Dual-frequency InSAR absolute interferometric phase correction method based on prior terrain / flat ground information

Abstract

The invention discloses a dual-frequency InSAR (Interferometric Synthetic Aperture Radar) absolute interferometric phase correction method based on prior terrain / flat ground information, and belongs to the technical field of interferometric synthetic aperture radar data processing. The method comprises the following steps: firstly, carrying out interference preprocessing on a dual-frequency SAR single-view complex image to obtain a dual-frequency unwrapping interference phase; secondly, constructing a proportional function of a dual-frequency unwrapping interference phase and a phase fuzzy number, deforming the proportional function to obtain noise distribution, performing Gaussian fitting on the noise distribution of the screened pixel points to obtain noise digital characteristics, and forming an equation by using a proportional function deformation form and a noise mean value; and obtaining an estimated value of a phase ambiguity number through two-dimensional search, and finally obtaining a corrected dual-frequency absolute interference phase. According to the invention, estimation of the dual-frequency phase ambiguity number can be realized without depending on a control point and high-precision prior terrain information, correction of the dual-frequency absolute interferometric phase is realized, and the speed of correction of the dual-frequency absolute interferometric phase is improved.

Description

Technical Field

[0001] The invention belongs to the technical field of interferometric synthetic aperture radar data processing, and in particular relates to a dual-frequency InSAR absolute interferometric phase correction method based on prior terrain / flat land information. Background Art

[0002] Interferometric Synthetic Aperture Radar (InSAR) has been widely studied for its ability to perform large-scale elevation mapping and surface deformation monitoring under all-day, all-weather conditions, utilizing the phase difference (interferometric phase) between pairs of SAR single-look complex images of the same ground area. InSAR uses the absolute interferometric phase to determine the slant range difference between the primary and secondary antennas, and then inverts the elevation based on the spatial geometric relationship between the primary and secondary antennas and the ground targets. Therefore, to ensure the accuracy of the inverted elevation, a precise absolute interferometric phase is required when converting the interferometric phase to elevation. However, due to factors such as phase ambiguity at the unwrapping starting point during the interferometric phase unwrapping process, a phase difference of an integer number of periods between the unwrapped interferometric phase and the absolute interferometric phase can occur. Therefore, it is necessary to calculate the phase ambiguity number before converting the interferometric phase to elevation and correct the unwrapped interferometric phase to the absolute interferometric phase. If the phase ambiguity number is calculated inaccurately, that is, the absolute interferometric phase differs from the true interferometric phase by an integer number of phase periods, the final inverted elevation will differ from the true elevation by an integer number of ambiguities, seriously affecting the absolute accuracy of the elevation inversion result. Therefore, calculating the absolute interferometric phase after fuzzy number correction is one of the key technologies of InSAR.

[0003] Based on different phase ambiguity number estimation methods, existing single-frequency InSAR absolute interferometric phase corrections are divided into two categories. One is to estimate the phase ambiguity number based on ground control points, and the other is to estimate the phase ambiguity number based on prior terrain information. The first method is limited by the placement of control points. Due to economic cost considerations or terrain reasons, control points may not be placed in the surveying area, and the control point information cannot be used to calculate the absolute interferometric phase for correction. The second method is limited by the accuracy of prior terrain information. There is a certain error between the existing DEM data and the actual terrain elevation. If the DEM data corresponding to the surveying area has a large error, there will be a deviation between the absolute interferometric phase calculated by it and the actual interferometric phase, which will affect the phase ambiguity number estimation.

[0004] The above two types of single-frequency InSAR absolute interferometric phase correction methods are highly dependent on control points and high-precision DEM data. If there are no control points in the surveying area or the DEM data used is of low precision, the phase ambiguity number cannot be correctly estimated. Summary of the Invention

[0005] The present invention provides a dual-frequency InSAR absolute interferometry phase correction method based on prior terrain / flatland information, improving absolute interferometry phase accuracy without relying on control points or high-precision prior terrain information. Leveraging the complementary nature of dual-frequency InSAR data—namely, the frequency-dependent proportional relationship between the reference terrain interferometry phase, the flatland interferometry phase, and the absolute interferometry phase—the present invention proposes a new dual-frequency InSAR absolute interferometry phase correction method based on prior terrain / flatland information, achieving high-precision absolute interferometry phase correction without relying on control points or high-precision prior terrain information.

