Node seismograph positioning coordinate rapid fitting method and device

Abstract

The invention provides a node seismograph positioning coordinate rapid fitting method and device. The method comprises the steps of obtaining a positioning coordinate data set P; calculating a point location mean value Mp of all coordinate data in the set P, calculating the distance from each point to the Mp, and solving a distance mean value Dp; selecting a positioning coordinate from the set P, wherein the distance between the positioning coordinate and the Mp is smaller than R, and obtaining a new coordinate data set L; calculating a point location mean value Lp of all coordinate data in the set L, solving a distance from each point to the Lp, and obtaining a distance Dmax between the farthest point and the point location mean value Lp; setting an iteration step length Const, selecting coordinate data from the set L, and forming a new coordinate data set A, wherein the distance between the coordinate data and the point location mean value is smaller than Dist; and performing iterative calculation to obtain final fitting coordinates of the node seismograph. The iterative calculation process is efficient, the precision of the node seismograph positioning coordinates obtained through fitting is high, the method can be used for pile mark automatic matching, and therefore the workload of field laying personnel is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of node seismic acquisition, and in particular to a method and device for quickly fitting node seismograph positioning coordinates. Background Art

[0002] In recent years, node seismometers with built-in GNSS chips and capable of autonomous data collection have freed geophysical exploration construction from the constraints of cables. With their outstanding advantages such as lightness, flexibility, and efficiency, they have developed rapidly and have been successfully applied to mixed node and cable data collection, as well as full-node data collection projects, achieving good seismic data collection results.

[0003] However, due to factors such as the insufficient precision of built-in GNSS chips or imperfect internal algorithms, the positioning accuracy of node seismometers cannot be guaranteed in complex field construction environments. Most node seismometers with built-in GNSS chips record positioning data, but due to the poor reliability of the coordinate data, they cannot be directly used for automatic matching of pile numbers. The positioning data is only used as a reference for quality control. In actual node seismometer construction, manual deployment of pile numbers is still required, which not only consumes a large amount of manpower and material resources, but also, to some extent, restricts the further development and promotion of node seismometers.

[0004] In Chinese patent application No. 201510917979.3, a GPS positioning coordinate screening method and device are disclosed. The method includes: continuously acquiring a plurality of GPS position points of a GPS positioning terminal in real time; traversing all GPS position points in chronological order, treating a plurality of consecutive GPS position points as a group of screening objects, excluding a starting position point and an ending position point, and deleting a GPS position point in a group of screening objects if it meets a position point accuracy deletion condition; selecting n consecutive GPS position points, calculating an average value for their coordinates, and removing m coordinate points with the largest difference from the average value; for all GPS position points, excluding the starting position and the ending position, calculating the middle value coordinates of the two GPS position points before and after according to the chronological order as the middle position point, and removing the original GPS position point; and step five, connecting all the middle position points in chronological order to generate a GPS trajectory curve.

[0005] Chinese patent application number 201510782688.8 discloses a method for correcting GNSS single-point positioning coordinates based on CORS. This method uses the CORS system to obtain reference station coordinates and observations. Based on the initial approximate coordinates obtained by the GNSS terminal using single-point positioning and the satellite list used for positioning, a coordinate correction is calculated. This correction is applied to the approximate coordinates, achieving accuracy comparable to pseudorange differentials. This method eliminates the need for the GNSS terminal to provide its own raw observations and addresses the constellation inconsistency issue inherent in traditional coordinate differential techniques, thus offering promising applications.

[0006] In the Chinese patent application with application number: 202011201851.4, a method and device for matching pile numbers of onshore wireless node seismic instruments are disclosed, including comparing the distance of each point from the center point with the distance average value. If it is greater than the distance average value, the current point state is marked as 1, otherwise the current point state is marked as 0. The geometric center point is recalculated using the point with the state marked as 1. This method marks the state of discrete points and flying points as 0 by marking the state of the mark point, and these points are not involved in the calculation of the new geometric center point. It completely eliminates the influence of discrete points and flying points on the calculation of new geometric center points, and overcomes the influence of discrete points and flying points on pile number matching in the inverse distance weighted algorithm. Through cyclic iterative calculation, the geometric center point gradually moves to the place with high point distribution density. When the loop terminates, the position of the geometric center point calculated last is the best, and the circle with the center point as the center and a specific distance as the radius (usually half the track distance) contains the largest number of point sets.

