3D reconstruction of this invention;

[0040] Figure 2 This is a schematic diagram of the baseline geometric relationship in the TCN coordinate system of this invention;

[0041] Figure 3 This is a schematic diagram of the baseline geometric relationship of near and far wavefront images in the TCN coordinate system of this invention;

[0042] Figure 4 The flowchart for verifying the accuracy of the distributed SAR satellite near-far wave position joint baseline calibration model is shown in this invention. Detailed Implementation

[0043] To better understand the technical solution of the present invention, the embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0044] Step 1: Construct a distributed InSAR terrain 3D reconstruction model

[0045] The principle of distributed InSAR terrain 3D reconstruction is to solve for the 3D coordinates of ground targets by simultaneously solving the distance equation, Doppler equation, and interferometric phase equation. The geometric relationships are as follows: Figure 1 In the diagram, O-XYZ represents the origin and three coordinate axes of the geocentric rectangular coordinate system. Let O be the vector pointing from the Earth's center O to the ground target P. The vector pointing from the geocenter O to the phase center S1 of the main satellite antenna. The slant range vectors from the phase centers S1 and S2 of the primary and secondary satellite antennas to the ground target P. The baseline vector pointing from the primary satellite to the secondary satellite.

[0046] in accordance with Figure 1 The distance equation, Doppler equation, and interference phase equation can be expressed as:

[0047] Distance equation:

[0048] Doppler equations:

[0049] Interference phase equation:

[0050] In the formula f d Main satellite Doppler frequency, Let λ be the velocity vector of the main star and λ be the wavelength. For the interference phase, R1 and R2 are The corresponding slant distance value. Solved using the orthogonal decomposition method of view vectors. This method requires establishing a VPQ coordinate system. The origin of the VPQ coordinate system is the phase center of the main satellite antenna. The V-axis is the direction of the main satellite velocity vector, the Q-axis is the direction of the cross product of the main satellite velocity vector and the baseline vector, and the P-axis forms a right-handed coordinate system with the V and Q axes. Three orthogonal bases are established on the V, P, and Q axes. They are respectively:

[0051]

[0052] According to the orthogonal decomposition method of view vectors, the VPQ coordinate system needs to be transformed into the geocentric rectangular coordinate system, then the distance equation can be expressed as:

[0053]

[0054] In VPQ coordinate system The unit vector whose components along the V, P, and Q axes can be expressed as:

[0055]

[0056] r v for Its projection onto the V-axis has the following value:

[0057]

[0058] The Doppler equation can be rewritten as:

[0059]

[0060] but:

[0061]

[0062] r p for The projection onto the P-axis has the following value:

[0063]

[0064] In the formula, β is and The included angle. In the triangle formed by S1, S2, and P, there are:

[0065]

[0066] Then r p It can be represented as:

[0067]

[0068] r q for The projection onto the Q-axis, because Since it is a unit vector, r can be calculated using the following formula. q :

[0069]

[0070] For distributed InSAR, the raw SAR data is typically focused onto the zero Doppler plane, at which point f d If = 0, then the distance equation can ultimately be expressed as:

[0071]

[0072] The above formula is the expression for the distributed InSAR terrain 3D reconstruction model. The parameters in the equation are: ground target 3D coordinates, satellite antenna phase center position, slant range, satellite velocity, baseline, and interferometric phase. If any 5 parameters are known, the remaining 1 unknown parameter can be calculated.

[0073] Step 2: Calculate the position and velocity of the satellite antenna phase center at the image center time.

[0074] The SAR image parameter file includes data such as satellite attitude, position, imaging time, and polarization. It provides the phase center positions and velocity vectors of several satellite antennas. By fitting a third-order polynomial, the antenna phase center positions and velocity vectors of the satellite at any given time can be calculated. The fitting polynomial is as follows:

[0075] X S =a0+a1t+a2t 2 +a3t 3

[0076] Y S =b0+b1t+b2t 2 +b3t 3

[0077] Z S =c0+c1t+c2t 2 +c3t 3

[0078] X v =d0+d1t+d2t 2 +d3t 3

[0079] Yv =e0+e1t+e2t 2 +e3t 3

[0080] Z v =f0+f1t+f2t 2 +f3t 3

[0081] In the formula, (X S Y S Z S (X) represents the phase center position of the satellite antenna. v Y v Z v ) represents the satellite velocity vector, a i b i c i d i e i f i (i = 0, 1, 2, 3) are the polynomial coefficients, and t is the azimuth time. Substituting the azimuth time of the image center into the fitting polynomial, the position and velocity of the satellite antenna phase center of the image center can be calculated.

[0082] Step 3: Calculate the three-dimensional spatial coordinates and slant distance of the ground target at the image center based on external DEM data.