[0006] A dual-frequency InSAR absolute interferometry phase correction method based on prior terrain / flatland information includes the following steps:

[0007] Step 1: Acquire a dual-frequency SAR single-look complex image pair and perform interferometric preprocessing to obtain the unwrapped interferometric phase of the dual-frequency band;

[0008] Interference preprocessing includes interference image pair registration, reference terrain interference phase removal / flat ground interference phase removal, interference phase filtering, and interference phase unwrapping.

[0009] The specific implementation steps of reference terrain interferometry phase removal / flat land interferometry phase removal in interferometry preprocessing are as follows:

[0010] (1) For reference terrain interferometric phase removal, obtain the prior DEM data within the scope of the studied scene; for flat land interferometric phase removal, obtain the longitude and latitude information within the scope of the studied scene, and set the elevation information to 0 or other constants;

[0011] (2) Project the acquired prior DEM data / flat land data into the SAR image coordinate system;

[0012] (3) Calculate the reference primary and secondary slant ranges of the primary and secondary antennas from the prior ground targets using the orbital data and the prior DEM data / flat ground data projected into the SAR image coordinate system;

[0013] (4) The corresponding components of the reference terrain interferometry phase / flat ground interferometry phase in the SAR primary and auxiliary images are removed using the reference primary and auxiliary slant ranges and the radar signal wavelength.

[0014] Step 2: Estimate the phase ambiguity number and correct the dual-frequency unwrapped interferometric phase to the absolute interferometric phase;

[0015] The specific steps include:

[0016] Step 2.1: Construct the ratio function of the dual-frequency unwrapping interferometer phase and phase ambiguity number;

[0017] The relationship between the actual interference phase, the slant range difference between the primary and secondary antennas, and the radar signal wavelength is as follows:

[0018]

[0019] Where u is the coefficient. If it is a single-base system, the coefficient u is 1. If it is a double-base system, the coefficient u is 2. s is the slant range from the auxiliary antenna to the ground target, R m is the slant range from the main antenna to the ground target. λ is the wavelength of the radar signal.

[0020] Based on formula (1), the proportional function of the dual-frequency unwrapping interferometer phase and phase ambiguity number is constructed as follows:

[0021]

[0022] where φ unwrapi 、φ refi 、k i ,λ i They represent the unwrapped interferometric phase of a certain frequency band, the reference terrain interferometric phase / flat ground interferometric phase, the phase ambiguity number, and the radar signal wavelength, respectively, i=1,2.

[0023] Step 2.2: Use the proportional function to transform the noise to obtain the statistical results, and fit the noise distribution to obtain the noise digital characteristics, that is, the noise mean;

[0024] The specific implementation steps are:

[0025] (1) Eliminate the reference terrain phase / flat ground phase term in the proportional function by utilizing the inverse proportional relationship between the dual-frequency reference terrain phase / flat ground phase and the radar signal wavelength under the same spatial geometric relationship;

[0026] The calculation method of dual-frequency reference terrain interferometry phase / flat ground interferometry phase is as follows:

[0027]

[0028] where R sref R is the slant range from the auxiliary antenna to the ground target in the reference terrain / reference flat ground. mref R is the slant range from the main antenna to the ground target under the reference terrain / reference flat ground. sref and R mref Remains unchanged when calculating dual-frequency reference terrain phase / flat ground phase.