[0007] The above existing technologies are all significantly different from the present invention. Therefore, it is urgent to develop a new node seismograph positioning coordinate fitting method. To this end, we invented a node seismograph positioning coordinate fast fitting method to solve the above technical problems. Summary of the Invention

[0008] The purpose of the present invention is to provide a method and device for quickly fitting the positioning coordinates of a node seismometer in view of the weak calculation capability and low positioning accuracy of the built-in GNSS chip of the node seismometer.

[0009] The purpose of the present invention can be achieved by the following technical measures: a node seismograph positioning coordinate rapid fitting method, the node seismograph positioning coordinate rapid fitting method comprising:

[0010] Step 1: Obtain the positioning coordinate data set P;

[0011] Step 2: Calculate the point mean M of all coordinate data in set P p , and calculate the distance from each point to M p The distance, calculate the average distance D p ;

[0012] Step 3: Select the same p The distance is less than the positioning coordinates of R, and a new coordinate data set L is obtained;

[0013] Step 4: Calculate the point mean L of all coordinate data in the set L p , and find the distance from each point to L p Distance, get the farthest point and the point mean L p The distance D max ;

[0014] Step 5: Set the iteration step length Const, select the coordinate data from the set L whose distance from the point mean is less than Dist, and form a new coordinate data set A;

[0015] Step 6: Perform iterative calculation to obtain the final fitting coordinates of the node seismometer.

[0016] The purpose of the present invention can also be achieved by the following technical measures:

[0017] In step 1, the positioning coordinate data directly read from the node seismometer are all WGS84 geodetic coordinates. In order to facilitate statistical analysis, the WGS84 geodetic coordinates should be converted into Beijing 54 plane rectangular coordinates. The coordinate data in set P are all Beijing 54 plane rectangular coordinates.

[0018] In step 1, the node seismometer positioning coordinate data is read, and the Bursa seven-parameter coordinate transformation method is used to transform the geodetic coordinates into plane rectangular coordinates to obtain the positioning coordinate data set P.

[0019] In step 2, the location coordinate data of the node seismometer is randomly distributed, and the location coordinate data point mean M of the node seismometer is p Take the simple arithmetic mean of the location coordinate data set.

[0020] In step 2, calculate the average value X of the horizontal coordinates of all coordinate data in the set P. p And the vertical axis mean Y p , then M p =(X p , Y p ).

[0021] In step 3, according to statistical analysis, as the size of the positioning coordinate data increases, the point distribution tends to be concentrated, of which 90% of the points are distributed in the M p The area with the center point and R as the radius is the core area, and R is 4 times the average of the distance, that is: R = 4*D p .

[0022] In step 3, the coordinate data beyond the core area are regarded as outlier data. Because of their large accidental deviation, they should be removed from the overall data and not participate in the subsequent iterative calculations. The number of iterations is controlled overall while ensuring the accuracy of the fitting coordinates.

[0023] In step 4, the point mean L p is the simple arithmetic mean of all coordinate data in set L. The method for obtaining it is: respectively obtain the mean value X of the horizontal coordinates of all coordinate data in set L. p And the vertical axis mean Y p , then L p =(X p , Y p ); maximum distance D max Indicates the farthest point in the set and the point mean L p The distance between them.

[0024] In step 5, the iteration step length Const should be a constant. When it is 2.5, the optimal fitting coordinates can be obtained, so that the mean error between the fitting coordinates and the measured coordinates of the node seismometer is minimized and the number of iterations is kept small. Dist is the difference between the maximum distance and the iteration step length, that is, Dist = D max -2.5.

[0025] In step 5, according to actual needs, the number of iterations and the accuracy of the fitting coordinates are controlled by changing the iteration step Const value; as the value of Const increases, the number of iterations decreases, and the error of the final fitting coordinate point increases.

