A method and system for identifying height anomaly and a height measurement system

Abstract

The present invention relates to the field of surveying and mapping technology, and provides a method and system for identifying height anomalies and a height measurement system, including the following steps: obtaining the coordinates of known control points within a target measurement area, and calculating the height difference based on the geodetic height of the control points and the height datum; respectively calculating the mean square error of the height difference of each control point, and determining whether the mean square error of the height difference is greater than a preset first threshold: if so, perform a secondary determination; otherwise, determine that there is no height anomaly; selecting a regional gravity model file, calculating the height anomaly value of the control points, and then calculating the relative level height; calculating the systematic error based on the relative level height of the control points and the height datum; using the mean value of the systematic error as the true value, and calculating the mean square error of the systematic error; determining whether the mean square error of the systematic error is less than a preset second threshold: if so, determine that there is a height anomaly, otherwise, check the correctness of the geodetic height and the height datum of the input target measurement point.

Description

Technical Field

[0001] The present invention relates to the field of surveying and mapping technology, and more specifically, to a method and system for identifying height anomalies and a height measurement system. Background Art

[0002] The height obtained by GNSS measurement is the geodetic height, which takes the ellipsoid surface as the starting surface, so it is also called the ellipsoidal height; while in actual production practice, the required measured height is the normal height. Whether it is the 56 Huanghai height datum or the National 85 height datum, both take the quasi-geoid as the starting surface.

[0003] Currently, to convert the height data obtained by GNSS measurement into the normal height required for production practice, methods such as fixed deviation calculation, plane fitting, and surface fitting are generally used. Among them, when the gravity field distribution in the measured area is uneven, height anomalies may occur, and the normal height cannot be directly obtained through fixed deviation calculation, and fitting is required; when the number of control points in the measured area is small or the distribution of control points is uneven, if fitting is directly carried out without judging whether the height data has anomalies, the measured normal height deviation will be too large, even reaching the meter level. In addition, in areas with a large number of control points, although the geoid refinement model can be used for correction, most of the data of this model is classified data, and individuals cannot obtain it due to data security reasons, so there are certain limitations in actual applications. Summary of the Invention

[0004] The present invention aims to overcome the defect that height anomalies cannot be accurately identified when converting the height data obtained by GNSS measurement into the normal height, and provides a method and system for identifying height anomalies, and a height measurement system.

[0005] To solve the above technical problems, the technical solution of the present invention is as follows:

[0006] A method for identifying height anomalies includes the following steps:

[0007] S1. Obtain the coordinates of known control points in the target measurement area, and calculate the height difference according to the geodetic height of the control points and the height datum;

[0008] S2. Take the mean value of the height differences as the true value, calculate the mean square error of the height difference corresponding to each control point respectively, and judge whether the mean square error of the height difference is greater than a preset first threshold: if so, execute step S3; otherwise, it is judged that there are no height anomalies in the target measurement area;

[0009] S3. Select the regional gravity model file corresponding to the target measurement area from the EGM08 global gravity model, calculate the height anomaly value of the control points according to the regional gravity model file, and then calculate the relative leveling height of the control points according to the geodetic height of the control points and their height anomaly values.

[0010] S4. Calculate the systematic error based on the relative level height and elevation datum of the control points.

[0011] S5. Use the mean value of the systematic error as the true value, and calculate the mean square error of the systematic error; determine whether the mean square error of the systematic error is less than a preset second threshold: if so, it is determined that there is an elevation anomaly in the target measurement area; otherwise, check the correctness of the geodetic height of the input target measurement points and the elevation datum.

[0012] Furthermore, the present invention also proposes an elevation anomaly identification system, which is applied to execute the above-mentioned elevation anomaly identification method. It specifically includes a data acquisition module, a first calculation module, a first judgment module, a gravity model file reading module, a second calculation module, a second judgment module, and an inspection module.

