Surface deformation measurement method and system based on different star different imaging mode SAR data

Abstract

The application provides a kind of surface deformation measurement method and system based on different imaging mode SAR data, comprising: obtaining different imaging mode SAR image data;Register SAR image data, obtain the slant range difference of main and auxiliary images, resampled main image and registered auxiliary image;Obtain the main and auxiliary images after downsampling;Interferometric processing obtains surface deformation information and outputs.The application constructs the end-to-end processing framework of different imaging mode SAR data, effectively reduces the spatial baseline incoherence risk of different imaging mode SAR system, ensures the space-time correlation of different star data;Through the whole link innovation of orbit design, joint registration, spectrum matching and terrain residual suppression, the cross-platform data interference incoherence bottleneck is broken, the registration error problem caused by spectrum shift and resolution difference of different imaging mode data is solved, and a systematic solution is provided for high-frequency and high-precision surface deformation monitoring;Through terrain phase separation technology, terrain residual is effectively suppressed.

Description

Technical Field

[0001] This invention belongs to the field of radar interferometry technology, specifically, it relates to a method and system for measuring surface deformation based on SAR data with different imaging modes, and in particular, it relates to a differential interferometry method based on synthetic aperture radar (SAR) data with different imaging modes for high-precision surface deformation monitoring. Background Technology

[0002] Surface deformation monitoring is a core technological requirement in fields such as geological disaster early warning, urban safety assessment, and resource exploration. Among numerous monitoring methods, differential interferometric synthetic aperture radar (D-InSAR) technology has become an important technical means for monitoring minute surface displacements due to its all-weather observation capabilities, sub-centimeter-level deformation measurement accuracy, and wide-area coverage.

[0003] However, the strong constraints of traditional D-InSAR technology on data sources severely limit its application effectiveness: if single-satellite revisit data is used, although the data homogeneity can be guaranteed, it is limited by the satellite revisit cycle (usually 8 to 30 days), making it difficult to capture the instantaneous deformation characteristics of sudden geological disasters such as earthquakes and landslides in a timely manner; if heterogeneous satellite data is used, although the time resolution bottleneck can be broken, significant systematic errors will be introduced by the differences in imaging modes (such as resolution, spectral characteristics, orbital parameters, etc.) of different satellite platforms.

[0004] The paper "Multidimensional time-series analysis of ground deformation from multiple InSAR data sets applied to Virunga Volcanic Province" (Samsonov SV, d'Oreye N. et al. Geophysical Research Letters, 2017) proposes a novel multidimensional small baseline subset method. This method utilizes the integration of multiple InSAR datasets, allowing the combination of airborne and spaceborne SAR data with different acquisition parameters, resolutions, bands, and polarizations to calculate the deformation of the observed area in two-dimensional or three-dimensional time series. However, it does not address the problem of interferometric phase decoherence caused by different imaging modes (such as different resolutions and spectral center differences), and it does not design an algorithm for spectral alignment and resolution adaptation.

[0005] The paper "Algorithm and Accuracy Analysis of Phase-Compensated SAR Differential Interferometric Extraction of Mountainous DEM" (Xiao Jinqun et al., Journal of Wuhan University, 2012) proposes to reduce the fringe rate of the interferogram by differentiating the deflating interferometric phase and the terrain phase simulated by the external DEM. Then, the simulated terrain phase is used to compensate the unwrapped phase of the differential interferogram to obtain the unwrapped phase of the deflating interferogram. This phase is then used for baseline refinement and elevation extraction, which can effectively reduce the influence of residual system phase and random phase errors introduced by unwrapping and external DEM. However, this method relies on the same source data (same satellite or same mode) and does not consider the terrain phase residual introduced by the slant range difference of different imaging modes.

[0006] The paper "Baseline Refinement and DEM Accuracy Analysis during the On-orbit Testing Phase of LuTan-1 Interferometric SAR" (Song Xinyou et al., Acta Geodaetica et al., 2024) proposes an iterative baseline refinement estimation method based on Fast Fourier Transform (FFT). Based on the corrected baseline, a digital elevation model (DEM) reconstruction of the study area was carried out. The paper also comprehensively evaluates and analyzes the quality of LuTan-1 products using other datasets, effectively correcting residual baseline errors. However, this paper only addresses single-satellite or same-mode data and does not address registration offsets caused by geometric baseline differences in heterogeneous data sources.

