Method and device for establishing InSAR deformation monitoring benchmark based on GNSS

Abstract

The embodiment of the present invention relates to a method and device for establishing an InSAR deformation monitoring benchmark based on GNSS, the method comprising the steps of: obtaining first deformation information of a PS target point without prior information of ground deformation; using the first deformation information to classify and calibrate the PS target point; calculating the linear deformation rate and elevation correction value of the PS target point according to the results of the classification and calibration; using the calibrated PS target point as the InSAR deformation starting benchmark to establish the InSAR deformation monitoring benchmark. This technical solution uses GNSS long-term continuous deformation monitoring information as prior information, accurately and quickly identifies reference points of PS target points in InSAR, and classifies stability and calibrates the rate, incorporates the calibrated PS points into the PS baseline function model and the PS network adjustment model, obtains the PSInSAR deformation field with ground information, and ensures the objectivity, reliability and uniformity of the deformation benchmark reference points.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of geodetic deformation monitoring, and in particular to a method and device for establishing an InSAR deformation monitoring benchmark based on GNSS. Background Art

[0002] High-precision interferometric synthetic aperture radar (InSAR) deformation monitoring has great application prospects in the fields of geodesy, engineering surveying, earth change monitoring, and earth system science, and has been widely used in engineering deformation monitoring and various disaster monitoring, such as urban surface settlement, mining area deformation monitoring, and post-earthquake deformation monitoring. Since the direct monitoring quantity of InSAR is the deformation in the line of sight, and the orbit inclination of InSAR satellites is relatively single, and the number of satellites is also limited, the reliability of InSAR monitoring three-dimensional surface deformation has received widespread attention.

[0003] At present, the main problems of InSAR in large-scale engineering applications are as follows: the system deviation caused by the relative independence of deformation reference datums presents the problem of inconsistent cross-region deformation monitoring datums. How to fully utilize the advantages of long-term continuous observation, high precision, and high temporal resolution of the ground-based Global Navigation Satellite System (GNSS) reference station network to achieve the unification of InSAR cross-image, cross-regional nationwide deformation monitoring reference datums, improve the absolute deformation monitoring accuracy of InSAR, and avoid the system deviation caused by the current self-limiting reference point selection of InSAR is a problem that needs to be solved urgently. Summary of the invention

[0004] Based on the above situation of the prior art, the purpose of the embodiments of the present invention is to provide a method and device for establishing an InSAR deformation monitoring benchmark based on GNSS, which utilizes the ground high-precision continuous observation GNSS technology, takes InSAR stable natural / artificial permanent scatterers (Persistent Scatterers, hereinafter referred to as "PS") points as the link, and constructs an InSARPS baseline network and a joint networking solution model of GNSS and other earth monitoring networks, thereby establishing a large-scale full-scale InSAR unified reference deformation benchmark.

[0005] To achieve the above object, according to one aspect of the present invention, a method for establishing a GNSS-based InSAR deformation monitoring benchmark is provided, comprising:

[0006] S101, using InSAR data to obtain first deformation information of a PS target point without prior ground deformation information;

[0007] S102, based on GNSS data, using the first deformation information to classify and calibrate PS target points;

[0008] S103, calculating the linear deformation rate and elevation correction value of the PS target point according to the classification and calibration results;

[0009] S104, using the calibrated PS target point as the InSAR deformation calculation benchmark to establish the InSAR deformation monitoring benchmark.

[0010] Furthermore, in step S101, the first deformation information of the PS target point is obtained by using the amplitude and phase joint threshold method.

[0011] Furthermore, in step S102, the classification and calibration include:

[0012] S1021, obtaining second deformation information of the PS target point in the radar sight direction from the regional three-dimensional deformation field;

[0013] S1022, calculating a correlation coefficient between the first deformation information and the second deformation information;

[0014] S1023, classifying the PS target point according to the correlation coefficient, and performing rate calibration on the PS target point to obtain the difference in deformation rate .