[0013] Among them, the data acquisition module is used to acquire the coordinates of several control points in the target measurement area and their corresponding elevation datums. The first calculation module is used to calculate the elevation difference of the control points based on the geodetic height and elevation datum of the control points, and then use the mean value of the elevation differences as the true value to calculate the mean square error of the elevation difference corresponding to each control point respectively. The first judgment module is used to determine whether the mean square error of the elevation difference is greater than a preset first threshold. If so, it sends a working signal to the second calculation module; otherwise, it directly outputs the recognition result that there is no elevation anomaly in the target measurement area. The gravity model file reading module is used to select the regional gravity model file corresponding to the target measurement area from the global gravity model and obtain the corresponding anomaly data. The second calculation module is used to calculate the elevation anomaly value of the control points; calculate the relative level height of the control points based on the geodetic height and its elevation anomaly value of the control points; calculate the systematic error based on the relative level height and elevation datum of the control points; use the mean value of the systematic error as the true value to calculate the mean square error of the systematic error. When the second calculation module receives the working signal, it sends a signal to the gravity model file reading module, and the gravity model file reading module returns the read regional gravity model file and its anomaly data to the second calculation module. The second judgment module is used to determine whether the mean square error of the systematic error is less than a preset second threshold. If so, it outputs the recognition result that there is an elevation anomaly in the target measurement area; if not, it sends a working signal to the inspection module; the inspection module checks the input correctness of the geodetic height and its corresponding elevation datum acquired by the coordinate data acquisition module and outputs the data correctness inspection result.

[0014] Furthermore, the present invention further provides an elevation measurement system, including a GNSS device, the above-mentioned elevation anomaly identification system, and a calibration module for calibrating the geodetic height according to the elevation anomaly identification result, wherein: the GNSS device measures the coordinates of unknown points in the target measurement area, and at the same time, the elevation anomaly identification system identifies the elevation anomaly in the target measurement area and sends the identification result to the calibration module; when the identification result received by the calibration module indicates the existence of an elevation anomaly, the surface fitting method or the leveling model method is used to calibrate the elevation of the unknown point; when the identification result received by the calibration module indicates the non-existence of an elevation anomaly, the elevation of the unknown point is calibrated according to the fixed offset value of the target measurement area.

[0015] Compared with the prior art, the beneficial effects of the technical solution of the present invention are: the present invention identifies the elevation anomaly and its abnormal cause through secondary judgment, and with the help of the EGM08 global gravity model, through the system error difference, it identifies whether there is an elevation anomaly in the unknown point in the GNSS elevation measurement, which can effectively improve the accuracy of elevation anomaly identification. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a flowchart of the elevation anomaly identification method in Embodiment 1.

[0017] Figure 2 It is a flowchart of the elevation anomaly identification method in Embodiment 2.

[0018] Figure 3 It is an architecture diagram of the elevation anomaly identification system in Embodiment 3.

[0019] Figure 4 It is an architecture diagram of the elevation measurement system in Embodiment 4. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0020] The drawings are only for illustrative purposes and should not be construed as a limitation of this patent;

[0021] For those skilled in the art, it is understandable that some well-known structures and their descriptions in the drawings may be omitted.

[0022] The technical solution of the present invention will be further described below with reference to the drawings and embodiments.

[0023] Embodiment 1

[0024] This embodiment provides an elevation anomaly identification method, as Figure 1 shown, it is a flowchart of the elevation anomaly identification method in this embodiment.

[0025] In the elevation anomaly identification method provided in this embodiment, it specifically includes the following steps:

[0026] S1. Obtain the coordinates of known control points within the target measurement area, and calculate the elevation difference based on the geodetic height of the control points and the elevation datum.

[0027] In this embodiment, the coordinates of the known control points within the target measurement area are obtained from the data provided by the Surveying and Mapping Bureau, or a control network is manually set up, and RTK is used to measure from high-level points and used as the starting data, and then obtained through adjustment calculation. The coordinates of the control points in this embodiment include the geodetic longitude B, geodetic latitude L, and geodetic height H in the spherical coordinate system.

[0028] The elevation datum in this embodiment adopts the 1985 National Elevation Datum and / or the 56 Huanghai Elevation Datum.

[0029] In a specific embodiment, the WGS84 geodetic height of the known point is subtracted from the consistent National 85 Elevation to obtain the elevation difference.

[0030] S2. Take the mean value of the elevation differences as the true value, calculate the mean error of the elevation difference corresponding to each control point respectively, and judge whether the mean error of the elevation difference is greater than a preset first threshold: if so, execute step S3; otherwise, it is judged that there is no elevation anomaly within the target measurement area.