[0007] The patent document "Synthetic Aperture Radar System Based on Time Series Interferometric Deformation Measurement" (CN216411556U) proposes to preprocess SAR image sets, remove flat and terrain phases from the interferometric phases to generate differential interferometric phases, calculate differential interferograms pixel by pixel, and then perform linear deformation phase estimation in the time and spatial domains on the differential interferometric phases to obtain the time series deformation phase of each point target. However, this method only focuses on frequency band and polarization differences and does not solve the spectral compatibility between different imaging modes in the same frequency band.

[0008] The patent document "Method and Equipment for Measuring Surface Deformation Based on Dual-Frequency Multi-Polarization Differential Interferometry" (CN115453520A) discloses a method based on dual-frequency multi-polarization differential interferometry. By fusing data from the L-band and X-band, differential interferometry is performed using the principle of optimal coherence of polarization interferometry. Combined with spatial domain image fusion methods, the optimal combination of polarization modes is selected. Although this method improves the deformation measurement accuracy of different land cover types, it only focuses on frequency band and polarization differences and does not solve the problem of spectral compatibility between data of different imaging modes (such as different resolutions and swath widths) in the same frequency band.

[0009] Therefore, there is an urgent need for a SAR surface deformation monitoring method with different imaging modes for different stars, in order to increase the monitoring frequency and meet the urgent needs of geological disaster monitoring. Summary of the Invention

[0010] To address the shortcomings of existing technologies, the purpose of this invention is to provide a method and system for measuring surface deformation based on SAR data from different planets and imaging modes.

[0011] A method for measuring surface deformation based on SAR data with different imaging modes according to the present invention includes:

[0012] Step S1: Acquire SAR image data of alien planets with different imaging modes;

[0013] Step S2: Register SAR image data to obtain the slant range difference between the main and auxiliary images, the resampled main image, and the registered auxiliary image. ;

[0014] Step S3: Based on the slant distance difference between the main and auxiliary images and Pre-filtered SAR image data is used to obtain downsampled main and secondary images;

[0015] Step S4: Interferometric processing of the downsampled main and auxiliary images to obtain surface deformation information;

[0016] Step S5: Output the surface deformation information as the measurement result.

[0017] Preferably, the SAR image data of different satellites and different imaging modes are SAR image data acquired from different satellites and different imaging modes.

[0018] The different satellites operate within the same strictly retrograde orbit plane, with phase intervals between them. satisfy:

[0019]

[0020] in, Indicates the number of days to strictly return to orbit;

[0021] Represent a positive integer and satisfy .

[0022] The interferometric processing includes interferometric phase generation, adaptive filtering and noise suppression, phase unwrapping and residual correction, and atmospheric phase correction and deformation inversion to obtain millimeter-level surface deformation information.

[0023] Preferably, step S2 includes:

[0024] Step S2.1: Set the lower resolution SAR image data as the main image and the higher resolution image as the auxiliary image;

[0025] Step S2.2: Modulate the frequency center of the auxiliary image to the frequency of the main image's distance spectrum center, and perform resolution reduction processing to obtain a reduced-resolution auxiliary image. ;

[0026] Step S2.3: Calculate the geometric relationships using an external digital elevation model and radar imaging geometry. The registration offset and slant distance difference between the master and slave images are obtained.

[0027] Step S2.4: Correct the registration offset using the correlation coefficient method;

[0028] Step S2.5: Resample the auxiliary image using the corrected registration offset to obtain the registered auxiliary image. .

[0029] Preferably, step S2.2 includes:

[0030] Step S2.2.1: Perform phase compensation on the auxiliary image at each azimuth time to obtain the modulated auxiliary image. :

[0031]

[0032] in, Indicates location and time;

[0033] Indicates distance and time;

[0034] j represents the imaginary part;

[0035] Represents the speed of light;

[0036] This indicates the signal history over a corresponding distance and time.

[0037] Represents auxiliary images;

[0038] , These represent the distance-to-center frequencies of the main image and the auxiliary image, respectively.

[0039] Step S2.2.2: Transform the main and auxiliary images to the two-dimensional frequency domain, extract the two-dimensional common spectrum of the two images and transform it to the two-dimensional time domain to obtain the transformed auxiliary image. Resample according to the sampling interval set for the main image to obtain the reduced-resolution auxiliary image. .