[0026] In step 6, perform iterative calculations and repeat steps 4-5 until the set A is empty. The point average value L obtained by the last calculation is p This is the final fitting coordinate of the node seismometer.

[0027] In step 6, if set A is not empty, and D max >2.5, then continue to recalculate the point mean L of all coordinate data in set A p , find the distance from each point to L p Distance, get the maximum distance D max ; At this time, the coordinate data in set A is L p The center point D max The coordinate data within the circular area with a radius of -2.5.

[0028] In step 6, if set A is an empty set, or D max ≤2.5, then the point mean L obtained by the last calculation p This is the final fitting coordinate of the node seismometer.

[0029] The purpose of the present invention can also be achieved by the following technical measures: a node seismograph positioning coordinate rapid fitting device, the node seismograph positioning coordinate rapid fitting device comprising:

[0030] Positioning coordinate conversion module, converting geodetic coordinates into plane rectangular coordinates;

[0031] Data visualization and statistical analysis module, which can display the positioning coordinates graphically and perform statistical analysis on the distribution of coordinate data;

[0032] The fitting coordinate solution module performs iterative fitting of coordinate data and solves the fitting coordinates of the node seismometer;

[0033] The fitting coordinate accuracy analysis module performs accuracy analysis of the node seismometer fitting coordinates, including point error analysis, mean square error analysis, and range analysis.

[0034] The purpose of the present invention can also be achieved by the following technical measures:

[0035] The positioning coordinate conversion module selects the Bursa seven-parameter conversion method or the three-parameter conversion method to convert the WGS84 geodetic coordinates into the Beijing 54 plane rectangular coordinates.

[0036] This data visualization and statistical analysis module displays the location coordinates of node seismometers in the form of a scatter plot, allowing an intuitive understanding of the point distribution; statistically analyzes the horizontal span, vertical span and maximum point spacing of the points; calculates the distance between each location coordinate and the center point, and draws a point distribution histogram.

[0037] The fitting coordinate solution module realizes the positioning coordinate fitting calculation according to the set iteration step size, and quickly iterates and calculates the fitting coordinates of the node seismometer.

[0038] This fitting coordinate accuracy analysis module performs accuracy analysis on the fitted coordinates when the measured coordinates of the node seismometer are known, including the lateral error, longitudinal error and point error between the measured coordinates, and also solves the range and mean square error between the fitted coordinates of seismometers at different nodes.

[0039] The present invention addresses the low positioning accuracy, weak coordinate solution capability, and poor reliability of positioning coordinates of node seismometers with built-in GNSS chips, and proposes a method and device for rapid fitting of node seismometer positioning coordinates. This method iteratively calculates the geometric center point of the positioning coordinate data set, gradually narrowing the core area of ​​the coordinate data. The iterative calculation process is highly efficient, and outlier coordinate data is effectively eliminated, eliminating the bias effect caused by coordinate data far from the geometric center point, so that the fitted coordinates gradually approach the point concentration area. The iterative calculation process of this method is efficient, and the node seismometer positioning coordinates obtained by fitting are highly accurate, which can be used for automatic matching of pile numbers, thereby greatly reducing the workload of field deployment personnel, further improving production efficiency, and reducing acquisition costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 This is a flow chart of a specific embodiment of a method for quickly fitting node seismograph positioning coordinates of the present invention;

[0041] Figure 2 It is a structural diagram of a specific embodiment of a device for quickly fitting node seismograph positioning coordinates of the present invention;

[0042] Figure 3 A scatter diagram showing the distribution of node seismograph positioning coordinates in a specific embodiment of the present invention;

[0043] Figure 4 A distribution histogram of node seismograph location coordinates in a specific embodiment of the present invention;

[0044] Figure 5 Schematic diagram of the iterative fitting process of node seismograph positioning coordinates when the value of Const is 2.5 in a specific embodiment of the present invention;

[0045] Figure 6 Schematic diagram of the iterative fitting process of node seismograph positioning coordinates when the value of Const is 5 in a specific embodiment of the present invention. DETAILED DESCRIPTION

[0046] It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which the present invention belongs.

[0047] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations and / or combinations thereof.