[0083] First, the external DEM is oversampled. Then, based on the oversampled external DEM and the range-Doppler model, a SAR image is simulated that meets a preset condition regarding the grid size of the actual SAR image. The closer the two are, the better. Finally, the simulated SAR image and the actual SAR image are precisely registered, and a transformation table is established. The latitude and longitude coordinates of the center of the actual SAR image are found according to the transformation table and converted into geocentric rectangular three-dimensional coordinates. The transformation relationship is as follows:

[0084]

[0085] Where (X, Y, Z) are the three-dimensional rectangular coordinates in geocentric space, (B, L, H) are the latitude and longitude coordinates, N is the radius of the zonal circle, and e is the first eccentricity.

[0086] The slant range can be calculated based on the ground target's three-dimensional Cartesian coordinates at the image center, combined with the satellite position calculated in step 2. The formula is as follows:

[0087]

[0088] Step 4: Calculate the image center time baseline

[0089] The baseline refers to the line connecting the phase centers of the primary and secondary satellite antennas when observing the same ground target. Based on image registration, a one-to-one correspondence between pixels in the primary and secondary satellite images can be established. Then, according to the primary and secondary SAR satellite image parameter files and the method in step 2, the phase center position (S) of the primary and secondary satellite antennas corresponding to the image center position can be obtained. X1 S Y1 S Z1 ), (S X2 S Y2 S Z2 The baseline can be calculated using the following formula:

[0090]

[0091] There is no strict order between steps 3 and 4. Alternatively, the time baseline at the image center can be calculated first, and then the three-dimensional spatial coordinates and slant distance of the ground target at the image center can be calculated based on the external DEM data.

[0092] Step 5: Simulate the phase of the center position of near and far wavefront images

[0093] Based on steps 2, 3, and 4, the satellite antenna phase center position, velocity, ground three-dimensional coordinates, slant range, and baseline at the center of the near and far wave positions image can be calculated respectively. Substituting these parameters into the three-dimensional reconstruction model in step 1, the simulated phase at the center of the near and far wave positions image can be calculated respectively.

[0094] Step 6: Calculate the parallel and vertical baselines at the center positions of near and far wavefront images.

[0095] The baseline calculated in step 4 is a three-dimensional vector in a geocentric Cartesian coordinate system. The baseline is generally represented in the TCN coordinate system, which has its origin at the phase center of the primary satellite radar antenna, with the N-axis pointing towards the Earth's center. The cross product of the N-axis and the velocity vector is the C-axis. The T-axis forms a right-handed coordinate system with the C and N axes. The three orthogonal bases of the T, C, and N axes are... They are respectively:

[0096]

[0097] The baseline vector in the TCN coordinate system can then be expressed as:

[0098]

[0099] (B t B c B n ) represents the three-axis components in the TCN coordinate system, (B x B y B z() represents the three-axis components of the geocentric Cartesian coordinate system. Considering that distributed InSAR calculations are projected onto the zero-Doppler plane of the main image, there will be an extension baseline B. t =0, then in the CN plane, there exists Figure 2 The baseline geometric relationships and baseline transformation relationships are as follows:

[0100] B / / =B c sinθ+B n cosθ

[0101] B ⊥ =B c cosθ-B n sinθ

[0102] B c =B ⊥ cosθ+B / / sinθ

[0103] B n =B / / cosθ-B ⊥ sinθ

[0104] In the formula B / / B ⊥ Let θ be the parallel and vertical baselines, respectively, and θ be the incident angle of the corresponding main image. The parallel and vertical baselines at the center positions of the near and far wavefront images can be calculated using the above formula. The trigonometric functions in the formula can be calculated using the following formula:

[0105]

[0106]

[0107] Step 7: Add errors to the parallel and vertical baselines at the center positions of near and far wavefront images.

[0108] When acquiring near and far position images using distributed SAR satellites, the baseline deviation is assumed to be a constant, and parallel and vertical baseline errors are added based on this.

[0109] B / / ne =B / / n +B / / n_err

[0110] B ⊥ne =B ⊥n +B ⊥n_err

[0111] B / / fe =B / / f +B / / f_err

[0112]

[0113] In the formula B / / n B ⊥n For near-wavelength parallel and vertical baselines, B / / n_err B ⊥n_err The parallel and vertical baseline errors added to the near-wave position, B / / ne B ⊥ne The baseline value B is the one with the error added to the near-wave position. / / f B ⊥f For far-wave positions, parallel and vertical baselines, B / / f_err Parallel baseline error added for far-wave positions, B / / fe B ⊥fe The baseline value with added error was applied to the far-wave position. Based on the actual baseline error magnitude, B... / / n_err B ⊥n_err B / / f_err It is usually measured in millimeters, but can also be measured in centimeters.