[0040] Step S2.5 includes:

[0041] Step S2.5.1: Resample the main image according to the sampling interval set for the auxiliary image;

[0042] Step S2.5.2: Adjust the auxiliary image according to the corrected registration offset. Resampling is performed to obtain the registered auxiliary image. .

[0043] Preferably, step S3 includes:

[0044] Step S3.1: Invert the topographic interferometric phase based on the slant range difference between the master and auxiliary images. .

[0045] Step S3.2: Adjust the terrain interferometric phase. Modulated into the phase of the registered auxiliary image, resulting in :

[0046]

[0047] Step S3.3: Perform two-dimensional frequency filtering on the auxiliary image according to the two-dimensional spectral range of the main image to obtain the pre-filtered auxiliary image. :

[0048]

[0049] in, Indicates Fourier transform;

[0050] Indicates the inverse Fourier transform;

[0051] , These represent the frequencies in the azimuth and range directions, respectively.

[0052] This represents a window function set based on the two-dimensional spectral range of the main image.

[0053] Step S3.4: Resample the main image and pre-filtered auxiliary image. Perform downsampling processing.

[0054] According to the present invention, a surface deformation measurement system based on alien imaging mode SAR data is provided, comprising:

[0055] Module M1: Acquire SAR image data of alien planets with different imaging modes;

[0056] Module M2 registers SAR image data to obtain the slant range difference between the primary and secondary images, the resampled primary image, and the registered secondary image. ;

[0057] Module M3, based on the slant distance difference between the primary and secondary images and Pre-filtered SAR image data is used to obtain downsampled main and secondary images;

[0058] Module M4 interferometrically processes downsampled main and auxiliary images to obtain surface deformation information;

[0059] Module M5 outputs surface deformation information as the measurement result.

[0060] In more preferred embodiments, the SAR image data of different satellites and different imaging modes are SAR image data acquired from different satellites and different imaging modes.

[0061] The different satellites operate within the same strictly retrograde orbit plane, with phase intervals between them. satisfy:

[0062]

[0063] in, Indicates the number of days to strictly return to orbit;

[0064] Represent a positive integer and satisfy .

[0065] The interferometric processing includes interferometric phase generation, adaptive filtering and noise suppression, phase unwrapping and residual correction, and atmospheric phase correction and deformation inversion to obtain millimeter-level surface deformation information.

[0066] In more preferred embodiments, module M2 includes:

[0067] Module M2.1 sets the lower-resolution SAR image data as the main image and the higher-resolution data as the secondary image;

[0068] Module M2.2 modulates the frequency center of the auxiliary image to the frequency of the main image's distance spectrum center, and performs down-resolution processing to obtain a down-resolution auxiliary image. ;

[0069] Module M2.3 calculates geometric relationships using an external digital elevation model and radar imaging geometry. The registration offset and slant distance difference between the master and slave images are obtained.

[0070] Module M2.4 uses the correlation coefficient method to correct the registration offset;

[0071] Module M2.5 resamples the auxiliary image using the corrected registration offset to obtain the registered auxiliary image. .

[0072] In more preferred embodiments, module M2.2 includes:

[0073] Module M2.2.1 performs phase compensation on the auxiliary image at each azimuth time to obtain the modulated auxiliary image. :

[0074]

[0075] in, Indicates location and time;

[0076] Indicates distance and time;

[0077] j represents the imaginary part;

[0078] Represents the speed of light;

[0079] This indicates the signal history over a corresponding distance and time.

[0080] Represents auxiliary images;

[0081] , These represent the distance-to-center frequencies of the main image and the auxiliary image, respectively.

[0082] Module M2.2.2 transforms the main and auxiliary images to the two-dimensional frequency domain, extracts the two-dimensional common spectrum of the two images and transforms it to the two-dimensional time domain to obtain the transformed auxiliary image. It then resamples the auxiliary image according to the sampling interval set for the main image to obtain the reduced-resolution auxiliary image. .

[0083] The module M2.5 includes:

[0084] Module M2.5.1 resamples the main image according to the sampling interval set for the auxiliary image;

[0085] Module M2.5.2, adjusts the auxiliary image according to the corrected registration offset. Resampling is performed to obtain the registered auxiliary image. .