[0015] Furthermore, the classification includes dividing the PS target points into multiple levels of stable points and unstable points.

[0016] Furthermore, in step S1023, the following constraint formula is used to perform rate calibration to obtain the difference in deformation rate: :

[0017] PS target point deformation rate difference calibration:

[0018]

[0019] Calibration of absolute deformation rate of primary stable PS target point:

[0020]

[0021] in, Neighborhood PS target point in the interference graph and The difference in deformation rate between PS target point in the interference pattern rate; , , and is the weight factor, and ; is the deformation rate difference between i and j in the radar line of sight direction obtained by InSAR; is the deformation rate difference between i and j in the radar line of sight direction obtained by GNSS; The deformation rate in the radar line of sight direction obtained by InSAR; It is the deformation rate in the radar line of sight direction obtained by GNSS.

[0022] Furthermore, in step S103, the linear deformation rate and elevation correction value of the PS target point are calculated, including:

[0023] S1031, calculating all baseline differential parameter solutions of the PS network with prior deformation constraints;

[0024] S1032. Obtain an optimal solution for the linear deformation rate and elevation correction value of the PS target point using the differential parameter solution.

[0025] Furthermore, in step S1031, all baseline differential parameter solutions of the PS network with prior deformation constraints are calculated using the differential phase basic function model based on the interference phase neighborhood PS point; wherein,

[0026] The basic function model of the differential phase at the PS point based on the interference phase neighborhood is:

[0027]

[0028] in, Neighborhood PS target point in the interference graph and The difference in elevation error between Neighborhood PS target point in the interference graph and The difference in deformation rate between is the differential phase of the interference phase neighborhood PS point; Neighborhood PS target point in the interference graph and The difference in the atmospheric residual phase between is the radar wavelength, is the distance from the radar to the ground point, For radar perspective, and Respectively The vertical spatial baseline and time baseline of the interferometric image pair;

[0029] The differential phase basic function model of the PS point based on the interference phase neighborhood is used to calculate all baseline differential parameter solutions of the PS network with prior deformation constraints, including the following steps:

[0030] The known Value and obtained As known parameters, the above basic function model is incorporated to obtain all baseline differential parameter solutions of the PS network with prior deformation constraints. and ,in, Obtained through solution space search in PS-InSAR data processing.

[0031] Furthermore, in step S1032, the optimal solution of the linear deformation rate and elevation correction value of the PS target point is obtained by using the differential parameter solution, including:

[0032] Solve all the baseline difference parameters and As a known quantity, bring back the basic function model and find all and value.

[0033] Furthermore, the constraint condition is:

[0034]

[0035] in, is the number of reference points, For the rest A reference point baseline design matrix, is the known prior information.

[0036] According to another aspect of the present invention, a GNSS-based InSAR deformation monitoring benchmark establishment device is provided, comprising a first deformation information acquisition module, a classification and calibration module, a calculation module, and a deformation monitoring benchmark establishment module; wherein,

[0037] The first deformation information acquisition module is used to acquire first deformation information of a PS target point without prior ground deformation information;

[0038] The grading and calibration module is used to grade and calibrate the PS target points using the first deformation information;

[0039] The calculation module is used to calculate the linear deformation rate and elevation correction value of the PS target point according to the results of the classification and calibration.

[0040] The deformation monitoring benchmark establishment module is used to establish the InSAR deformation monitoring benchmark by taking the calibrated PS target point as the InSAR deformation calculation benchmark.