[0114] Step 8: Calculate the elevation error value at the center of the near and far wavefront images.

[0115] Based on the baseline transformation relationship in step 6, the parallel and perpendicular baselines, after adding errors, are converted into the axis components of the TCN coordinate system, and then transformed to the geocentric Cartesian coordinate system. The transformation formula is as follows:

[0116]

[0117] The above formula can be used to obtain the baseline at the center of the near and far wavefront images. The parameters involved in step 5 include the satellite antenna phase center position, satellite velocity, slant range, and simulated phase at the center of the near and far wavefront images. Substituting these five parameters into the three-dimensional reconstruction model in step 1, the three-dimensional coordinates of the ground target at the center of the near and far wavefront images are calculated. Converting these coordinates to latitude and longitude coordinates, the elevation value at the center of the near and far wavefront images can be obtained. The elevation error can then be calculated using the following formula:

[0118] h n_err =H ne -H n

[0119] h f_err =H fe -H f

[0120] H ne H fe H represents the elevation at the center of the near and far position images after adding baseline error. n H f The elevations h at the center of the near and far position images provided by the external DEM are respectively. n_err hf_err These represent the calculated elevation errors at the center of the near and far wavefront images, respectively.

[0121] Step 9: Calculate the parallel and vertical baseline errors based on the near and far wave position joint baseline calibration model.

[0122] The parallel baseline calibration model is as follows:

[0123]

[0124] In the formula h err For elevation error, B / / err For parallel baseline error, h amb The fuzzy height is calculated using the following formula:

[0125]

[0126] In actual calculations, the slope distance R1 and the sine function of the incident angle sinθ in the formula can be obtained from external control data. Therefore, the results calculated in steps 5 and 6 can be used directly for the vertical baseline B. ⊥ Since the true value is unknown, the vertical baseline with error from step 7 is used, and the fuzzy height at the center of the near and far wavefront images can be calculated. Substituting the fuzzy height and the elevation error at the center of the near and far wavefront images from step 8 into the parallel baseline calibration model, the parallel baseline error at the center of the near and far wavefront images can be calculated, denoted as B. / / n_err1 B / / f_err1 The vertical baseline calibration model is established based on the baseline deviation of near and far position image pairs. It is established based on a fixed value, and the geometric relationship is as follows: Figure 3 The formula is expressed as follows:

[0127]

[0128] Decomposing the above equation onto the C and N axes, we get:

[0129]

[0130] θ n θ f These are the incident angles corresponding to the center positions of the main image in near and far-position images, respectively. k1 and k2 can be calculated using the above formula. This is the vertical baseline error vector of near and far wavefront images.

[0131] Step 10: Calculate the accuracy of the joint baseline calibration model for near and far wavelengths.

[0132] The difference between the calculated vertical and parallel baseline errors and the added vertical and parallel baseline errors is calculated.

[0133] B / / nΔ =B / / n_err1 -B / / n_err

[0134]

[0135] B / / fΔ =B / / f_err1 -B / / f_err

[0136]

[0137] B / / nΔ B ⊥nΔ B is the difference between the parallel and vertical baseline errors calculated for near-wave positions and the added parallel and vertical baseline errors. / / fΔ B ⊥fΔ The difference between the calculated parallel and vertical baseline errors for the far-wave position and the added parallel and vertical baseline errors. The final value is the mean B. / / Δ B ⊥Δ The accuracy of the near-far wave position joint baseline calibration model is evaluated; the smaller the value, the higher the accuracy.

[0138]

[0139]

[0140] The flowchart for verifying the accuracy of the distributed SAR satellite near-far wave position joint baseline calibration model is shown below. Figure 4 .

[0141] The above description is an embodiment of the present invention, and the scope of protection of the present invention should not be limited by this description. Those skilled in the art should understand that any modifications or partial substitutions based on the technical solutions of the present invention fall within the scope of protection of the claims of the present invention.

[0142] The contents not described in detail in this specification are common knowledge to those skilled in the art.

Claims

1. A method for verifying the accuracy of a SAR satellite near-far wavefront joint baseline calibration model, characterized in that... include: Constructing a distributed InSAR terrain 3D reconstruction model; Calculate the satellite antenna phase center position and velocity at the time of the near and far wavefront image center; obtain the three-dimensional coordinates and slant range of the ground target at the near and far wavefront image center based on external DEM data and antenna phase center position, and obtain the baseline at the time of the near and far wavefront image center; calculate the phase of the near and far wavefront image center position. Add errors to the baseline and obtain the elevation error value at the center of the near and far position images; calculate the baseline error based on the near and far position joint baseline calibration model. The accuracy of the near-far wavelength joint baseline calibration model is obtained by comparing the added baseline error with the baseline error calculated using the near-far wavelength joint baseline calibration model.

