Method for unifying InSAR reference framework and decomposing velocity field by using GNSS (Global Navigation Satellite System)

Abstract

The invention discloses a method for unifying an InSAR reference framework by using a GNSS and decomposing a velocity field, which comprises the following steps: (1) modeling a GNSS north-south velocity field based on a multi-scale spherical wavelet method, and deducting the contribution of the modeling velocity field in the sight line direction from an InSAR deformation field; (2) directly resolving east-west direction and vertical direction deformation fields by using an InSAR lifting rail sight direction velocity field; (3) establishing a quadratic polynomial function to carry out difference fitting so as to remove the influence of orbit errors and a reference frame; and (4) carrying out result analysis and verification in combination with cross comparison of ground measurement data. According to the method, the InSAR sight direction velocity field is decomposed in the east-west direction and the vertical direction by considering the contribution of north-south deformation, the reference framework of the calculated velocity field is unified by using GNSS data, so that more real deformation information is obtained, the data accuracy is ensured through multi-source data cross validation, and reliable data support can be provided.

Description

Technical Field

[0001] The invention relates to the field of surveying and mapping science and technology, and relates to a method for unifying an InSAR reference frame by using GNSS and performing velocity field decomposition. Background Art

[0002] Geodetic observations such as Synthetic Aperture Radar Interferometry (InSAR) and Global Navigation Satellite System (GNSS) are the main technologies for studying interseismic crustal deformation. The horizontal velocity obtained by continuous GNSS observations can reach the millimeter level, but it is limited to the measuring stations and has limited spatial resolution. Researchers usually deploy measuring stations in some key areas near the fault to improve the spatial resolution of the deformation field as much as possible, but even so, it is still impossible to fully capture the spatial variation characteristics of the deformation field. InSAR observations can obtain a large range of continuous surface deformations with an accuracy of up to millimeter level, but due to the influence of orbital errors, terrain errors, decoherence errors and atmospheric errors, as well as the insensitivity to north-south deformations and the limitations of one-dimensional line-of-sight deformations, as well as the requirements for interference conditions, there are still many challenges in obtaining high-precision interseismic three-dimensional deformation fields.

[0003] Taking full advantage of the high accuracy of GNSS single-point three-dimensional velocity and the ability of InSAR to provide spatially continuous line-of-sight deformation, combined GNSS / InSAR observations are currently the main method for extracting high spatial resolution interseismic three-dimensional deformation fields. For example, the interpolated GNSS north-south velocity field is used as a priori constraint to solve the east-west and vertical velocity fields; the GNSS horizontal velocity field and the InSAR ascending and descending orbit line-of-sight velocity field are combined to establish an energy function or use the least squares method to complete the fusion of the velocity field; stress-strain tensors are estimated based on elastic theory to solve the three-dimensional deformation components. In summary, how to combine GNSS, InSAR data and geodetic data such as leveling to establish a tectonic deformation field model is still in the exploratory stage, and the fusion method is still being optimized. The fundamental principle is to ensure the accuracy of the fused deformation field and improve the resolution of the near-field and far-field deformation models of the fault. The ultimate goal of the above methods is to obtain a high-precision three-dimensional deformation field. However, considering that the vertical deformation of the Qinghai-Tibet Plateau is relatively complex, the vertical deformation is often ignored and only the GNSS horizontal velocity observations are used to study the solution method of the three-dimensional deformation field. Or, considering that InSAR data is insensitive to north-south deformation, the north-south deformation is ignored and only the ascending and descending InSAR data are used to solve the east-west and vertical deformation, which leads to overestimation or underestimation of the results. How to combine multi-source data for velocity field decomposition without "ignoring" is still unclear.

[0004] In summary, the present invention proposes a method for unifying the InSAR reference frame using GNSS and performing velocity field decomposition. This method models the GNSS north-south velocity field based on the multi-scale spherical wavelet method, deducts the contribution of the modeled velocity field in the line of sight from the InSAR velocity field, and directly solves the east-west and vertical deformation fields using only the InSAR ascending and descending orbit line of sight velocity field, establishes a quadratic polynomial function for difference fitting to remove the influence of orbit error and reference frame, and ensures the accuracy of the data through cross-validation of ground measurement data, so as to obtain a large-scale, high-precision, and high-spatial-resolution deformation field. Summary of the invention

[0005] The present invention proposes a method for using GNSS to unify the InSAR reference frame and perform velocity field decomposition. The method models the GNSS north-south velocity field based on a multi-scale spherical wavelet method, deducts the contribution of the modeled velocity field in the line of sight from the InSAR velocity field, and directly solves the east-west and vertical deformation fields using only the InSAR ascending and descending orbit line of sight velocity field. A quadratic polynomial function is established for difference fitting to remove the influence of orbit error and reference frame, and the accuracy of the data is ensured by cross-validation of ground measurement data, so as to obtain a large-scale, high-precision, and high-spatial-resolution deformation field.