[0086] In more preferred embodiments, module M3 includes:

[0087] Module M3.1: Inverting the topographic interferometric phase based on the slant range difference between the master and auxiliary images. .

[0088] Module M3.2, Terrain Interferometric Phase Modulated into the phase of the registered auxiliary image, resulting in :

[0089]

[0090] Module M3.3 performs two-dimensional frequency filtering on the auxiliary image according to the two-dimensional spectral range of the main image to obtain the pre-filtered auxiliary image. :

[0091]

[0092] in, Indicates Fourier transform;

[0093] Indicates the inverse Fourier transform;

[0094] , These represent the frequencies in the azimuth and range directions, respectively.

[0095] This represents a window function set based on the two-dimensional spectral range of the main image.

[0096] Module M3.4: Processes the resampled main image and the pre-filtered auxiliary image. Perform downsampling processing.

[0097] Compared with the prior art, the present invention has the following beneficial effects:

[0098] 1. This invention effectively reduces the risk of spatial baseline decoherence in SAR systems with different imaging modes on different planets. By designing phase interval constraints on satellite orbits, it ensures the spatiotemporal correlation of alien data. Compared with traditional single-satellite differential interferometric InSAR technology, it significantly enhances the emergency response capability for geological disasters while maintaining sub-centimeter accuracy.

[0099] 2. The registration method for heterogeneous data of the present invention solves the registration misalignment problem caused by spectral offset and resolution difference of heterogeneous imaging mode data by fusing spectral center modulation and resolution reduction processing.

[0100] 3. This invention uses terrain phase separation technology to invert the terrain phase based on the slant range difference and modulate it onto the auxiliary image. Combined with two-dimensional spectral filtering, it effectively suppresses terrain residuals. Attached Figure Description

[0101] Other features, objects, and advantages of the invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0102] Figure 1 This is a schematic diagram of the differential interferometric SAR surface deformation measurement process of the present invention, which uses different imaging modes for different stars.

[0103] Figure 2 SAR image of Shanghai region from strip pattern 1 of Land Detection-1 Group A satellite;

[0104] Figure 3 SAR image of Shanghai region from strip mode 2 of Land Detection-1 Group B satellite;

[0105] Figure 4 This is a differential interferometric phase diagram of two SAR images, with the image of satellite A as the main image. Detailed Implementation

[0106] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.

[0107] This invention provides a method for measuring surface deformation based on SAR data with different imaging modes from different planets. An end-to-end processing framework for SAR data with different imaging modes from different planets is constructed. Through phase-separation constrained satellite orbit design, fusion of spectrum center modulation, resolution reduction processing and geometric-correlation joint registration, and pre-filtering processing, the entire link of data acquisition, registration, pre-filtering, and interferometric processing of the SAR system with different imaging modes from different planets is adapted. Figure 1 For example, including:

[0108] Step S1: Acquisition of SAR image data in different imaging modes for different planets;

[0109] Specifically, the alien imaging mode SAR image data refers to SAR image data acquired from different satellites under different imaging modes. The two satellites operate within the same strictly regressive orbit plane with a phase interval of [missing information]. satisfy:

[0110]

[0111] in, To strictly determine the number of days to return to orbit, are positive integers and satisfy Different SAR image operating modes refer to differences in resolution and swath width, but they have a certain degree of overlap in Doppler bandwidth and range-frequency bandwidth.

[0112] Step S2: Registration of SAR image data for different imaging modes based on radar geometry and image correlation processing;

[0113] Specifically, step S2 includes the following steps:

[0114] Step S2.1: Use the low-resolution SAR image as the main image and the high-resolution image as the auxiliary image;

[0115] Step S2.2: Modulate the frequency center of the auxiliary image to the frequency center of the main image's distance spectrum, and then perform resolution reduction processing;

[0116] Specifically, step S2.2 includes:

[0117] Step S2.2.1: Modulate the frequency center of the auxiliary image to the frequency of the main image's distance spectrum center;

[0118] If the main image is The auxiliary image is The modulated auxiliary image is The modulation process can be represented as performing phase compensation on the auxiliary image at each azimuth time point to obtain the auxiliary image. ,Right now:

[0119]

[0120] in, For location and time, Let j represent the distance over time, and j represent the imaginary part. At the speed of light, This represents the signal history over a corresponding distance and time period. , These are the distance-to-center frequencies of the main image and the auxiliary image, respectively.