[0031] In this step, the mean value of the elevation differences of all known points is used as a reference value, and then the deviation between the elevation difference corresponding to each known control point and this reference value is calculated as the mean error of the elevation difference, and further a first judgment is made through the mean error of the elevation difference and the preset first threshold.

[0032] Among them, when the mean error of the elevation difference exceeds the first threshold, it indicates that there may be an elevation anomaly caused by the gravity field, or it may be due to data entry reasons, and further judgment is needed.

[0033] In a specific embodiment, considering that the RTK elevation measurement accuracy is 3 - 5 cm, and the first judgment only realizes preliminary anomaly identification, the first threshold is set to 10 - 15 cm.

[0034] In a specific embodiment, when the mean error of the elevation difference exceeds the first threshold, first check the correctness of the geodetic height of the input target measurement point and the elevation datum. If it is checked that the data input is incorrect, output the inspection result, and the staff can judge whether it is necessary to correct the geodetic height of the target measurement point and its elevation datum according to the output inspection result, and then execute step S3.

[0035] S3. Select the regional gravity model file corresponding to the target measurement area from the EGM08 global gravity model, calculate the elevation anomaly value of the control points according to the regional gravity model file, and then calculate the relative level height of the known control points according to the geodetic height of the control points and their elevation anomaly values.

[0036] The specific steps are as follows:

[0037] S3.1. Obtain the regional gravity model file corresponding to the target measurement area from the EGM08 global gravity model through the leveling segmentation tool;

[0038] S3.2. According to the coordinates of the known control points, read the anomaly data at the grid positions corresponding to the coordinates in the regional gravity model file, and then calculate the elevation anomalies of all control points in the target measurement area through interpolation processing of the anomaly data;

[0039] Among them, in this embodiment, biquadratic interpolation method, bilinear interpolation method and / or bicubic spline interpolation method are used to interpolate the anomaly data;

[0040] S3.3. Calculate the relative leveling height of the control points according to the geodetic height and elevation anomaly of the control points.

[0041] In this step, the WGS84 geodetic height of the control point is subtracted from the elevation anomaly to obtain the relative leveling height of the control point.

[0042] S4. Calculate the systematic error according to the relative leveling height of the control points and the elevation datum.

[0043] S5. Take the mean value of the systematic error as the true value, and calculate the mean square error of the systematic error; determine whether the mean square error of the systematic error is less than a preset second threshold: if so, it is determined that there is an elevation anomaly in the target measurement area; if not, check the correctness of the geodetic height of the input target measurement point and the elevation datum, and determine whether the input data is abnormal.

[0044] In the second judgment process, with the help of the EGM08 global gravity model, identify whether there is an elevation anomaly in the corresponding control points through the systematic error difference. When the mean square error of the systematic error is lower than the preset second threshold, it is determined that there is an elevation anomaly caused by the gravity field. When the mean square error of the systematic error exceeds the preset second threshold, there may be a problem with the input data. At this time, it is necessary to further check the correctness of the geodetic height of the input target measurement point and the elevation datum. When it is checked that the geodetic height of the input target measurement point and the elevation datum are abnormal, output the corresponding inspection result, and the staff can judge whether it is necessary to correct the geodetic height of the target measurement point and its elevation datum according to the output inspection result; when it is checked that the input data is correct, it means that there is no elevation anomaly in the target measurement area.

[0045] In this embodiment, the height anomaly is preliminarily detected and judged through the first judgment. When there is indeed an anomaly, the EGM08 global gravity model is combined to further judge the cause of the anomaly through the system error difference, such as: the height anomaly caused by the gravity field, the height anomaly caused by incorrect data entry.

[0046] In a specific implementation process, as shown in Table 1 below, the WGS84 geodetic height of the known point is subtracted from the known national 85 height to obtain the height difference.

[0047] Table 1 Height Difference

[0048]

[0049]

[0050]

[0051] Based on the data shown in the above table, the mean value N of the height difference is further calculated, and then the mean square error is obtained as 23.5 cm. At this time, the mean square error of the height difference is greater than the first threshold (15 cm), so it is determined that there is a height anomaly and further judgment is required.

[0052] The regional gravity model file corresponding to the target measurement area is obtained from the EGM08 global gravity model through the leveling segmentation tool. According to the latitude B and longitude L of the WGS84 ellipsoid of the known control point data, the anomaly data of the corresponding grid in the regional gravity model file is read, and then the interpolated processing is performed on the read anomaly data to calculate the height anomaly value at the control point position; then the 84 geodetic height is subtracted from the height anomaly to obtain the relative leveling height.