[0048] The node seismograph positioning coordinate fast fitting method of the present invention comprises:

[0049] Step 1: Read the node seismometer positioning coordinate data, and use the Bursa seven-parameter coordinate transformation method to convert the geodetic coordinates into plane rectangular coordinates to obtain the positioning coordinate data set P;

[0050] Step 2: Calculate the point mean M of all coordinate data in set P p , and calculate the distance from each point to M p The distance, calculate the average distance D p ;

[0051] Step 3: Select the same as M from the set P p The distance is less than the positioning coordinates of R, and a new coordinate data set L is obtained;

[0052] Step 4: Calculate the point mean L of all coordinate data in the set p , and find the distance from each point to L p Distance, get the farthest point and the point mean L p The distance D max ;

[0053] Step 5: Set the iteration step length Const, and select the coordinate data whose distance from the point mean is less than Dist from the set to form a new coordinate data set A;

[0054] Step 6: Perform iterative calculations and repeat steps 4-5 until the set A is empty. The point average value L obtained by the last calculation is p This is the final fitting coordinate of the node seismometer.

[0055] The node seismograph positioning coordinate rapid fitting device of the present invention comprises:

[0056] Positioning coordinate conversion module: used to convert WGS84 geodetic coordinates into Beijing 54 plane rectangular coordinates;

[0057] Data visualization and statistical analysis module: used for graphical display of positioning coordinates and statistical analysis of the distribution of coordinate data;

[0058] Fitting coordinate solution module: used for iterative fitting of coordinate data and solving fitting coordinates of node seismometers;

[0059] Fitting coordinate accuracy analysis module: used for accuracy analysis of fitting coordinates of node seismometers, including point error analysis, mean square error analysis, range analysis, etc.

[0060] The following are several specific embodiments of the present invention.

[0061] Example 1:

[0062] In a specific embodiment 1 of the present invention, Figure 1 FIG. 1 is a flow chart of a method for quickly fitting node seismograph positioning coordinates according to the present invention.

[0063] Step 101: Read the node seismograph positioning coordinate data, convert the geodetic coordinates into plane rectangular coordinates, and obtain the positioning coordinate data set P;

[0064] The positioning coordinate data directly read from the node seismometers are all WGS84 geodetic coordinates. In order to facilitate statistical analysis, the WGS84 geodetic coordinates should be converted into Beijing 54 plane rectangular coordinates. The coordinate data in set P are all Beijing 54 plane rectangular coordinates.

[0065] The conversion of WGS84 geodetic coordinates to Beijing 54 plane rectangular coordinates can usually be done by using the seven-parameter or three-parameter conversion method depending on the actual situation.

[0066] Step 102: Calculate the point mean M of all coordinate data in the set P p , and calculate the distance from each point to M p The distance, calculate the average distance D p ;

[0067] The location coordinate data of the node seismometer are randomly distributed points, and the location coordinate data point mean M p Take the simple arithmetic mean of the location coordinate data set.

[0068] Calculate the average value X of the horizontal coordinates of all coordinate data in the set P respectively p And the vertical axis mean Y p , then M p =(X p , Y p ).

[0069] Step 103: Select from set P to M p The positioning coordinates whose distance is less than 4 times the average distance are obtained to obtain a new coordinate data set L;

[0070] According to statistical analysis, as the scale of positioning coordinate data increases, the distribution of points tends to be concentrated, of which 90% of the points are distributed in the M p The center point is the area with R as the radius (core area). R is the average value of 4 times the distance, that is, R = 4*D p .

[0071] Coordinate data beyond the core area are considered outlier data. Because of their large accidental deviations, they should be removed from the overall data and not participate in subsequent iterative calculations. This will control the number of iterations overall while ensuring the accuracy of the fitted coordinates.

[0072] Step 104: Calculate the point mean L of all coordinate data in the set p , and find the distance from each point to L p Distance, get the farthest point and the point mean L p The distance D max ;

[0073] Point mean L p is the simple arithmetic mean of all coordinate data in set L. The method for obtaining it is: respectively obtain the mean value X of the horizontal coordinates of all coordinate data in set L. p And the vertical axis mean Y p , then L p =(X p , Y p ). Maximum distance D max Indicates the farthest point in the set and the point mean L p The distance between them.