[0029] For the dual-frequency reference terrain interferometry phase / flat ground interferometry phase under the same terrain, the following proportional relationship should be maintained with the radar signal wavelength:

[0030]

[0031] (2) Transform the proportional function so that the left side of the equation contains the dual-frequency phase ambiguity number to be estimated, and the right side of the equation contains the processed dual-frequency unwrapped phase and wavelength, and the right side of the equation is set to noise v;

[0032] Based on formula (4), the terms related to the dual-frequency reference terrain interferometry phase / flat ground interferometry phase in formula (2) can be eliminated, and the transformation of the proportional function is obtained by transforming the equation as follows:

[0033]

[0034] Let the right side of the equation be the noise v.

[0035] (3) Calculate the correlation coefficients corresponding to all pixels in the studied scene and set a threshold to filter out pixels with high correlation coefficients;

[0036] (4) Calculate the noise value corresponding to the pixel point after screening to obtain the statistical result of the noise, perform Gaussian fitting on the obtained noise statistical result, and obtain the corresponding first-order digital feature, that is, the mean.

[0037] Step 2.3: Estimate the phase ambiguity number based on the noise digital characteristics (mean) and the proportional function variant to obtain the dual-frequency absolute interferometric phase;

[0038] (1) Using the proportional function deformation and the noise mean to form an equation, a two-dimensional search is performed to obtain the dual-frequency phase ambiguity number.

[0039] The proportional function deformation and the noise mean m form the equation as follows:

[0040]

[0041] Based on formula (6), a two-dimensional search is performed on the estimated dual-frequency phase ambiguity numbers k1 and k2, so that the estimated value of the dual-frequency phase ambiguity number is The following relationship is satisfied:

[0042]

[0043] (2) Multiply the phase ambiguity number obtained by the search by 2π, and add the reference terrain interferometry phase / flat ground interferometry phase and the unwrapped interferometry phase obtained in step 1 to obtain the corrected dual-frequency absolute interferometry phase:

[0044]

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] (1) By introducing the proportional function of the dual-frequency unwrapped interferometer phase and the phase ambiguity number, the method of the present invention can estimate the dual-frequency phase ambiguity number without relying on control points and high-precision prior terrain information, thereby correctly correcting the dual-frequency absolute interferometer phase and providing reliable absolute interferometer phase support for accurate reconstruction of dual-frequency InSAR terrain.

[0047] (2) The method of the present invention estimates the dual-frequency phase ambiguity number simultaneously, that is, realizes the dual-frequency absolute interference phase correction simultaneously, avoids two correction operations, and improves the speed of dual-frequency absolute interference phase correction. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 This is a flow chart of the dual-frequency InSAR absolute interferometry phase correction method based on prior terrain / flatland information of the present invention;

[0049] Figure 2 is the interference phase diagram of the Ku band generated by simulation in an embodiment of the present invention;

[0050] Figure 3 is an X-band interference phase diagram generated by simulation in an embodiment of the present invention;

[0051] Figure 4 is the interference phase diagram of the Ku band after removing the reference terrain interference phase in the embodiment of the present invention;

[0052] Figure 5 is an interferometric phase diagram of the X-band in an embodiment of the present invention after removing the reference terrain interferometric phase;

[0053] Figure 6 is the unwrapped interferometric phase diagram of the Ku band in an embodiment of the present invention;

[0054] Figure 7 is an unwrapped interferometric phase diagram of the X-band in an embodiment of the present invention;

[0055] Figure 8 1 is a noise distribution histogram and a fitting result diagram in an embodiment of the present invention;

[0056] Figure 9 is the Ku-band absolute interferometric phase image corrected based on the priori terrain information method in an embodiment of the present invention;

[0057] Figure 10 is an X-band absolute interferometry phase image corrected based on a priori terrain information method in an embodiment of the present invention;

[0058] Figure 11 is the Ku-band absolute interferometric phase diagram after correction by the method of the present invention in an embodiment of the present invention;

[0059] Figure 12This is the X-band absolute interference phase diagram after correction by the method of the present invention in an embodiment of the present invention. DETAILED DESCRIPTION