[0121] Step S2.2.2: The resolution reduction process involves transforming the primary and secondary images to the two-dimensional frequency domain, extracting the two-dimensional common spectrum of the two images, and transforming it to the two-dimensional time domain to obtain the transformed secondary image. This secondary image is then resampled according to the sampling interval of the primary image to obtain the reduced-resolution secondary image used for calculating the registration offset. .

[0122] By combining spectrum center modulation and down-resolution registration, the problem of cross-mode data spectrum mismatch is solved, and phase alignment of heterogeneous resolution data is achieved.

[0123] Step S2.3: Use the external digital elevation model (DEM) and radar imaging geometry to determine the azimuth and range registration offset and the slant range difference between the main and auxiliary images;

[0124] Directly using the correlation coefficient method for registering SAR image data of different planets and different imaging modes involves too much computation. Determining the approximate azimuth and range registration offset through geometric relationships and then using the correlation coefficient method for correction can greatly reduce the amount of computation and improve processing efficiency.

[0125] Step S2.4: Correct the registration offset obtained in step S2.3 using the correlation coefficient method;

[0126] The geometric-correlation joint registration method corrects the azimuth / distance offset of cross-platform data by using an external DEM and correlation coefficient, thus solving the problem of geometric baseline mismatch in different modes.

[0127] Step S2.5: Resample the auxiliary image using the registration offset.

[0128] Specifically, step S2.5 includes:

[0129] Step S2.5.1: Resample the main image according to the sampling interval of the auxiliary image;

[0130] Step S2.5.2: Use the obtained registration offset to register the original high-resolution auxiliary image. Resampling is performed to obtain the registered auxiliary image. .

[0131] Step S3: Pre-filtering of SAR image data of different imaging modes based on terrain inversion phase and spectral center correction;

[0132] Focusing on cross-mode data within the same frequency band (such as high / low resolution stripe patterns), pre-filtering and downsampling are used to unify the spectral range, ensuring spatial consistency of the interferometric phase. Simultaneously, terrain phase is inverted by the slant range difference between the main and auxiliary images and modulated onto the auxiliary image. Combined with two-dimensional spectral filtering, terrain residuals in the cross-mode data are suppressed.

[0133] Specifically, step S3 includes:

[0134] Step S3.1: Invert the topographic interferometric phase using the slant range difference between the master and auxiliary images obtained in the geometric registration step S2.3. ;

[0135] Step S3.2: Modulate the inverted terrain interferometric phase onto the phase of the resampled auxiliary image to obtain the auxiliary image. :

[0136]

[0137] Step S3.3: Perform two-dimensional frequency filtering on the auxiliary image according to the two-dimensional spectral range of the main image to obtain the pre-filtered auxiliary image. :

[0138]

[0139] in, Indicates Fourier transform, This represents the inverse Fourier transform. and These represent the frequencies in the azimuth and range directions, respectively. This represents a window function set based on the two-dimensional spectral range of the main image.

[0140] Step S3.4: Resample the main image from step S2.5.1 and the auxiliary image from step S3.3. After downsampling, both images still satisfy the Nyquist sampling condition.

[0141] Step S4: Interferometric processing of pre-filtered SAR image data;

[0142] Specifically, conventional interferometric processing is performed on the registered and pre-filtered master and slave image data, mainly including interferometric phase generation, adaptive filtering and noise suppression, phase unwrapping and residual correction, atmospheric phase correction and deformation inversion, to obtain millimeter-level surface deformation information.

[0143] In more preferred examples, the Land Observation 1 01 group of satellites was used for verification. The two SAR images used in the experiment are as follows: Figure 2 and Figure 3 As shown. Figure 2 This is a SAR image (signal bandwidth 80MHz) acquired by the LuTan-1 01A satellite in strip mode 1 on July 22, 2023. Figure 3 The image shows a SAR image (60MHz signal bandwidth) acquired by the LuTan-1 01 Group B satellite on March 4, 2023, using strip mode 2. The interferometric fringe pattern obtained using the differential interferometry method is shown below. Figure 4 As shown in the figure, the obtained interference fringe pattern is clear and meets the requirements for differential interferometric deformation measurement.