[0041] In summary, the embodiment of the present invention provides a method and device for establishing an InSAR deformation monitoring benchmark based on GNSS, the method comprising the steps of: S101, obtaining the first deformation information of a PS target point without ground deformation prior information; S102, using the first deformation information to classify and calibrate the PS target point; S103, calculating the linear deformation rate and elevation correction value of the PS target point according to the results of the classification and calibration. The technical solution provided by the embodiment of the present invention uses GNSS long-term continuous deformation monitoring information as prior information to accurately and quickly identify the reference points of the PS target points in InSAR, classify the stability and calibrate the rate, and quickly jointly analyze and calibrate the InSAR / GNSS contemporaneous deformation time series based on the adaptive window sliding method, incorporate the calibrated PS points into the PS baseline function model and the PS network adjustment model, obtain the PSInSAR deformation field with ground information, realize the rapid analysis of massive permanent scatterers and the accurate optimization of their deformation reference points, and ensure the objectivity, reliability and uniformity of the deformation benchmark reference points. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 is a flow chart of a method for establishing a GNSS-based InSAR deformation monitoring benchmark provided by an embodiment of the present invention;

[0043] Figure 2 is a flow chart of classification and calibration of PS target points in an embodiment of the present invention;

[0044] Figure 3 is a flow chart of calculating the linear deformation rate and elevation correction value of a PS target point in an embodiment of the present invention;

[0045] Figure 4 It is a block diagram of a GNSS-based InSAR deformation monitoring benchmark establishment device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical scheme and advantages of the present invention clearer, the present invention is further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings. It should be understood that these descriptions are only exemplary and are not intended to limit the scope of the present invention. In addition, in the following description, the description of well-known structures and technologies is omitted to avoid unnecessary confusion of the concept of the present invention.

[0047] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in one or more embodiments of the present invention should be understood by people with ordinary skills in the field to which the present disclosure belongs. The "first", "second" and similar words used in one or more embodiments of the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0048] The technical solution of the present invention is described in detail below with reference to the accompanying drawings. In an embodiment of the present invention, a method for establishing a GNSS-based InSAR deformation monitoring benchmark is provided. The flowchart of the method is shown in FIG. Figure 1 As shown, the following steps are included:

[0049] S101, using InSAR data to obtain first deformation information of a PS target point without prior ground deformation information. In this step, an amplitude and phase joint threshold method can be used to obtain the first deformation information of an initial PS target point, that is, a PS target point without prior ground deformation information.

[0050] S102: Based on GNSS data, the PS target points are classified and calibrated using the first deformation information. Figure 2 The flowchart of the classification and calibration of the PS target points in this embodiment is shown in FIG. The correlation coefficient between the first deformation information of the PS target point and the second deformation information of the prior GNSS ground is used to determine the accuracy of the PS point and the prior information. On this basis, the PS point is divided into primary, secondary, ... and other multi-level stable points, as well as unstable points. The stable points strictly comply with the PS point stability assumption, and the unstable points can be regarded as nonlinear deformation monitoring points. The classification and calibration process can be implemented through the following steps:

[0051] S1021, obtaining second deformation information of the PS target point in the radar line of sight direction from the regional three-dimensional deformation field. In this step, the ground deformation obtained by long-term continuous observation of GNSS can be used as a priori model, and the second deformation information of the PS target point in the radar line of sight direction can be obtained through the priori model.

[0052] S1022: Calculate a correlation coefficient between the first deformation information and the second deformation information.

[0053] Wherein, r represents the correlation coefficient between the first deformation information and the second deformation information,

[0054] S1023. According to the correlation coefficient, the PS target point is graded for stability, and the PS target point is calibrated for rate. The stability grading can divide the PS target point into multiple levels of stable points and unstable points, such as primary, secondary, ..., wherein the lower the level, the higher the stability of the PS target point. Taking the classification into three-level stable points and unstable points as an example, when the calculated correlation coefficient does not exceed the first threshold, the PS target point is classified as an unstable point; when the calculated correlation coefficient exceeds the first threshold but does not exceed the second threshold, the PS target point is classified as a third-level stable point; when the calculated correlation coefficient exceeds the second threshold but does not exceed the third threshold, the PS target point is classified as a second-level stable point; when the calculated correlation coefficient exceeds the third threshold, the PS target point is classified as a first-level stable point. The level of stable points and the thresholds of each level can be set according to actual needs. Through the above-mentioned steps of stability grading based on the reference benchmark of the regional three-dimensional deformation field, PS target points with high levels of stability can be identified to establish an effective connection between the PS baseline network and the GNSS station network. Using the long-term continuous prior deformation information of the GNSS ground as a reference, different levels of PS points are calibrated, a reliable prior ground deformation benchmark is given to high-level stable PS target points, and the deformation rate difference of the neighboring PS target points and the absolute deformation of the PS target points are calibrated separately. The following constraint methods can be used to achieve calibration:

[0055] PS target point deformation rate difference calibration:

[0056]

[0057] Calibration of absolute deformation rate of primary stable PS target point:

[0058]

[0059] in, Neighborhood PS target point in the interference graph and The difference in deformation rate between PS target point in the interference pattern rate; , , and is the weight factor, and ; is the deformation rate difference between i and j in the radar line of sight direction obtained by InSAR; is the deformation rate difference between i and j in the radar line of sight direction obtained by GNSS; The deformation rate in the radar line of sight direction obtained by InSAR; The deformation rate in the radar line of sight direction obtained by GNSS. By accurately calibrating the PS target point, more prior information can be provided for PS baseline solution and network adjustment, and more redundant observation information can be provided for the estimation of InSAR atmospheric errors.

[0060] S103: Calculate the linear deformation rate and elevation correction value of the PS target point according to the classification and calibration results. Figure 3 A flowchart for calculating the linear deformation rate and elevation correction value of the PS target point is shown in FIG.

[0061] S1031. Calculate all baseline differential parameter solutions of the PS network with prior deformation constraints. In step S1031, all baseline differential parameter solutions of the PS network with prior deformation constraints are calculated using the basic function model of the differential phase of the neighborhood PS point based on the interference phase. The baseline differential parameter solution with prior deformation constraints takes into account the autocorrelation characteristics of the atmospheric state in the same image, and further differentiates the neighborhood PS interference phase from the spatial scale, which can reduce the influence of atmospheric phase delay to a certain extent. The basic function model of the differential phase of the neighborhood PS point based on the interference phase is:

[0062]

[0063] in, Neighborhood PS target point in the interference graph and The difference in elevation error between Neighborhood PS target point in the interference graph and The difference in deformation rate between is the differential phase of the interference phase neighborhood PS point; Neighborhood PS target point in the interference graph and The difference in the atmospheric residual phase between is the radar wavelength, is the distance from the radar to the ground point, For radar perspective, and Respectively The vertical spatial baseline and time baseline of the interferometric image pair are calculated by using the basic function model of the differential phase of the PS point in the interferometric phase neighborhood to calculate the differential parameter solutions of all baselines of the PS network with prior deformation constraints, including the following steps:

[0064] Will be obtained Values ​​and known As known parameters, the above basic function model is incorporated to obtain all baseline differential parameter solutions of the PS network with prior deformation constraints. and ,in, It can be obtained by searching the solution space in PS-InSAR data processing, which is a common solution method in this field.

[0065] In the above solution process, a constraint condition is added to the basic function model of differential phase at the PS point based on the interference phase neighborhood. The constraint condition is:

[0066]

[0067]

[0068] in, is the number of reference points, For the rest A reference point baseline design matrix, is the known prior information. Thus, the optimal solution of the linear deformation rate and elevation correction value of the PS point can be obtained.

[0069] S1032, using the differential parameter solution to obtain the optimal solution of the linear deformation rate and elevation correction value of the PS target point, including: obtaining all the baseline differential parameter solutions and As a known quantity, bring back the basic function model and find all and value.

[0070] S104, using the calibrated PS target point as the InSAR deformation calculation benchmark to establish the InSAR deformation monitoring benchmark.