2. The method for verifying the accuracy of a SAR satellite near-far wave position joint baseline calibration model according to claim 1, characterized in that: To add errors to the baseline, firstly, based on geometric relationships, the baselines at the center time of the near and far wave positions images are transformed from the geocentric rectangular coordinate system to the TCN coordinate system, and then transformed into parallel and vertical baselines; then, using the baseline deviation as a constant value as a benchmark, errors are added to the parallel and vertical baselines at the center time of the near and far wave positions images respectively.

3. The method for verifying the accuracy of a SAR satellite near-far wave position joint baseline calibration model according to claim 2, characterized in that: The parallel and vertical baselines are achieved using the following formulas. in, They are parallel and vertical baselines, respectively. Let c be the c-axis and n-axis components of the baseline in the TCN coordinate system. This is the incident angle corresponding to the main image.

4. The method for verifying the accuracy of a SAR satellite near-far wave position joint baseline calibration model according to claim 3, characterized in that: The parallel and vertical baselines at the center time of near and far position images after adding errors are achieved using the following formulas. in, To add errors to the near-wavelength parallel and vertical baselines, For near-wavelength parallel and vertical baselines, For the far-wave parallel baseline and vertical baseline, The far-wave parallel baseline and vertical baseline values ​​after adding errors. To add near-wavelength parallel baseline error and vertical baseline error, This is for the added far-wave parallel baseline error.

5. A method for verifying the accuracy of a SAR satellite near-far wavefront joint baseline calibration model according to claim 1 or 2, characterized in that: The elevation error value at the center of the near and far wavefront images is calculated by the following steps: inputting the baseline, satellite antenna phase center position, velocity, slant range, and phase after adding the error into the 3D reconstruction model to obtain the 3D coordinates of the ground target at the center of the near and far wavefront images; converting the coordinates into latitude and longitude coordinates to obtain the elevation value at the center of the near and far wavefront images; and obtaining the elevation error value by comparing it with the elevation at the center of the near and far wavefront images in the external DEM.

6. The method for verifying the accuracy of a SAR satellite near-far wave position joint baseline calibration model according to claim 1, characterized in that: The parallel baseline error calculated based on the joint near-far wavelength baseline calibration model is achieved using the following formula. in, For parallel baseline error, For wavelength, For elevation error, For fuzzy high.

7. The method for verifying the accuracy of a SAR satellite near-far wave position joint baseline calibration model according to claim 1, characterized in that: The vertical baseline error calculated based on the joint near-far wavelength baseline calibration model is achieved using the following formula. in, For the baseline error vector, This is the near-wave parallel baseline error vector. For the far-wave parallel baseline error vector, This is the near-wave vertical baseline error vector. Vertical baseline error vector at far-wave position.

8. The method for verifying the accuracy of a SAR satellite near-far wave position joint baseline calibration model according to claim 7, characterized in that: The accuracy of the near-far wavefront joint baseline calibration model is as follows: To conduct an evaluation, in, For near-wavelength parallel baseline error, To add near-wave parallel baseline error, For the parallel baseline error at the far-wave position, To add the parallel baseline error at the far-wave position, This refers to the near-wave vertical baseline error. For the vertical baseline error of the far-wave position, This is for the added near-wave vertical baseline error.

9. The method for verifying the accuracy of a SAR satellite near-far wave position joint baseline calibration model according to claim 1, characterized in that: The distributed InSAR terrain 3D reconstruction model is implemented using the following formula. in, The vector pointing from the Earth's center to the ground target. The vector pointing from the Earth's center to the phase center of the main satellite antenna. The slant range from the phase center of the main satellite antenna to the ground target. The baseline pointing from the primary satellite to the secondary satellite. These are three orthogonal bases on the V, P, and Q axes. , The main star's velocity vector, For interference phase, For wavelength, for Projection on the P-axis In VPQ coordinate system The unit vector.

10. The method for verifying the accuracy of a SAR satellite near-far wave position joint baseline calibration model according to claim 1, characterized in that: The calculation of the three-dimensional coordinates of the ground target at the center of the near and far wavefront images is achieved through the following steps: First, the external DEM is oversampled. Then, based on the oversampled external DEM and the range-Doppler model, a SAR image with a grid size that meets the preset conditions is simulated and the actual SAR image is simulated. Finally, the simulated SAR image is registered with the actual SAR image, a transformation table is established, the latitude and longitude coordinates of the center of the actual SAR image are obtained according to the transformation table, and then they are converted into geocentric rectangular three-dimensional coordinates.

Images