[0060] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0061] The present invention proposes a dual-frequency InSAR absolute interferometry phase correction method based on prior terrain / flatland information. First, a proportional function between the dual-frequency unwrapped interferometry phase and the phase ambiguity number is constructed. The proportional function is then deformed to obtain a noise distribution. The noise distribution of the filtered pixels is Gaussian fitted to obtain the first-order digital feature (mean). The proportional function deformation and the mean of the noise are used to form an equation. Then, a two-dimensional search is performed to obtain an estimated value of the phase ambiguity number, and finally the corrected dual-frequency absolute interferometry phase is obtained. Figure 1 , the specific implementation method includes the following steps:

[0062] Step 1: Obtain dual-frequency InSAR data and its orbital parameters collected by synthetic aperture radar; perform interferometric preprocessing on the dual-frequency SAR single-look complex image, including interferometric image pair registration, reference terrain interferometric phase removal / flat ground interferometric phase removal, interferometric phase filtering, and interferometric phase unwrapping, ultimately obtaining the dual-frequency unwrapped interferometric phase.

[0063] Among them, the specific implementation steps of interference image pair registration are:

[0064] (1) Registration of two dual-frequency SAR main images;

[0065] (2) The auxiliary SAR images of each frequency band are registered with the main SAR images of the corresponding frequency bands in (1).

[0066] The reference terrain interferometry phase removal / flat-land interferometry phase removal steps indicate that both reference terrain interferometry phase removal and flat-land interferometry phase removal can be used in the present invention.

[0067] The specific implementation steps of reference terrain interferometry phase removal / flat ground interferometry phase removal in interferometry preprocessing are as follows:

[0068] (1) If the reference terrain interferometry phase removal is used, the prior DEM data within the approximate range of the studied scene is obtained. If the reference terrain interferometry phase removal is used, the latitude and longitude information within the approximate range of the studied scene is obtained. The elevation information can be set to 0 or other constants.

[0069] (2) The acquired prior DEM data / flat land data are projected into the SAR image coordinate system;

[0070] (3) Calculate the reference primary and secondary slant ranges of the primary and secondary antennas from the prior ground targets using the orbital data and the prior DEM data / flat ground data projected into the SAR image coordinate system;

[0071] (4) The corresponding components of the reference terrain interferometry phase / flat ground interferometry phase in the SAR primary and auxiliary images are removed using the reference primary and auxiliary slant ranges and the radar signal wavelength.

[0072] According to the above scheme, the accuracy requirement for the priori terrain information in the reference terrain interferometric phase removal in the interferometric preprocessing is low, and the absolute error and relative error of the priori terrain information are allowed.

[0073] Step 2: Estimate the phase ambiguity number and correct the dual-frequency unwrapped interferometer phase to the absolute interferometer phase. The specific steps are as follows:

[0074] Step 2.1: Construct the ratio function of the dual-frequency unwrapping interferometer phase and phase ambiguity number;

[0075] The phase ambiguity number k is the integer number of cycles corresponding to the phase difference between the absolute interferometric phase and the sum of the unwrapped interferometric phase and the reference terrain interferometric phase / flat ground interferometric phase.

[0076] The proportional function of the dual-frequency unwrapped interferometry phase and the phase ambiguity number is related to the dual-frequency unwrapped interferometry phase, the dual-frequency reference terrain interferometry phase / dual-frequency flat-terrain interferometry phase, the dual-frequency phase ambiguity number, and the wavelength of the dual-frequency radar signal. Since the interferometry phase is proportional to the slant range difference between the primary and secondary SAR images and inversely proportional to the wavelength of the radar signal, the ratio of the dual-frequency absolute interferometry phases should be inversely proportional to the wavelength ratio of the dual-frequency radar signals, provided the spatial geometry is consistent.

[0077] The relationship between the actual interference phase, the slant range difference between the main and auxiliary antennas, and the radar signal wavelength is as follows:

[0078]

[0079] Where u is the coefficient. If it is a single-base system, the coefficient u is 1. If it is a double-base system, the coefficient u is 2. s is the slant range from the auxiliary antenna to the ground target, R m is the slant range from the main antenna to the ground target. λ is the wavelength of the radar signal.