[0144] Step S5: Output the results of differential interferometric surface measurement information.

[0145] Compared with traditional single-satellite differential interferometry (InSAR) technology, this technology significantly enhances the emergency response capability for geological disasters while maintaining sub-centimeter-level accuracy. It enables millimeter-level deformation interferometry measurement of SAR systems with different imaging modes from different satellites, breaks through the bottleneck of cross-platform data interference incoherence, fills the technical gap in collaborative deformation monitoring of heterogeneous multi-mode SAR data, and provides a systematic solution for high-frequency, high-precision surface deformation monitoring.

[0146] The present invention also provides a method and system for measuring surface deformation based on alien imaging mode SAR data. The surface deformation measurement system based on alien imaging mode SAR data can be implemented by executing the process steps of the surface deformation measurement method based on alien imaging mode SAR data. That is, those skilled in the art can understand the surface deformation measurement method based on alien imaging mode SAR data as a preferred embodiment of the surface deformation measurement system based on alien imaging mode SAR data.

[0147] According to the present invention, a surface deformation measurement system based on alien imaging mode SAR data is provided, comprising:

[0148] Module M1: Acquire SAR image data of alien planets with different imaging modes;

[0149] Module M2 registers SAR image data to obtain the slant range difference between the primary and secondary images, the resampled primary image, and the registered secondary image. ;

[0150] Module M3, based on the slant distance difference between the primary and secondary images and Pre-filtered SAR image data is used to obtain downsampled main and secondary images;

[0151] Module M4 interferometrically processes downsampled main and auxiliary images to obtain surface deformation information;

[0152] Module M5 outputs surface deformation information as the measurement result.

[0153] In more preferred embodiments, the SAR image data of different satellites and different imaging modes are SAR image data acquired under different imaging modes of different satellites.

[0154] The different satellites operate within the same strictly retrograde orbit plane, with phase intervals between them. satisfy:

[0155]

[0156] in, Indicates the number of days to strictly return to orbit;

[0157] Represent a positive integer and satisfy .

[0158] The interferometric processing includes interferometric phase generation, adaptive filtering and noise suppression, phase unwrapping and residual correction, and atmospheric phase correction and deformation inversion to obtain millimeter-level surface deformation information.

[0159] In more preferred embodiments, module M2 includes:

[0160] Module M2.1 sets the lower-resolution SAR image data as the main image and the higher-resolution data as the secondary image;

[0161] Module M2.2 modulates the frequency center of the auxiliary image to the frequency of the main image's distance spectrum center, and performs down-resolution processing to obtain the down-resolution auxiliary image. ;

[0162] Module M2.3 calculates geometric relationships using an external digital elevation model and radar imaging geometry. The registration offset and slant distance difference between the master and slave images are obtained.

[0163] Module M2.4 uses the correlation coefficient method to correct the registration offset;

[0164] Module M2.5 resamples the auxiliary image using the corrected registration offset to obtain the registered auxiliary image. .

[0165] In more preferred embodiments, module M2.2 includes:

[0166] Module M2.2.1 performs phase compensation on the auxiliary image at each azimuth time to obtain the modulated auxiliary image. :

[0167]

[0168] in, Indicates location and time;

[0169] Indicates distance and time;

[0170] j represents the imaginary part;

[0171] Represents the speed of light;

[0172] This indicates the signal history over a corresponding distance and time.

[0173] Represents auxiliary images;

[0174] , These represent the distance-to-center frequencies of the main image and the auxiliary image, respectively.

[0175] Module M2.2.2 transforms the main and auxiliary images to the two-dimensional frequency domain, extracts the two-dimensional common spectrum of the two images and transforms it to the two-dimensional time domain to obtain the transformed auxiliary image. It then resamples the auxiliary image according to the sampling interval set for the main image to obtain the down-resolution auxiliary image. .

[0176] The module M2.5 includes:

[0177] Module M2.5.1 resamples the main image according to the sampling interval set for the auxiliary image;

[0178] Module M2.5.2, adjusts the auxiliary image according to the corrected registration offset. Resampling is performed to obtain the registered auxiliary image. .

