An Optimal Deployment Method for InSAR-Assisted GNSS Monitoring Network

Abstract

The present invention provides an InSAR-assisted GNSS monitoring network optimization layout method, comprising the following steps: arranging a number of monitoring points in a test area to form an initial monitoring network; based on the influencing factors of the GNSS monitoring point layout, using the hierarchical analysis method to screen the monitoring points to form a GNSS monitoring network; the influencing factors of the GNSS monitoring point layout include the basic requirements for the GNSS monitoring point layout, the historical InSAR monitoring results, and the geological disaster investigation results. The optimization layout method provided by the present invention introduces the historical InSAR monitoring results under the condition of considering the influencing factors of the GNSS monitoring point layout, uses the hierarchical analysis method to screen the appropriate monitoring points, forms a GNSS monitoring network, optimizes the monitoring points in the monitoring network, saves the monitoring cost, and obtains a high-precision monitoring result that can accurately reflect the surface deformation.

Description

Technical Field

[0001] The present invention relates to the technical field of geological disaster monitoring, and in particular to an optimization layout method of an InSAR-assisted GNSS monitoring network. Background Art

[0002] GNSS technology monitors deformation, with the advantages of all-weather, high degree of automation, no need for line of sight, flexible and simple operation, real-time three-dimensional monitoring, high precision, and high efficiency. As an important deformation monitoring technology in the field of geodesy, it has been widely used in geological disaster deformation monitoring. In the late 1980s, the international community has gradually adopted GNSS technology to monitor and warn geological disasters such as volcanoes, landslides, collapses, ground subsidence, ground fissures, and ground collapse. A large number of literatures have verified through experiments that GNSS technology is fully suitable for deformation monitoring of geological disasters such as landslides.

[0003] In practice, when using GNSS technology to monitor deformation of geological disasters such as landslides, the selection of coordinate systems and reference datums, the layout of monitoring points and network construction plans, monitoring accuracy indicators and operation methods, monitoring data collection, and deformation monitoring result processing will have an impact on the GNSS monitoring accuracy that cannot be ignored. There are still many technical issues that deserve in-depth research and discussion. For example: high-precision deformation monitoring results are closely related to many factors such as the layout of GNSS monitoring points, the deformation characteristics of geological disaster bodies, deformation amount and deformation speed. How to reasonably layout GNSS deformation monitoring points is also a technical issue in deformation monitoring of geological disasters such as landslides that needs to be tested through in-depth research and a lot of practice.

[0004] At present, the literature on the deployment of GNSS deformation monitoring points for geological disasters usually only considers factors such as measurement specifications, monitoring network type, signal conditions, solution accuracy, receiver type, ease of deployment, number of equipment, observation period, and economy. It is unable to effectively select representative monitoring points for GNSS deployment, resulting in poor accuracy of deformation monitoring results and the inability to accurately reflect surface deformation conditions.

[0005] In summary, there is an urgent need for an optimized deployment method of an InSAR-assisted GNSS monitoring network to solve the problems existing in the prior art. Summary of the invention

[0006] The present invention aims to provide an optimized deployment method of an InSAR-assisted GNSS monitoring network, aiming to solve the problem that the existing technology selects inaccurate monitoring points, resulting in poor accuracy of deformation monitoring results and inability to accurately reflect the surface deformation. The specific technical solution is as follows:

[0007] An optimized deployment method of an InSAR-assisted GNSS monitoring network comprises the following steps:

[0008] S1: Several monitoring points are set up in the test area to form an initial monitoring network;

[0009] S2: Based on the influencing factors of GNSS monitoring point layout, the analytic hierarchy process is used to screen the monitoring points to form a GNSS monitoring network; the influencing factors of GNSS monitoring point layout include the basic requirements for GNSS monitoring point layout, historical InSAR monitoring results and geological disaster investigation results.

[0010] Preferably, the step S2 is specifically as follows:

[0011] S2-1: Select two monitoring points and obtain the influencing factors of GNSS monitoring point layout;

[0012] S2-2: Construct an orthogonal matrix based on the influencing factors of GNSS monitoring point layout;

[0013] S2-3: Take geometric average of each row vector of the orthogonal matrix and then normalize it to obtain weights and eigenvectors;

[0014] S2-4: Check the consistency of the orthogonal matrix. If it is consistent, output the weight comparison result between the two points; otherwise, return to step S2-2;

[0015] S2-5: Return to step S2-1 until all monitoring points are compared with each other; arrange all monitoring points in order according to the weight comparison results, and select monitoring points to form a monitoring network according to the requirements of monitoring network layout.

[0016] Preferably, the step S2-2 specifically includes: constructing an orthogonal matrix based on the influencing factors of the GNSS monitoring point layout, and the expression is as follows:

[0017]

[0018] Among them, A represents an orthogonal matrix, a ij It represents the importance score of the i-th influencing factor relative to the j-th influencing factor, 1≤i≤n, 1≤j≤n, and n represents the total number of influencing factors.