[0074] Step 105: Set the iteration step length Const, select the coordinate data whose distance from the point mean is less than Dist from the set, and form a new coordinate data set A;

[0075] The iteration step length Const should be a constant. When it is 2.5, the optimal fitting coordinates can be obtained, so that the mean error between the fitting coordinates and the measured coordinates of the node seismometer is minimized, and the number of iterations is kept small. Dist is the difference between the maximum distance and the iteration step length, that is: Dist = D max -2.5.

[0076] The number of iterations and the accuracy of the fitted coordinates can be controlled by changing the iteration step Const value according to actual needs. As the value of Const increases, the number of iterations decreases, and the error of the final fitted coordinate point increases.

[0077] Step 106: Perform iterative calculations and repeat steps 4-5 until the set A is empty. The point average value L obtained by the last calculation is p This is the final fitting coordinate of the node seismometer.

[0078] If set A is not empty, and D max >2.5, then continue to recalculate the point mean L of all coordinate data in set A p , find the distance from each point to L p Distance, get the maximum distance D max At this time, the coordinate data in set A is L p The center point D max The coordinate data within the circular area with a radius of -2.5.

[0079] If set A is an empty set, or D max ≤2.5, then the point mean L obtained by the last calculation p This is the final fitting coordinate of the node seismometer.

[0080] Example 2:

[0081] In a specific embodiment 2 of the present invention, as Figure 2 FIG. 1 is a structural diagram of a device for quickly fitting node seismograph positioning coordinates according to the present invention, the device comprising:

[0082] Positioning coordinate conversion module 201, used for converting WGS84 geodetic coordinates into Beijing 54 plane rectangular coordinates, and the coordinate conversion can choose seven-parameter conversion method or three-parameter conversion method;

[0083] The data visualization and statistical analysis module 202 is used to graphically display positioning coordinates and statistically analyze the distribution of coordinate data. The positioning coordinates of the node seismometers can be displayed in the form of a scatter plot to intuitively understand the point distribution. The horizontal span, vertical span, and maximum point spacing of the points can be statistically analyzed. The distance between each positioning coordinate and the center point can be calculated and a point distribution histogram can be plotted.

[0084] The fitting coordinate solution module 203 is used for iterative fitting of coordinate data and solution of fitting coordinates of node seismometers. This module can realize positioning coordinate fitting calculation according to the set iteration step size and quickly iterate and calculate the fitting coordinates of node seismometers.

[0085] The fitting coordinate accuracy analysis module 204 is used to analyze the accuracy of the fitting coordinates of the node seismometers, including point error analysis, mean square error analysis, and range analysis. Given the measured coordinates of the node seismometers, this module can perform accuracy analysis on the fitting coordinates, including lateral error, longitudinal error, and point error compared to the measured coordinates. It can also calculate the range and mean square error between the fitted coordinates of different node seismometers.

[0086] Example 3:

[0087] In specific embodiment 3 of the present invention, in order to achieve automatic matching of pile numbers, the point error of the fitting coordinates of the node seismometer should be within 1 / 2 of the track spacing. If calculated based on a track spacing of 25 meters, the point error of the fitting coordinates of the node seismometer should be limited to within 12.5 meters, that is: ΔS≤12.5m.

[0088] Read the node seismograph positioning coordinate data, convert the geodetic coordinates into plane rectangular coordinates, calculate the point mean of the coordinate data, and the distance from each point to the point mean, then calculate the average distance, and select the coordinate data in the area with the point mean as the center point and 4 times the average distance as the radius as the core data for iterative calculation. By continuously recalculating the point center point of the core area and using D max -2.5 is the radius, and the core area is continuously reduced until there are no point coordinates or D in the core area. max If the value is ≤2.5, the center point of the core area obtained from the last calculation is the fitting coordinate of the node seismometer. This method can quickly fit the node seismometer positioning coordinates and control the point position error within 1 / 2 track spacing, meeting the accuracy requirements of automatic stake number matching.