[0179] In more preferred embodiments, module M3 includes:

[0180] Module M3.1: Inverting the topographic interferometric phase based on the slant range difference between the master and auxiliary images. .

[0181] Module M3.2, Terrain Interferometric Phase Modulated into the phase of the registered auxiliary image, resulting in :

[0182]

[0183] Module M3.3 performs two-dimensional frequency filtering on the auxiliary image according to the two-dimensional spectral range of the main image to obtain the pre-filtered auxiliary image. :

[0184]

[0185] in, Indicates Fourier transform;

[0186] Indicates the inverse Fourier transform;

[0187] , These represent the frequencies in the azimuth and range directions, respectively.

[0188] This represents a window function set based on the two-dimensional spectral range of the main image.

[0189] Module M3.4: Resamples the main image from module M2.5.1 and the auxiliary image from module M3.3 after pre-filtering. Perform downsampling processing.

[0190] Those skilled in the art will understand that, besides implementing the system and its various devices, modules, and units provided by this invention in the form of purely computer-readable program code, the same functions can be achieved entirely through logical programming of the method steps, making the system and its various devices, modules, and units of this invention function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, the system and its various devices, modules, and units provided by this invention can be considered as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be considered as structures within the hardware component; alternatively, the devices, modules, and units for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0191] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A method for measuring surface deformation based on SAR data with different imaging modes from different planets, characterized in that, include: Step S1: Acquire SAR image data of alien planets with different imaging modes; The SAR image data of the different satellite imaging modes refers to SAR image data acquired from different satellites under different imaging modes. The different satellites operate within the same strictly regressive orbital plane; Step S2: Register SAR image data to obtain the slant range difference between the main and auxiliary images, the resampled main image, and the registered auxiliary image. ; Step S3: Based on the slant distance difference between the main and auxiliary images and Pre-filtered SAR image data is used to obtain downsampled main and secondary images; Step S4: Interferometric processing of the downsampled main and auxiliary images to obtain surface deformation information; The interferometric processing includes interferometric phase generation, adaptive filtering and noise suppression, phase unwrapping and residual correction, and atmospheric phase correction and deformation inversion to obtain millimeter-level surface deformation information. Step S5: Output the surface deformation information as the measurement result; Step S2 includes: Step S2.1: Set the lower resolution SAR image data as the main image and the higher resolution image as the auxiliary image; Step S2.2: Modulate the frequency center of the auxiliary image to the frequency of the main image's distance spectrum center, and perform resolution reduction processing to obtain a reduced-resolution auxiliary image. ; Step S2.3: Calculate the geometric relationships using an external digital elevation model and radar imaging geometry. The registration offset and slant distance difference between the master and slave images are obtained. Step S2.4: Correct the registration offset using the correlation coefficient method; Step S2.5: Resample the auxiliary image using the corrected registration offset to obtain the registered auxiliary image. ; Step S3 includes: Step S3.1: Invert the topographic interferometric phase based on the slant range difference between the master and auxiliary images. ; Step S3.2: Adjust the terrain interferometric phase. Modulated into the phase of the registered auxiliary image, resulting in ; Step S3.3: Perform two-dimensional frequency filtering on the auxiliary image according to the two-dimensional spectral range of the main image to obtain the pre-filtered auxiliary image. ; Step S3.4: Resample the main image and pre-filtered auxiliary image. Perform downsampling processing.

2. The method for measuring surface deformation based on SAR data with different imaging modes from different planets according to claim 1, characterized in that, The phase interval of the different satellites satisfy: in, Indicates the number of days to strictly return to orbit; Represent a positive integer and satisfy .

3. The method for measuring surface deformation based on SAR data with different imaging modes from different planets according to claim 1, characterized in that, Step S2.2 includes: Step S2.2.1: Perform phase compensation on the auxiliary image at each azimuth time to obtain the modulated auxiliary image. : in, Indicates location and time; Indicates distance and time; j represents the imaginary part; Represents the speed of light; This indicates the signal history over a corresponding distance and time. Representing auxiliary images; , These represent the distance-to-center frequencies of the main image and the auxiliary image, respectively. Step S2.2.2: Transform the main and auxiliary images to the two-dimensional frequency domain, extract the two-dimensional common spectrum of the two images and transform it to the two-dimensional time domain to obtain the transformed auxiliary image. Resample according to the sampling interval set for the main image to obtain the reduced-resolution auxiliary image. ; Step S2.5 includes: Step S2.5.1: Resample the main image according to the sampling interval set for the auxiliary image; Step S2.5.2: Adjust the auxiliary image according to the corrected registration offset. Resampling is performed to obtain the registered auxiliary image. .