[0053] The national 85 height of the known point is subtracted from the calculated relative leveling height to obtain a list of system errors, as shown in Table 2 below. Further, taking the mean value of the system error as the true value, the mean square error of the system error is calculated. If the mean square error is less than the specified threshold, there is a height anomaly in the measurement area.

[0054] Table 2 System Error List

[0055]

[0056]

[0057]

[0058] As can be seen from Table 2, the calculated mean value is 5.0 cm and the variance is 3.3 cm. Thus, it can be identified that there is a height anomaly in this measurement area.

[0059] Embodiment 2

[0060] This embodiment proposes a method for identifying height anomalies, as Figure 2 shown, which is the flowchart of the height anomaly identification in this embodiment.

[0061] Based on the method for identifying height anomalies proposed in Embodiment 1, the following steps are further included:

[0062] Measure the coordinates of unknown points in the target measurement area through GNSS to obtain the geodetic longitude B, geodetic latitude L, and geodetic height H of the unknown points in the spherical coordinate system of the earth. Then, calibrate the height of the unknown points according to the judgment result of whether there is a height anomaly in the corresponding measurement area: if there is no height anomaly, directly calibrate the height of the unknown points according to the fixed offset value of the target measurement area; if there is a height anomaly, use the surface fitting method or the leveling model method to calibrate the height of the unknown points.

[0063] In this embodiment, the method for identifying height anomalies proposed in Embodiment 1 is further applied to the identification of height anomalies of unknown points, or directly applied to height measurement, which is convenient for ordinary measurement users to use.

[0064] Embodiment 3

[0065] This embodiment proposes a height anomaly identification system, as Figure 3 shown, which is the architecture diagram of the height anomaly identification system in this embodiment.

[0066] The height anomaly identification system proposed in this embodiment includes a data acquisition module 1, a first calculation module 2, a first judgment module 3, a gravity model file reading module 4, a second calculation module 5, a second judgment module 6, and an inspection module 7.

[0067] Among them, the data acquisition module 1 is used to acquire the coordinates of several control points in the target measurement area and their corresponding height benchmarks.

[0068] The first calculation module 2 is used to calculate the height difference of the control points according to the geodetic height and the height benchmark of the control points, and then use the mean value of the height differences as the true value to calculate the mean square error of the height difference corresponding to each control point respectively.

[0069] The first judgment module 3 is used to judge whether the mean square error of the height difference is greater than a preset first threshold. If so, send a working signal to the second calculation module 5; otherwise, directly output the recognition result that there is no height anomaly in the target measurement area.

[0070] The gravity model file reading module 4 is used to select the regional gravity model file corresponding to the target measurement area from the global gravity model and obtain the corresponding anomaly data.

[0071] The second calculation module 5 is used to calculate the elevation anomaly value of the control point; calculate the relative level height of the control point according to the geodetic height of the control point and its elevation anomaly value; calculate the systematic error according to the relative level height of the control point and the elevation datum; use the mean value of the systematic error as the true value, and calculate the mean square error of the systematic error.

[0072] When the second calculation module 5 receives the working signal, the second calculation module 5 sends a signal to the gravity model file reading module 4, and the gravity model file reading module 4 returns the read regional gravity model file and its anomaly data to the second calculation module 5.

[0073] The second judgment module 6 is used to judge whether the mean square error of the systematic error is less than a preset second threshold. If so, it outputs the recognition result that there is an elevation anomaly in the target measurement area; if not, it sends a working signal to the inspection module 7.

[0074] The inspection module 7 is used to check the input correctness of the geodetic height obtained by the coordinate data acquisition module 1 and its corresponding elevation datum, and output the data correctness inspection result.

[0075] In the specific implementation process, the data acquisition module 1 directly obtains the coordinate data of the control point from the surveying and mapping bureau, or measures the coordinate of the control point through a GNSS device, further obtains its corresponding elevation datum according to the geodetic height in the coordinate, and then sends it to the first calculation module 2.