[0080] Based on formula (1), the proportional function of the dual-frequency unwrapping interferometer phase and phase ambiguity number is constructed as follows:

[0081]

[0082] where φ unwrapi 、φ refi 、k i ,λ i They represent the unwrapped interferometric phase of a certain frequency band, the reference terrain interferometric phase / flat ground interferometric phase, the phase ambiguity number, and the radar signal wavelength respectively.

[0083] Step 2.2: Since the dual-frequency SAR primary and secondary images are acquired in the same spatial geometric relationship, the dual-frequency reference terrain interferometry phase / flat ground interferometry phase is calculated as follows:

[0084]

[0085] where R sref R is the slant range from the auxiliary antenna to the ground target in the reference terrain / reference flat ground. mref R is the slant range from the main antenna to the ground target under the reference terrain / reference flat ground. sref and R mref Remains unchanged when calculating dual-frequency reference terrain phase / flat ground phase.

[0086] Therefore, for the dual-frequency reference terrain interferometry phase / flat ground interferometry phase under the same terrain, the following proportional relationship should be maintained with the radar signal wavelength:

[0087]

[0088] Since the calculation of the dual-frequency reference terrain interferometry phase only depends on the same orbital parameters, the same prior terrain information and the wavelength of each radar signal, the proportional relationship of formula (4) can still be well maintained even when there is a large error between the prior terrain information used and the actual terrain information.

[0089] Based on formula (4), the terms related to the dual-frequency reference terrain interferometry phase / flat ground interferometry phase in formula (2) can be eliminated, and the transformation of the proportional function is obtained by transforming the equation as follows:

[0090]

[0091] Let the right side of the equation be the noise v.

[0092] The correlation coefficients for all pixels in the studied scene are calculated, and a threshold is set to select pixels with high correlation coefficients for subsequent estimation. The threshold is set based on experience; correlation coefficients above 0.7 to 0.8 are generally considered reliable. The noise values ​​corresponding to the selected pixels are calculated using the processed dual-frequency unwrapped interferometric phase and the known wavelength to obtain noise statistics. Since the noise in the interferometric phase generally follows a Gaussian distribution, the obtained noise statistics are Gaussian-fitted to obtain the corresponding first-order digital feature—the mean m.

[0093] Step 2.3: Based on formula (5) and the noise mean value calculated in step 2.2, construct the following equation:

[0094]

[0095] From formula (6), we can see that the left side of the equation contains two unknowns, namely the dual-frequency phase ambiguity numbers k1 and k2, while there is only one equation. If formula (6) is regarded as an equation, the number of unknowns in the equation is greater than the number of equations, that is, it is an underdetermined equation, and the phase ambiguity number cannot be estimated using methods such as the least squares method. Therefore, the method of the present invention utilizes the limitation that the phase ambiguity number is an integer and performs a two-dimensional search on the dual-frequency phase ambiguity numbers k1 and k2 to be estimated based on formula (6). So that the estimated value of the dual-frequency phase ambiguity number is The following relationship is satisfied:

[0096]

[0097] The dual-frequency phase ambiguity estimate Substitute the following formula to calculate the corrected dual-frequency absolute interferometry phase:

[0098]

[0099] Experimental results

[0100] To illustrate the effectiveness of the present invention, this embodiment is experimentally verified on dual-frequency InSAR data.

[0101] The experiment was conducted by simulating the system parameters shown in Table 1 to obtain the primary and secondary SAR images of the Ku band and the X band, and absolute interferometric phase correction was performed on the dual-frequency simulation data using the steps in the specific implementation method.

[0102] Table 1 Simulation parameters of dual-frequency InSAR system

[0103]

[0104] Figure 2 and Figure 3 These are the interference phase diagrams of Ku band and X band generated by simulation respectively.