4. The method for measuring surface deformation based on SAR data with different imaging modes from different planets according to claim 1, characterized in that, In step S3.2, the following is obtained: : In step S3.3, the pre-filtered auxiliary image is obtained. : in, Indicates Fourier transform; Indicates the inverse Fourier transform; , These represent the frequencies in the azimuth and range directions, respectively. This represents a window function set based on the two-dimensional spectral range of the main image.

5. A surface deformation measurement system based on alien imaging mode SAR data, characterized in that, include: Module M1: Acquire SAR image data of alien planets with different imaging modes; The SAR image data of the different satellite imaging modes refers to SAR image data acquired from different satellites under different imaging modes. The different satellites operate within the same strictly regressive orbital plane; Module M2 registers SAR image data to obtain the slant range difference between the primary and secondary images, the resampled primary image, and the registered secondary image. ; Module M3, based on the slant distance difference between the primary and secondary images and Pre-filtered SAR image data is used to obtain downsampled main and secondary images; Module M4 interferometrically processes downsampled main and auxiliary images to obtain surface deformation information; The interferometric processing includes interferometric phase generation, adaptive filtering and noise suppression, phase unwrapping and residual correction, and atmospheric phase correction and deformation inversion to obtain millimeter-level surface deformation information. Module M5 outputs surface deformation information as measurement results; The module M2 includes: Module M2.1 sets the lower-resolution SAR image data as the main image and the higher-resolution data as the secondary image; Module M2.2 modulates the frequency center of the auxiliary image to the frequency of the main image's distance spectrum center, and performs down-resolution processing to obtain a down-resolution auxiliary image. ; Module M2.3 calculates geometric relationships using an external digital elevation model and radar imaging geometry. The registration offset and slant distance difference between the master and slave images are obtained. Module M2.4 uses the correlation coefficient method to correct the registration offset; Module M2.5 resamples the auxiliary image using the corrected registration offset to obtain the registered auxiliary image. ; Module M3 includes: Module M3.1: Inverting the topographic interferometric phase based on the slant range difference between the master and auxiliary images. ; Module M3.2, Terrain Interferometric Phase Modulated into the phase of the registered auxiliary image, resulting in ; Module M3.4: Processes the resampled main image and the pre-filtered auxiliary image. Perform downsampling processing.

6. The surface deformation measurement system based on alien imaging mode SAR data according to claim 5, characterized in that, The phase interval of the different satellites satisfy: in, Indicates the number of days to strictly return to orbit; Represent a positive integer and satisfy .

7. The surface deformation measurement system based on alien imaging mode SAR data according to claim 5, characterized in that, The module M2.2 includes: Module M2.2.1 performs phase compensation on the auxiliary image at each azimuth time to obtain the modulated auxiliary image. : in, Indicates location and time; Indicates distance and time; j represents the imaginary part; Represents the speed of light; This indicates the signal history over a corresponding distance and time. Representing auxiliary images; , These represent the distance-to-center frequencies of the main image and the auxiliary image, respectively. Module M2.2.2 transforms the main and auxiliary images to the two-dimensional frequency domain, extracts the two-dimensional common spectrum of the two images and transforms it to the two-dimensional time domain to obtain the transformed auxiliary image. It then resamples the auxiliary image according to the sampling interval set for the main image to obtain the reduced-resolution auxiliary image. ; The module M2.5 includes: Module M2.5.1 resamples the main image according to the sampling interval set for the auxiliary image; Module M2.5.2, adjusts the auxiliary image according to the corrected registration offset. Resampling is performed to obtain the registered auxiliary image. .

8. The surface deformation measurement system based on alien imaging mode SAR data according to claim 5, characterized in that, In module M3.2, the following is obtained: : In module M3.3, the pre-filtered auxiliary image is obtained. : in, Indicates Fourier transform; Indicates the inverse Fourier transform; , These represent the frequencies in the azimuth and range directions, respectively. This represents a window function set based on the two-dimensional spectral range of the main image.

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