[0089] Example 4:

[0090] In the specific embodiment 4 of the present invention, as Figure 3 As shown in FIG, it is a scatter diagram of the distribution of node seismograph positioning coordinates in a specific embodiment; Figure 4 As shown in FIG, it is a histogram of the node seismograph location coordinate distribution in a specific embodiment; Figure 5 FIG. 1 is a schematic diagram of the iterative fitting process of a node seismometer in a specific embodiment. The specific implementation includes the following steps:

[0091] Step 1: Read the node seismograph positioning coordinate data. This coordinate data is the node seismograph WGS84 geodetic coordinate recorded by the node seismograph for 16 hours of observation. All four geodetic coordinates are converted into Beijing 54 plane rectangular coordinates using the Bursa seven-parameter transformation method.

[0092] Step 2: The location coordinate data of the node seismometer is randomly distributed, and the point mean M p It can be expressed by a simple arithmetic mean. Calculate the horizontal coordinate average value X of all coordinate data in the set P respectively p And the vertical axis mean Y p , then M p =(X p , Y p ).

[0093] Step 3: According to Figure 4 As shown, more than 95% of the points are distributed in M p The center point is within an area with a radius of 4 times the average distance.

[0094] Step 4: The coordinate data beyond the core area are regarded as outlier data. Because of their large accidental deviation, they should be removed from the overall data and not participate in the subsequent iteration process. The number of iterations is controlled as a whole, while ensuring the accuracy of the fitting coordinates.

[0095] Step 5: Calculate the average value X of the horizontal coordinates of all coordinate data in the set L p And the vertical axis mean Y p , then the point mean L p =(X p , Y p ), then find the points and L p The maximum distance D is obtained max .

[0096] Step 6: Through continuous iteration, calculate the mean value of the coordinates of the coordinate data set, gradually eliminate the deviation caused by the coordinate data far from the center point, and make the solved coordinates gradually approach the point concentration area. At the same time, the number of iterations and the error of the fitted coordinate points can be controlled by changing the value of Const. Figure 5 As shown in the figure, when Const = 2.5, after 27 iterations, the node seismometer fitting coordinates are finally obtained. Its horizontal coordinate X p =629811.819m, vertical coordinate Y p =4142331.300m. The measured horizontal coordinate X of the node seismometer s =629812.130m, measured vertical coordinate Y s =4142331.066m, the position error is 0.389m; Figure 6 As shown in the figure, when Const = 5, after 14 iterations, the node seismometer fitting coordinates are finally obtained. p =629811.008m, vertical coordinate Y p =4142330.944m. The measured horizontal coordinate X of the node seismometer s =629812.130m, measured vertical coordinate Y s =4142331.066m, the point error is 1.129m.

[0097] The node seismograph positioning coordinate rapid fitting method of the present invention has high iterative calculation efficiency, effectively eliminates outlier coordinate data, eliminates the deviation influence brought by coordinate data far away from the geometric center point, and makes the fitting coordinates gradually approach the point concentration area. The node seismograph positioning coordinates obtained by fitting have high accuracy and can be used for automatic matching of pile numbers without manual deployment of pile numbers, thereby greatly reducing the workload of field deployment personnel, further improving production efficiency, and reducing acquisition costs.

[0098] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art may still modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features therein. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

[0099] Except for the technical features described in the specification, all other technical features are known technologies to those skilled in the art.

Claims

1. A fast fitting method for node seismograph positioning coordinates, characterized in that: The node seismograph positioning coordinate fast fitting method includes: Step 1, obtain the positioning coordinate data set P; Step 2: Calculate the point mean M of all coordinate data in set P p , and calculate the distance from each point to M p The distance between p ; Step 3: Select the same p The distance is less than the positioning coordinates of R, and a new coordinate data set L is obtained; Step 4: Calculate the point mean L of all coordinate data in set L p , and find the distance from each point to L p Distance, get the farthest point and the point mean L p The distance D max ; Step 5, set the iteration step length Const, select the coordinate data whose distance from the point mean is less than Dist from the set L, and form a new coordinate data set A; Step 6: Perform iterative calculation to obtain the final fitting coordinates of the node seismometer.