[0019] Preferably, the expression of the weight is as follows:

[0020]

[0021] Among them, w i represents the weight of the i-th influencing factor, represents the average weight;

[0022] The expression of the feature vector is:

[0023]

[0024] Among them, X represents the feature vector, x n The feature vector representing the nth evaluation indicator.

[0025] Preferably, the step S2-4 is specifically as follows:

[0026] Calculate the consistency of the orthogonal matrix, the expression is as follows:

[0027] CR = CI / RI;

[0028] Among them, CR refers to the consistency ratio, CI represents the consistency index, and RI represents the random consistency index. When CR≤δ, the matrix is ​​consistent, and the weight comparison result between the two points is output; when CR>δ, the matrix is ​​inconsistent, and returns to step S2-2, and δ is the set value.

[0029] Preferably, the value range of δ is 0.08-0.12.

[0030] Preferably, the historical InSAR monitoring results include deformation magnitude and deformation rate; the geological disaster investigation results include geological conditions, threat level and slope; the basic requirements for the layout of GNSS monitoring points include signal conditions and layout conditions.

[0031] Preferably, the types of the GNSS monitoring network include cross type, grid type, arbitrary type, triangle type, benchmark type or multi-layer type.

[0032] The application of the technical solution of the present invention has the following beneficial effects:

[0033] The optimization layout method provided by the present invention introduces historical InSAR monitoring results while considering the influencing factors of GNSS monitoring point layout, uses the hierarchical analysis method to screen suitable monitoring points, forms a GNSS monitoring network, optimizes the monitoring points in the monitoring network, saves monitoring costs, and obtains monitoring results with high accuracy, which can accurately reflect the surface deformation.

[0034] In addition to the above-described purposes, features and advantages, the present invention has other purposes, features and advantages. The present invention will be further described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The drawings constituting a part of this application are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0036] Figure 1 is a schematic flow chart of step S2 in preferred embodiment 1 of the present invention;

[0037] Figure 2 It is a schematic diagram of the InSAR monitoring results of the test area of ​​the preferred embodiment 1 of the present invention;

[0038] Figure 3 yes Figure 2 Schematic diagram of the InSAR monitoring deformation level of No. 3 waste rock pile in the test area;

[0039] Figure 4 yes Figure 2 The contour map of the average deformation rate of No. 3 waste rock pile monitored by InSAR in the test area;

[0040] Figure 5 yes Figure 2 Schematic diagram of the locations of monitoring points A and B on the No. 3 waste rock pile in the test area;

[0041] Figure 6 yes Figure 5 Schematic diagram of InSAR monitoring deformation at monitoring point A;

[0042] Figure 7 yes Figure 5 Schematic diagram of InSAR monitoring deformation at monitoring point B;

[0043] Figure 8 yes Figure 5 Weight distribution diagram of monitoring point A and monitoring point B;

[0044] Fig. 9 yes Figure 5 Schematic diagram of the weight comparison results between monitoring point A and monitoring point B. DETAILED DESCRIPTION

[0045] In order to facilitate the understanding of the present invention, the present invention will be described more comprehensively below, and preferred embodiments of the present invention are provided. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present invention more thorough and comprehensive.

[0046] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0047] Embodiment 1:

[0048] See also Figure 1 , an optimization layout method of an InSAR-assisted GNSS monitoring network, comprising the following steps:

[0049] S1: In the test area (No. 3 waste rock pile, see Figure 2 ) deploying a number of monitoring points to form an initial monitoring network (in this embodiment, an arbitrary type);

[0050] S2: Based on the influencing factors of GNSS monitoring point layout, the monitoring points are screened by using the hierarchical analysis method to form a GNSS monitoring network; the influencing factors of GNSS monitoring point layout include historical InSAR monitoring results and geological disaster investigation results; see Figure 3-7 And Table 1, specifically including:

[0051] S2-1: Select two monitoring points, namely point A and point B, and obtain the geological disaster investigation results of point A and point B as well as the historical InSAR monitoring results. Figure 2-7 And Table 1; the factors affecting the layout of the GNSS monitoring points include deformation magnitude, deformation rate, signal conditions (determined according to the specific on-site conditions during the experiment, mainly considering whether there is any obstruction around the point, strong electromagnetic interference, etc.), layout conditions (determined according to the specific on-site conditions during the experiment, mainly considering the stability and accessibility of the point foundation, etc.), geological conditions (geological conditions described by the surface morphology and deformation characteristics in Table 1), threat degree (hazard degree in Table 1) and slope (slope in the surface morphology and deformation characteristics in Table 1);

[0052] Table 1 Geological survey table of point A and point B

[0053]

[0054] S2-2: Based on the influencing factors of GNSS monitoring point layout, an orthogonal matrix is ​​constructed, and the expression is as follows:

[0055]

[0056] Among them, A represents an orthogonal matrix, a ij represents the comparison result score of the i-th influencing factor relative to the j-th influencing factor, 1≤i≤n, 1≤j≤n, n represents the total number of influencing factors; the a ij The values ​​are assigned according to the relative importance of the influencing factors. The assignment criteria are shown in Table 2:

[0057] Table 2 Numerical setting standard group

[0058] Serial number A pair of comparison values definition 1 1 The two factors are equally important. 2 3 Compared with the two factors, the former is slightly more important than the latter. 3 5 Compared with the two factors, the former is obviously more important than the latter. 4 7 Compared with the two factors, the former is more important than the latter. 5 9 Compared with the two factors, the former is extremely more important than the latter. 6 2、4、6、8 The middle value of the above adjacent judgments

[0059] S2-3: Take the geometric mean of each row vector of the orthogonal matrix and then normalize it to obtain the weight and eigenvector, see Figure 8 ; The expression of the weight is as follows:

[0060]

[0061] Among them, w i represents the weight of the i-th influencing factor, Represents the average weight.