[0006] In order to achieve the above object, the present invention adopts the following technical solution:

[0007] A method for unifying the InSAR reference frame and decomposing the velocity field using GNSS includes four parts: using GNSS to model the north-south velocity field and subtracting it from the InSAR line of sight, using the InSAR line of sight velocity field to decompose the east-west and vertical deformations, unifying the reference frame and eliminating orbit errors, and analyzing and verifying the results.

[0008] The steps to model the north-south velocity field using GNSS and subtract it from the InSAR line of sight are as follows:

[0009] S1: Resample the InSAR line of sight velocity field to find the same-name points of ascending and descending orbit data;

[0010] S2: Model the north-south velocity field based on the multi-scale spherical wavelet method, project the modeling results to the line of sight according to the InSAR imaging geometry, and deduct the contribution of the modeled north-south deformation from the InSAR line of sight deformation;

[0011] The steps for using the InSAR line-of-sight velocity field to perform east-west and vertical decomposition are as follows:

[0012] S3: Take the ascending and descending orbit InSAR data containing only east-west and vertical deformation as input values, construct decomposition equations, and solve the east-west and vertical deformation fields;

[0013] The steps for reference frame unification and orbit error elimination are as follows:

[0014] S4: Taking the difference between the GNSS velocity field and the velocity field decomposed by InSAR as the observation value, the east-west velocity field calculated by InSAR is corrected based on the difference surface fitted by a quadratic polynomial function;

[0015] S5: Taking the difference between the leveling data and the vertical velocity field decomposed by InSAR as the observation value, the slope function is fitted to correct the vertical velocity field calculated by InSAR;

[0016] The steps for result analysis and verification are as follows:

[0017] S6: Cross-check with ground measurement data (GNSS and leveling) to verify the external compliance accuracy.

[0018] The method proposed in the present invention of using GNSS to unify the InSAR reference frame and decompose the velocity field is highly scientific, efficient and applicable. Taking into account the contribution of north-south deformation, the InSAR line-of-sight velocity field is decomposed in the east-west and vertical directions, and the reference frame of the solved east-west velocity field is unified using GNSS, thereby obtaining more realistic deformation information, ensuring the accuracy of the data through multi-source data cross-validation, and providing reliable data support. The method is easy to implement and can be widely used in the fields of geological disaster monitoring and engineering deformation monitoring.

[0019] Explanation of Figures and Tables

[0020] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings and tables required for use in the embodiments or the description of the prior art. Obviously, the drawings in the following description are merely schematic diagrams and tables of the present invention. For ordinary technicians in this field, other drawings and tables can be obtained based on the provided drawings without paying any creative work.

[0021] Figure 1 A flow chart of a method for utilizing GNSS to unify the InSAR reference frame and perform velocity field decomposition provided by the present invention.

[0022] Figure 2 Schematic diagram of InSAR line-of-sight velocity field.

[0023] Figure 3 Schematic diagram of GNSS horizontal velocity field.

[0024] Figure 4 Schematic diagram of the GNSS north-south velocity field model based on the multi-scale spherical wavelet method.

[0025] Figure 5Schematic diagram of the east-west and vertical deformation velocity fields calculated by InSAR.

[0026] Figure 6 Schematic diagram of the east-west and vertical deformation velocity fields to remove the influence of orbit error and reference frame.

[0027] Figure 7 This is a schematic diagram of the correlation analysis between the final velocity field and GNSS data and leveling data. DETAILED DESCRIPTION

[0028] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] The following steps are to model the north-south velocity field using GNSS and subtract it from the InSAR line of sight:

[0030] Step 1: Resample the InSAR line-of-sight velocity field and find the same-name points of the ascending and descending orbit data. In order to improve the computational efficiency and obtain a large-scale deformation rate field, the study area is divided into a 0.01°×0.003° grid. The mean value of all InSAR data points in the rectangular area with offsets of 0.006° and 0.003°, centered at each grid point, is taken as the line-of-sight velocity value corresponding to the grid point.

[0031] The InSAR line-of-sight velocity field is as follows: Figure 2 shown.

[0032] Step 2: Model the GNSS north-south velocity field based on the multi-scale spherical wavelet method, project the modeling results to the line of sight using the InSAR imaging geometry, subtract the modeled north-south velocity from the InSAR line of sight velocity to deduct the contribution of the north-south deformation in the InSAR line of sight, and obtain the line of sight velocity field that only contains east-west and vertical deformations. The projection formula is as follows:

[0033] D GNSSN LOS =D n sin(α)sin(θ) (1)

[0034] Where D GNSSN LOS To project the GNSS north-south deformation into the deformation value of the line of sight, D nis the north-south deformation component of GNSS, α is the flight azimuth of Sentinel-1 satellite, and θ is the local incidence angle of the satellite.

[0035] The GNSS horizontal velocity field is as follows: Figure 3 As shown in the figure, the GNSS north-south velocity field model based on the multi-scale spherical wavelet method is as follows: Figure 4 shown.

[0036] The following steps are to use the InSAR line-of-sight velocity field to perform east-west and vertical decomposition.