2. The node seismograph positioning coordinate fast fitting method according to claim 1, characterized in that: In step 1, the node seismograph positioning coordinate data is read, and the Bursa seven-parameter coordinate transformation method is used to transform the geodetic coordinates into plane rectangular coordinates to obtain the positioning coordinate data set P.

3. The node seismograph positioning coordinate fast fitting method according to claim 1, characterized in that: In step 2, calculate the average value X of the horizontal coordinates of all coordinate data in set P. p And the vertical axis mean Y p , then M p =(X p , Y p ).

4. The node seismograph positioning coordinate fast fitting method according to claim 1, characterized in that: In step 3, according to statistical analysis, as the size of the positioning coordinate data increases, the point distribution tends to be concentrated, and 90% of the points are distributed in the M p The area with R as the radius is the core area, and R is the average value of 4 times the distance, that is, R = 4*D p ; The coordinate data beyond the core area are regarded as outlier data. Because of their large accidental deviations, they should be eliminated from the overall data and not participate in the subsequent iterative calculations. The number of iterations is controlled as a whole, while ensuring the accuracy of the fitting coordinates.

5. The node seismograph positioning coordinate fast fitting method according to claim 1, characterized in that: In step 4, the point mean L p is the simple arithmetic mean of all coordinate data in set L. The method for obtaining it is: respectively obtain the horizontal coordinate mean value X of all coordinate data in set L p And the vertical axis mean Y p , then L p =(X p , Y p );D max Indicates the farthest point in the set and the point mean L p The distance between.

6. The node seismograph positioning coordinate fast fitting method according to claim 1, characterized in that: In step 5, the iteration step length Const should be a constant. When the value is 2.5, the optimal fitting coordinates can be obtained, so that the mean value of the position error between the fitting coordinates and the measured coordinates of the node seismometer is minimized, and a small number of iterations is guaranteed; Dist is the difference between the maximum distance and the iteration step length, that is: Dist = D max -2.5; In practical applications, the number of iterations and the accuracy of fitting coordinates can be controlled by changing the iteration step Const value; as the Const value increases, the number of iterations decreases, and the final fitting coordinate point error increases.

7. The node seismograph positioning coordinate fast fitting method according to claim 1, characterized in that: In step 6, perform iterative calculations and repeat steps 4-5. If set A is not an empty set and D max >2.5, then continue to recalculate the point mean L of all coordinate data in set A p , find the distance from each point to L p Distance, get the maximum distance D max ; At this time, the coordinate data in set A is L p The center point D max The coordinate data within the circular area with a radius of -2.

5.

8. The node seismograph positioning coordinate fast fitting method according to claim 7, characterized in that: In step 6, if set A is an empty set, or D max ≤2.5, then the point mean value L obtained by the last calculation p That is the final fitting coordinate of the node seismometer.

9. A device for quickly fitting node seismograph positioning coordinates, characterized in that: The node seismograph positioning coordinate fast fitting device comprises: Positioning coordinate conversion module, converting geodetic coordinates into plane rectangular coordinates; Data visualization and statistical analysis module, which can display the positioning coordinates graphically and analyze the distribution of coordinate data statistically; The fitting coordinate solution module performs iterative fitting of coordinate data and solves the fitting coordinates of the node seismometer; The fitting coordinate accuracy analysis module performs accuracy analysis of the node seismometer fitting coordinates, including point error analysis, mean square error analysis, and range analysis.

10. The node seismograph positioning coordinate rapid fitting device according to claim 9, characterized in that: The data visualization and statistical analysis module displays the location coordinates of the node seismometer in the form of a scatter plot; statistically analyzes the horizontal span, vertical span and maximum point spacing of the point; counts the distance between each location coordinate and the center point, and draws a point distribution histogram.

11. The node seismograph positioning coordinate rapid fitting device according to claim 9, characterized in that: The fitting coordinate solution module realizes the positioning coordinate fitting calculation according to the set iteration step size, and quickly iterates and calculates the fitting coordinates of the node seismometer.

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