[0076] The first calculation module 2 calculates the elevation difference according to the geodetic height of the control point and the elevation datum, and then uses the mean value of the elevation difference as the true value to calculate the mean square error of the elevation difference corresponding to each control point respectively. The first calculation module 2 sends the mean square error of the elevation difference it calculates to the first judgment module 3 for judgment.

[0077] The first judgment module 3 judges whether the mean square error of the elevation difference is greater than a preset first threshold. If so, it sends a working signal to the second calculation module 5, otherwise it directly outputs the recognition result that there is no elevation anomaly in the target measurement area.

[0078] When the second calculation module 5 receives the working signal, the second calculation module 5 sends a working signal to the gravity model file reading module 4. The gravity model file reading module 4 selects the regional gravity model file corresponding to the target measurement area from the global gravity model, and obtains the corresponding anomaly data, and then returns it to the second calculation module 5. Among them, the anomaly data read by the gravity model file reading module 4 is the anomaly data at the grid position corresponding to the coordinate in the regional gravity model file. The gravity model file reading module 4 performs interpolation processing on the read anomaly data to obtain the elevation anomaly value of the control point.

[0079] The second calculation module 5 calculates the elevation anomaly value of the control point according to the regional gravity model file, then calculates the relative level height of the control point based on the geodetic height and its elevation anomaly value of the control point, and further calculates the system error list according to the relative level height of the control point and the elevation datum; then uses the mean value of the system error as the true value to calculate the mean square error of the system error. The second calculation module 5 sends the mean square error of the system error it calculates to the second judgment module 6 to perform the second elevation anomaly judgment.

[0080] The second judgment module 6 judges whether the mean square error of the system error it currently receives is less than a preset second threshold. If so, it is judged that there is an elevation anomaly in the target measurement area; otherwise, it sends a working signal to the inspection module 7. The inspection module 7 further checks the input correctness of the geodetic height and its corresponding elevation datum obtained by the coordinate data acquisition module 1, and outputs the data correctness inspection result for the staff to judge whether it is necessary to correct the input data.

[0081] In another embodiment, when the first judgment module 3 judges that the mean square error of the elevation difference is greater than a preset first threshold, the first judgment module 3 sends a working signal to the inspection module 7. The inspection module 7 further checks the input correctness of the geodetic height and its corresponding elevation datum obtained by the coordinate data acquisition module 1. When the inspection result of the inspection module 7 is that the data is correct, the inspection module 7 feeds back the inspection result to the first judgment module 3, and the first judgment module 3 then sends a working signal to the second calculation module 5.

[0082] Embodiment 4

[0083] This embodiment proposes an elevation measurement system, as Figure 4 shown, which is the architecture diagram of the elevation measurement system of this embodiment.

[0084] In the elevation measurement system proposed in this embodiment, it includes a GNSS device 8 and an elevation anomaly detection system proposed in Embodiment 3, and a calibration module 9 for calibrating the geodetic height according to the elevation anomaly identification result.

[0085] In this embodiment, the GNSS device 8 measures the coordinates of unknown points in the target measurement area. At the same time, the elevation anomaly identification system identifies the elevation anomaly in the target measurement area and sends the identification result to the calibration module 9; when the identification result received by the calibration module 9 is that there is an elevation anomaly, the surface fitting method or the level model method is used to calibrate the elevation of the unknown point; when the identification result received by the calibration module 9 is that there is no elevation anomaly, the elevation of the unknown point is calibrated according to the fixed offset value of the target measurement area.

[0086] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, rather than limitations on the implementation manners of the present invention. For those of ordinary skill in the art, other different forms of changes or alterations can be made based on the above description. It is not necessary and impossible to enumerate all implementation manners here. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the claims of the present invention.

Claims

1. A method for identifying height anomaly, characterized in that, Including the following steps: S1. Obtain the coordinates of known control points within the target measurement area, and calculate the elevation difference based on the geodetic height of the control points and the elevation datum. S2. Use the mean value of the elevation differences as the true value, calculate the mean square error of the elevation difference corresponding to each control point, and determine whether the mean square error of the elevation difference is greater than a preset first threshold: If so, execute step S3; otherwise, it is determined that there is no elevation anomaly within the target measurement area. S3. Select the regional gravity model file corresponding to the target measurement area from the EGM08 global gravity model, calculate the elevation anomaly value of the control points according to the regional gravity model file, and then calculate the relative leveling height of the control points based on the geodetic height of the control points and their elevation anomaly values. Specifically, it includes the following steps: S3.