[0105] Figure 4 and Figure 5 The interferometric phase maps for the Ku and X bands are shown after the reference terrain interferometry phase is removed. Since the simulation data is based on SRTM (Shuttle Radar Topography Mission) data, the prior DEM data used for the reference terrain interferometry phase removal is based on the SRTM data with noise uniformly distributed between 10 and 30 meters added to simulate low-precision prior DEM data. Because the prior DEM data used is less accurate and does not align with the actual terrain data, the interferometric phase after the reference terrain interferometry phase removal still contains residual terrain interferometry phase.

[0106] Figure 6 and Figure 7 These are the unwrapped interferometric phase diagrams of the Ku band and X band, respectively.

[0107] Figure 8 The noise distribution histogram and fitting results are shown in Figure 2. The blue column represents the noise distribution, the red line is the fitted Gaussian distribution curve, and the green line is the mean corresponding to the fitted Gaussian distribution. It can be seen that the Gaussian distribution fits the noise distribution well, indicating that the mean corresponding to the fitted Gaussian distribution is highly reliable.

[0108] The following compares the phase ambiguity number estimation value obtained by the method of the present invention using dual-frequency information and the phase ambiguity number estimation value obtained by the comparative example based on prior terrain information using only single-frequency information. The two sets of estimation results and the true value of the phase ambiguity number are shown in Table 2 below.

[0109] Table 2 Comparison of absolute interferometric phase correction methods

[0110]

[0111] A comparison shows that the estimated phase ambiguity numbers for the Ku and X bands obtained using the method based on prior terrain information deviate significantly from their true values. This is due to errors between the prior terrain information and the actual terrain information. However, the estimated phase ambiguity numbers for the Ku and X bands obtained using the method of the present invention are consistent with their true values, demonstrating that the proposed method, without relying on control points or high-precision prior terrain information, can estimate phase ambiguity numbers with high accuracy.

[0112] Figure 9 and Figure 10 These are the absolute interferometric phase images of the Ku band and X band after correction based on the prior terrain information method. Figure 11 and Figure 12 The following are the absolute interferometric phase diagrams for the Ku-band and X-band, respectively, after correction using the method of the present invention. To further quantitatively evaluate the accuracy of the corrected absolute interferometric phase, the error and root mean square error of the corrected absolute interferometric phase using the two methods were calculated using landmark points, as shown in Table 3.

[0113] Table 3 Absolute interferometry phase accuracy evaluation

[0114]

[0115] By comparison, the errors of each marking point and the root mean square error of the absolute interferometric phase corrected by the method of the present invention are smaller than those corrected by the method based on prior terrain information, which proves the superiority of the method of the present invention.

[0116] The above embodiments are intended only to illustrate the design concepts and features of the present invention. Their purpose is to enable those skilled in the art to understand the contents of the present invention and implement them accordingly. The scope of protection of the present invention is not limited to the above embodiments. Therefore, any equivalent changes or modifications made based on the principles and design concepts disclosed in the present invention are within the scope of protection of the present invention.

Claims

1. A dual-frequency InSAR absolute interferometry phase correction method based on prior terrain / flatland information, characterized in that: The following steps are involved: Step 1: Obtain a dual-frequency SAR single-view complex image pair and perform interferometric preprocessing to obtain the unwrapped interferometric phase of the dual-frequency band; Step 2: estimate the phase ambiguity number and correct the dual-frequency unwrapped interferometric phase to the absolute interferometric phase; The specific steps include: Step 2.1: Construct the proportional function of the dual-frequency unwrapping interferometer phase and the phase ambiguity number as follows: Among them, φ unwrapi 、φ refi 、k i ,λ i Respectively represent the unwrapped interferometric phase of a certain frequency band, the reference terrain interferometric phase / flat ground interferometric phase, the phase ambiguity number, and the radar signal wavelength, i = 1, 2; Step 2.2: Use the proportional function to transform the noise to obtain the statistical results, and fit the noise distribution to obtain the noise digital characteristics, that is, the noise mean; Step 2.3: Estimate the phase ambiguity number based on the noise digital characteristics and the proportional function variant to obtain the dual-frequency absolute interferometric phase; (1) Using the proportional function deformation and the noise mean to form an equation, a two-dimensional search is performed to obtain the dual-frequency phase ambiguity number; The proportional function deformation and the noise mean m form the equation as follows: Based on formula (2), a two-dimensional search is performed on the estimated dual-frequency phase ambiguity numbers k1 and k2, so that the estimated value of the dual-frequency phase ambiguity number is The following relationship is satisfied: (2) Multiply the phase ambiguity number obtained by the search by 2π, and add the reference terrain interferometry phase / flat ground interferometry phase and the unwrapped interferometry phase obtained in step 1 to obtain the corrected dual-frequency absolute interferometry phase:

2. The dual-frequency InSAR absolute interferometry phase correction method based on prior terrain / flatland information according to claim 1, characterized in that: The interference preprocessing includes interference image pair registration, reference terrain interference phase removal / flat ground interference phase removal, interference phase filtering, and interference phase unwrapping.

3. The dual-frequency InSAR absolute interferometry phase correction method based on prior terrain / flatland information according to claim 2, characterized in that: The specific implementation steps of interference image pair registration are: (1) Registration of two dual-frequency SAR main images; (2) The auxiliary SAR images of each frequency band are registered with the main SAR images of the corresponding frequency bands in (1).

4. The dual-frequency InSAR absolute interferometry phase correction method based on prior terrain / flatland information according to claim 2, characterized in that: The specific implementation steps of terrain interferometry phase removal / flat land interferometry phase removal are as follows: (1) For reference terrain interferometric phase removal, obtain the prior DEM data within the scope of the studied scene; for flat land interferometric phase removal, obtain the longitude and latitude information within the scope of the studied scene, and set the elevation information to 0 or other constants; (2) Project the acquired prior DEM data / flat land data into the SAR image coordinate system; (3) Calculate the reference primary and secondary slant ranges of the primary and secondary antennas from the prior ground targets using the orbital data and the prior DEM data / flat ground data projected into the SAR image coordinate system; (4) The corresponding components of the reference terrain interferometry phase / flat ground interferometry phase in the SAR primary and auxiliary images are removed using the reference primary and auxiliary slant ranges and the radar signal wavelength.

5. The dual-frequency InSAR absolute interferometry phase correction method based on prior terrain / flatland information according to claim 1, characterized in that: The calculation process of the noise mean is: (1) Eliminate the reference terrain phase / flat ground phase term in the proportional function by utilizing the inverse proportional relationship between the dual-frequency reference terrain phase / flat ground phase and the radar signal wavelength under the same spatial geometric relationship; The calculation method of dual-frequency reference terrain interferometry phase / flat ground interferometry phase is as follows: where R sref R is the slant range from the auxiliary antenna to the ground target in the reference terrain / reference flat ground. mref R is the slant range from the main antenna to the ground target under the reference terrain / reference flat ground; sref and R mref Remains unchanged when calculating dual-frequency reference terrain phase / flat ground phase; For the dual-frequency reference terrain interferometry phase / flat ground interferometry phase under the same terrain, the following proportional relationship should be maintained with the radar signal wavelength: (2) Transform the proportional function so that the left side of the equation contains the dual-frequency phase ambiguity number to be estimated, and the right side of the equation contains the processed dual-frequency unwrapped phase and wavelength, and the right side of the equation is set to noise v; Based on formula (6), the terms related to the dual-frequency reference terrain interferometry phase / flat ground interferometry phase in formula (1) can be eliminated, and the transformation of the proportional function is obtained by transforming the equation as follows: Set the right side of the equation to noise v; (3) Calculate the correlation coefficients corresponding to all pixels in the studied scene and set a threshold to filter out pixels with high correlation coefficients; (4) Calculate the noise value corresponding to the pixel point after screening to obtain the statistical result of the noise, perform Gaussian fitting on the obtained noise statistical result, and obtain the corresponding first-order digital feature, that is, the mean.

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