[0062] The expression of the feature vector is:

[0063]

[0064] Among them, X represents the feature vector, x n The feature vector representing the nth evaluation index;

[0065] S2-4: Check the consistency of the orthogonal matrix and calculate the maximum eigenvalue λ max , the expression is as follows:

[0066]

[0067] Where A is an orthogonal matrix;

[0068] Calculate the consistency index CI, the expression is as follows:

[0069]

[0070] Calculate the consistency ratio CR:

[0071] CR = CI / RI;

[0072] Among them, RI represents the random consistency index, and its value is obtained by looking up the table.

[0073] When CR≤δ, the matrix is ​​consistent, and the weight comparison result between the two points is output, see Fig. 9 , it can be seen that the weight of monitoring point B is better than that of monitoring point A; when CR>δ, the matrix is ​​not consistent, and the process returns to step S2-2, where the value of δ is 0.1;

[0074] The calculation results in step S2-3 and step S2-4 are shown in Table 3:

[0075] Table 3 Influencing factors in orthogonal matrix and orthogonal matrix consistency calculation results

[0076]

[0077]

[0078]

[0079]

[0080] From Table 3 we can get Figure 8 and Fig. 9It can be seen that the weight value of point B is better than that of point A. When it is necessary to choose one between point A and point B as the component of the monitoring network, point B is obviously more suitable.

[0081] S2-5: Return to step S2-1 until all monitoring points are compared with each other; arrange all monitoring points in order according to the weight comparison results, and select monitoring points to form a monitoring network according to the requirements of monitoring network layout.

[0082] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An optimized deployment method of an InSAR-assisted GNSS monitoring network, characterized in that: The following steps are involved: S1: Several monitoring points are set up in the test area to form an initial monitoring network; S2: Based on the influencing factors of GNSS monitoring point layout, the monitoring points are screened by using the hierarchical analysis method to form a GNSS monitoring network; the influencing factors of GNSS monitoring point layout include the basic requirements for GNSS monitoring point layout, historical InSAR monitoring results and geological disaster investigation results; S2-1: Select two monitoring points and obtain the influencing factors of GNSS monitoring point layout; S2-2: Construct an orthogonal matrix based on the influencing factors of GNSS monitoring point layout; S2-3: Take geometric average of each row vector of the orthogonal matrix and then normalize it to obtain weights and eigenvectors; S2-4: Check the consistency of the orthogonal matrix. If it is consistent, output the weight comparison result between the two points; otherwise, return to step S2-2; S2-5: Return to step S2-1 until all monitoring points are compared with each other; all monitoring points are arranged in sequence according to the weight comparison results, and monitoring points are selected according to the monitoring network layout requirements to form a monitoring network; The step S2-2 specifically includes: constructing an orthogonal matrix based on the influencing factors of the GNSS monitoring point layout, and the expression is as follows: Among them, A represents an orthogonal matrix, a ij represents the importance score of the i-th influencing factor relative to the j-th influencing factor, 1≤i≤n, 1≤j≤n, n represents the total number of influencing factors; the a ij Assign values ​​based on the relative importance of influencing factors.

2. The optimization layout method according to claim 1, characterized in that: The expression of the weight is as follows: Among them, w i represents the weight of the i-th influencing factor, represents the average weight; The expression of the feature vector is: Among them, X represents the feature vector, x n The feature vector representing the nth evaluation indicator.

3. The optimization layout method according to claim 2, characterized in that: The step S2-4 is specifically as follows: Calculate the consistency of the orthogonal matrix, the expression is as follows: CR = CI / RI; Among them, CR refers to the consistency ratio, CI represents the consistency index, and RI represents the random consistency index. When CR≤δ, the matrix is ​​consistent, and the weight comparison result between the two points is output; when CR>δ, the matrix is ​​inconsistent, and returns to step S2-2, and δ is the set value.

4. The optimization layout method according to claim 3, characterized in that: The value range of δ is 0.08-0.

12.

5. The optimization layout method according to claim 1, characterized in that: The historical InSAR monitoring results include deformation magnitude and deformation rate; the geological disaster investigation results include geological conditions, threat level and slope; the basic requirements for the layout of GNSS monitoring points include signal conditions and layout conditions.

6. The optimized layout method according to claim 1, characterized in that: The types of the GNSS monitoring network include cross type, grid type, arbitrary type, triangle type, benchmark type or multi-layer type.

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