[0071] The embodiment of the present invention further provides a GNSS-based InSAR deformation monitoring benchmark establishment device, the structure block diagram of the device is as follows: Figure 4 As shown, it includes a first deformation information acquisition module, a grading and calibration module, and a calculation module.

[0072] The first deformation information acquisition module is used to acquire the first deformation information of the PS target point without prior ground deformation information.

[0073] The grading and calibration module is used to grade and calibrate the PS target points using the first deformation information.

[0074] The calculation module is used to calculate the linear deformation rate and elevation correction value of the PS target point according to the results of the classification and calibration.

[0075] The deformation monitoring benchmark establishment module is used to establish the InSAR deformation monitoring benchmark by taking the calibrated PS target point as the InSAR deformation calculation benchmark.

[0076] In the GNSS-based InSAR deformation monitoring benchmark establishment device provided in this embodiment of the present invention, the specific process of each module realizing its function is the same as the steps of the GNSS-based InSAR deformation monitoring benchmark establishment method provided in the above embodiment of the present invention, and will not be described one by one here.

[0077] In summary, an embodiment of the present invention relates to a method and device for establishing an InSAR deformation monitoring benchmark based on GNSS, the method comprising the steps of: S101, obtaining first deformation information of a PS target point without prior information of ground deformation; S102, grading and calibrating the PS target points using the first deformation information; S103, calculating the linear deformation rate and elevation correction value of the PS target point according to the results of the grading and calibration; S104, using the calibrated PS target point as the InSAR deformation starting benchmark to establish an InSAR deformation monitoring benchmark. The technical solution provided by the embodiment of the present invention utilizes GNSS long-term continuous deformation monitoring information as prior information, accurately and quickly identifies reference points of PS target points in InSAR, and performs stability classification and rate calibration. Based on the adaptive window sliding method, the InSAR / GNSS contemporaneous deformation time series is quickly jointly analyzed and calibrated, and the calibrated PS points are incorporated into the PS baseline function model and the PS network adjustment model to obtain the PSInSAR deformation field with ground information, realize rapid analysis of massive permanent scatterers and accurate optimization of their deformation reference points, and ensure the objectivity, reliability and uniformity of the deformation benchmark reference points.

[0078] It should be understood that the discussion of any of the above embodiments is only exemplary and is not intended to imply that the scope of the present invention (including claims) is limited to these examples; under the concept of the present invention, the technical features in the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other changes in different aspects of one or more embodiments of the present invention as described above, which are not provided in detail for the sake of simplicity. The above specific embodiments of the present invention are only used to illustrate or explain the principles of the present invention, and do not constitute a limitation on the present invention. Therefore, any modifications, equivalent substitutions, improvements, etc. made without departing from the spirit and scope of the present invention should be included in the scope of protection of the present invention. In addition, the claims attached to the present invention are intended to cover all changes and modifications that fall within the scope and boundaries of the attached claims, or the equivalent forms of such scope and boundaries.

Claims

1. A method for establishing a GNSS-based InSAR deformation monitoring benchmark, characterized in that: include: S101, using InSAR data to obtain first deformation information of a PS target point without prior ground deformation information; S102: Based on the GNSS data, the PS target points are classified and calibrated using the first deformation information; the classification and calibration include: S1021, obtaining second deformation information of the PS target point in the radar sight direction from the regional three-dimensional deformation field; S1022, calculating a correlation coefficient between the first deformation information and the second deformation information; S1023, classifying the PS target point according to the correlation coefficient, and performing rate calibration on the PS target point to obtain the difference in deformation rate Δv ij ; S103, calculating the linear deformation rate and elevation correction value of the PS target point according to the classification and calibration results; S104, using the calibrated PS target point as the InSAR deformation calculation benchmark to establish the InSAR deformation monitoring benchmark.

2. The method according to claim 1, characterized in that In the step S101, the first deformation information of the PS target point is obtained by using the amplitude and phase combined threshold method.

3. The method according to claim 1, characterized in that The classification includes dividing the PS target points into multiple levels of stable points and unstable points.