[0037] Step 3: Take the ascending and descending InSAR data containing only east-west and vertical deformation as input values, construct decomposition equations, and solve the east-west and vertical deformation fields. The specific formula is as follows, where θ is the satellite incidence angle and α is the satellite azimuth. and are the original InSAR ascending and descending orbit line-of-sight velocity, V GNSSN LOSA , V GNSSN LOSD are the projection of GNSS north-south deformation into the deformation value of the line of sight, V E , V U is the east-west and vertical velocity field to be determined.

[0038]

[0039] The east-west and vertical velocity fields solved by InSAR are as follows Figure 5 shown.

[0040] The following steps are for reference frame unification and orbit error elimination:

[0041] Step 4: Use the north-south velocity field model based on the multi-scale spherical wavelet method to solve the velocity field by subtracting the contribution of the north-south deformation from the original InSAR line-of-sight velocity field. The result is affected by the north-south modeling rate framework. Interpolate the GNSS velocity field to obtain a continuous crustal movement field. Take the difference between the GNSS velocity field and the velocity field decomposed by InSAR as the observation value, and correct the east-west velocity field solved by InSAR based on the fitting difference of the quadratic polynomial function. The above method can convert the spatial reference of the data to the same reference as the GNSS velocity field, effectively remove the long-wavelength signal error with a wavelength greater than 100 km, and retain the small-scale local deformation characteristics of the InSAR data.

[0042] Step 5: InSAR is a relative measurement technology. Each interferogram is relative to the selected reference point. There are systematic differences between the adjacent orbit results of ascending and descending orbits obtained by time series solution, and there are still significant orbit errors in the time series InSAR results. The difference between the leveling data and the vertical velocity field decomposed by InSAR is used as the observation value, and the slope function (trend surface) is fitted to correct the vertical velocity field solved by InSAR.

[0043] The east-west and vertical deformation velocity fields after removing the orbit error and reference frame influence are as follows: Figure 6 shown.

[0044] The following steps are for the result accuracy verification part

[0045] Step 6: Verify and evaluate the external accuracy by cross-comparison with ground measurement data (GNSS and leveling). Use the abundant GNSS observation data and leveling data in the study area to compare and analyze the result velocity field and evaluate the external accuracy of the result data.

[0046] The coherence analysis diagram between velocity field, GNSS data and leveling data is shown in the figure below. Figure 7 shown.

[0047] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined in the present invention may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown in the present invention, but will conform to the widest scope consistent with the principles and novel features disclosed in the present invention.

Claims

1. A method for unifying the InSAR reference frame and decomposing the velocity field using GNSS, including using GNSS to model the north-south velocity field and deduct it from the InSAR line of sight, using the InSAR line of sight velocity field to decompose the east-west and vertical directions, unifying the reference frame and eliminating orbit errors, and analyzing and verifying the results. The steps to model the north-south velocity field using GNSS and subtract it from the InSAR line of sight are as follows: S1: Resample the InSAR line of sight velocity field to find the same-name points of ascending and descending orbit data; S2: Model the GNSS north-south velocity field based on the multi-scale spherical wavelet method, project the modeling results to the line of sight according to the InSAR imaging geometry, and deduct the contribution of the modeled north-south deformation from the InSAR line of sight deformation; The steps for using the InSAR line-of-sight velocity field to perform east-west and vertical decomposition are as follows: S3: Take the ascending and descending orbit InSAR data containing only east-west and vertical deformation as input values, construct decomposition equations, and solve the east-west and vertical deformation fields; The steps for reference frame unification and orbit error elimination are as follows: S4: Taking the difference between the GNSS velocity field and the velocity field decomposed by InSAR as the observation value, the east-west velocity field calculated by InSAR is corrected based on the difference surface fitted by a quadratic polynomial function; S5: Taking the difference between the leveling data and the vertical velocity field decomposed by InSAR as the observation value, the slope function is fitted to correct the vertical velocity field calculated by InSAR; The steps for result analysis and verification are as follows: S6: Cross-check with ground measurement data (GNSS and leveling) to verify the external compliance accuracy.

2. The method of using GNSS to unify the InSAR reference frame and perform velocity field decomposition according to claim 1, characterized in that: In steps S1 to S6, the north-south velocity field is modeled using GNSS data and its contribution in the line of sight is deducted from the InSAR velocity field. Only the LOS velocity field is used for east-west and vertical decomposition. The difference is fitted with a quadratic polynomial function to remove the influence of orbit error and reference frame. The accuracy of the data is ensured through cross-validation of multi-source data to obtain a large-scale, high-precision, and high-spatial resolution deformation field.

3. The method of using GNSS to unify the InSAR reference frame and perform velocity field decomposition according to claim 1 or 2, characterized in that: In step S2, the InSAR data is decomposed in the east-west and vertical directions by taking into account the contribution of the north-south deformation, so that a more realistic deformation rate can be calculated. The application scenarios include: geological disaster monitoring and engineering deformation monitoring.

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