1. From the EGM08 global gravity model, obtain the regional gravity model file corresponding to the target measurement area through the leveling segmentation tool. S3.

2. According to the coordinates of the known control points, read the anomaly data at the grid positions corresponding to the coordinates in the regional gravity model file, and then calculate the elevation anomaly values of all control points within the target measurement area through interpolation processing of the anomaly data. S3.

3. Calculate the relative leveling height of the control points based on the geodetic height of the control points and their elevation anomaly values. S4. Calculate the systematic error based on the relative leveling height of the control points and the elevation datum. S5. Use the mean value of the systematic error as the true value, calculate the mean square error of the systematic error; determine whether the mean square error of the systematic error is less than a preset second threshold: If so, it is determined that there is an elevation anomaly within the target measurement area, otherwise, check the correctness of the geodetic height of the input target measurement point and the elevation datum.

2. The height anomaly recognition method according to claim 1, wherein In step S3.2, any one of the biquadratic interpolation method, bilinear interpolation method, and bicubic spline interpolation method is used to perform interpolation processing on the anomaly data.

3. The height anomaly recognition method according to claim 1, characterized in that The elevation datum includes the 1985 National Elevation Datum or the 1956 Huanghai Elevation Datum.

4. The method for identifying height anomaly according to claim 1, characterized in that The first threshold is set to 10 - 15 cm, and the second threshold is set to 5 - 10 cm.

5. The height anomaly identification method according to any one of claims 1 to 4, characterized in that It further includes the following steps: Measure the coordinates of unknown points within the target measurement area through GNSS, and calibrate the elevation of the unknown points according to the judgment result of whether there is an elevation anomaly in the corresponding measurement area: If there is no elevation anomaly, directly calibrate the elevation of the unknown points according to the fixed offset value of the target measurement area. If there is an elevation anomaly, use the surface fitting method or the leveling model method to calibrate the elevation of the unknown points.

6. An elevation anomaly recognition system applying the method described in any one of claims 1 to 5, characterized in that, Including: A data acquisition module for obtaining the coordinates of several control points within the target measurement area and their corresponding elevation datum. A first calculation module for calculating the elevation difference of the control points based on the geodetic height of the control points and the elevation datum, and then using the mean value of the elevation differences as the true value to calculate the mean square error of the elevation difference corresponding to each control point. A first judgment module for determining whether the mean square error of the elevation difference is greater than a preset first threshold. If so, send a working signal to the second calculation module; otherwise, directly output the recognition result that there is no elevation anomaly within the target measurement area. A gravity model file reading module, which is used to select a regional gravity model file corresponding to a target measurement area from a global gravity model and obtain corresponding anomaly data; A second calculation module, which is used to calculate the elevation anomaly value of a control point; and calculate the relative level height of the control point according to the geodetic height and the elevation anomaly value of the control point; Calculate the systematic error according to the relative level height of the control point and the elevation datum; use the mean value of the systematic error as the true value, and calculate the mean square error of the systematic error; When the second calculation module receives a working signal, the second calculation module sends a signal to the gravity model file reading module, and the gravity model file reading module returns the read regional gravity model file and its anomaly data to the second calculation module; A second judgment module, which is used to judge whether the mean square error of the systematic error is less than a preset second threshold. If so, output the recognition result that there is an elevation anomaly in the target measurement area; If not, send a working signal to the inspection module; An inspection module, which is used to inspect the input correctness of the geodetic height and its corresponding elevation datum obtained by the coordinate data acquisition module, and output the data correctness inspection result.

7. An elevation measurement system, characterized in that, An elevation anomaly recognition system, including a GNSS device and as described in claim 6, and a calibration module for calibrating the geodetic height according to the elevation anomaly recognition result, wherein: The GNSS device measures the coordinates of unknown points in the target measurement area, and at the same time the elevation anomaly recognition system recognizes the elevation anomaly in the target measurement area and sends the recognition result to the calibration module; when the recognition result received by the calibration module is that there is an elevation anomaly, the elevation of the unknown point is calibrated by using the surface fitting method or the level model method; when the recognition result received by the calibration module is that there is no elevation anomaly, the elevation of the unknown point is calibrated according to the fixed offset value of the target measurement area.

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