4. The method according to claim 3, characterized in that: In step S1023, the following constraint formula is used to perform rate calibration to obtain the difference in deformation rate Δv: ij : PS target point deformation rate difference calibration: Calibration of absolute deformation rate of primary stable PS target point: Where Δv i,j is the difference in deformation rate between the neighborhood PS target points i and j in the interference graph; v l is the velocity of PS target point l in the interference pattern; 11 , 12 , 21 and λ 22 is the weight factor, and λ 11 +λ 12 =1,λ 21 +λ 22 =1; is the deformation rate difference between i and j in the radar line of sight direction obtained by InSAR; is the deformation rate difference between i and j in the radar line of sight direction obtained by GNSS; The deformation rate in the radar line of sight direction obtained by InSAR; It is the deformation rate in the radar line of sight direction obtained by GNSS.

5. The method according to claim 4, characterized in that In step S103, the linear deformation rate and elevation correction value of the PS target point are calculated, including: S1031, calculating all baseline differential parameter solutions of the PS network with prior deformation constraints; S1032. Obtain an optimal solution for the linear deformation rate and elevation correction value of the PS target point using the differential parameter solution.

6. The method according to claim 5, characterized in that In the step S1031, all baseline differential parameter solutions of the PS network with prior deformation constraints are calculated using the differential phase basic function model based on the interference phase neighborhood PS point; wherein, The basic function model of the differential phase at the PS point based on the interference phase neighborhood is: in, is the difference in elevation error between the neighborhood PS target points i and j in the interference graph, Δv ij is the difference in deformation rate between the neighborhood PS target points i and j in the interference graph; is the differential phase of the interference phase neighborhood PS point; is the difference in atmospheric residual phase between neighboring PS target points i and j in the interference graph, λ is the radar wavelength, R is the distance from the radar to the ground point, θ is the radar viewing angle, and B k and T k are the vertical spatial baseline and time baseline of the kth interferometric image pair respectively; The differential phase basic function model of the PS point based on the interference phase neighborhood is used to calculate all baseline differential parameter solutions of the PS network with prior deformation constraints, including the following steps: The known Value and the obtained Δv ij As known parameters, the above basic function model is incorporated to obtain all baseline differential parameter solutions of the PS network with prior deformation constraints. and Where Δv ij Obtained through solution space search in PS-InSAR data processing.

7. The method according to claim 6, characterized in that In step S1032, the optimal solution of the linear deformation rate and elevation correction value of the PS target point is obtained by using the differential parameter solution, including: Solve all the baseline difference parameters and As a known quantity, bring back the basic function model and find all and Δv ij value.

8. The method according to claim 7, characterized in that A constraint condition is added to the basic function model of differential phase at PS point based on interference phase neighborhood, and the constraint condition is: GX=W T =0 Where T is the number of reference points, G is the baseline design matrix for the remaining T-1 reference points, and W T is the known prior information.

9. A GNSS-based InSAR deformation monitoring benchmark establishment device, characterized in that: It includes a first deformation information acquisition module, a classification and calibration module, a calculation module, and a deformation monitoring benchmark establishment module; wherein, The first deformation information acquisition module is used to acquire first deformation information of a PS target point without prior ground deformation information; The grading and calibration module is used to grade and calibrate the PS target point using the first deformation information; the grading and calibration include: obtaining the second deformation information of the PS target point in the radar line of sight direction from the regional three-dimensional deformation field; calculating the correlation coefficient between the first deformation information and the second deformation information; grading the PS target point according to the correlation coefficient, and performing rate calibration on the PS target point to obtain the difference in deformation rate Δv ij ; The calculation module is used to calculate the linear deformation rate and elevation correction value of the PS target point according to the results of the classification and calibration. The deformation monitoring benchmark establishment module is used to establish the InSAR deformation monitoring benchmark by taking the calibrated PS target point as the InSAR deformation calculation benchmark.

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