Geodetic mapping method based on two-way round-trip zero drift rate correction of gravimeter

Abstract

The present invention discloses a geodetic surveying method based on two-way round-trip zero drift rate correction of a gravimeter, relates to the technical field of surveying and mapping, and is used to solve the problem that a surveying path may be affected by factors such as the environment, and that the zero drift error of a gravimeter may gradually accumulate over time, resulting in systematic deviations in measurement data, which requires regular correction. The method comprises collecting analysis data required for the surveying path, including the symmetry of the path and the real-time environment of the path, pre-processing the data and storing the data in a database; retrieving data from the database to respectively evaluate the symmetry and real-time environment of the path; and using TOPSIS to comprehensively analyze the symmetry and real-time environment of the path, thereby selecting a suitable surveying path. By real-time monitoring of the zero drift rate of the gravimeter, setting a reasonable threshold, and dynamically adjusting the regular correction time according to the zero drift rate, the accuracy and reliability of gravity measurement data can be effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of surveying and mapping technology, and more particularly to a geodetic surveying and mapping method based on two-way round-trip zero drift rate correction of a gravimeter. Background Art

[0002] Gravimeter round-trip zero drift correction is used to reduce or eliminate zero drift errors in gravity measurements. This method utilizes the symmetry of the forward and reverse measurement paths. By comparing and correcting the two measurement data, it can effectively reduce or eliminate the zero drift error of the gravimeter.

[0003] Geodesy is a science that studies the shape, size and gravity field distribution of the Earth. It is mainly used in surveying and mapping, navigation, geographic information systems (GIS) and earth science research.

[0004] The geodetic surveying method based on the two-way round-trip zero drift rate correction of the gravimeter is a technology that improves the geodetic surveying accuracy by correcting the zero drift error of the gravimeter.

[0005] The existing geodetic mapping process for gravity involves selecting a mapping path during the preparation phase, which is a key step in ensuring the accuracy of the measured data. However, the mapping path is affected by factors such as the environment, and the zero drift error of the gravimeter gradually accumulates over time, leading to systematic deviations in the measured data, which requires regular correction. Therefore, this application proposes a geodetic mapping method based on the round-trip zero drift rate of the gravimeter. The method aims to select an appropriate mapping path and dynamically adjust the time of regular corrections to ensure the accuracy and reliability of the data.

[0006] In view of the above problems, the present invention proposes a solution. Summary of the Invention

[0007] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a geodetic mapping method based on a two-way round-trip zero drift rate correction of a gravimeter to solve the problems raised in the above-mentioned background technology.

[0008] To achieve the above object, the present invention provides the following technical solutions:

[0009] The geodetic mapping method based on the two-way round-trip zero drift rate correction of the gravimeter includes the following steps:

[0010] Step 1: Collect the analytical data required for mapping the route, including the symmetry of the route and the real-time environment of the route, pre-process the data and store it in the database;

[0011] Step 2: Retrieve data from the database to evaluate the path symmetry and real-time environment;

[0012] Step 3: Use TOPSIS to comprehensively analyze the symmetry of the path and the real-time environment of the path to select the appropriate mapping path;

[0013] Step 4: Set the zero drift rate threshold based on the historical zero drift rate, compare it with the real-time zero drift rate, and adjust and calculate the periodic correction time.

[0014] In a preferred embodiment, in step 2, the geometric center of each path is calculated to obtain a symmetry coefficient, and finally the symmetry of the path is obtained. The specific process of calculating the symmetry of the path is as follows:

[0015] S1: Data preparation; suppose there are n surveying and mapping paths to be selected, and there are m measurement points on each path;

[0016] Collect the coordinate data of m measurement points on the n paths and mark them as (x ij ,y ij , z ij ); where i is the path number, j is the measurement point number, and x ij The horizontal coordinate of the jth measurement point of the i-th mapping path;

[0017] S2: Calculate the geometric center of each path; for all measurement points on each path, calculate its geometric center (xc i , yc i , zc i ); Where m is the number of measurement points;

[0018] S3: Calculate the symmetric point and deviation of each measurement point; for each measurement point on each path, calculate its symmetric point (x ci ,y ci , z ci )=(2xc i -x ij , 2yc i -y ij , 2zc i -z ij ); then calculate the distance deviation between each measurement point and its symmetrical point where x cij is the coordinate of the symmetrical point of the jth measurement point on the i-th path relative to the geometric center;

[0019] S4: Calculate the total deviation and average deviation of each path; for each path, calculate the total deviation Di and average deviation of all measurement points

[0020] S5: Calculate the symmetry coefficient of each path; to calculate the symmetry of each path, Where D max is the maximum deviation value among all paths, Ei is the symmetry coefficient of the i-th mapping path; the value range of the symmetry coefficient is 0 to 1;

[0021] The symmetry coefficients of the n paths are compared, and the path with the best symmetry is selected, that is, the symmetry of the selected path is E=max(E1, E2, ..., En).

[0022] In a preferred embodiment, in step S2, the real-time environment for calculating the path is as follows:

[0023] Preprocess the data of each measurement point, including removing outliers and data cleaning;

[0024] Perform statistical analysis on the environmental data collected at each measurement point and calculate the average, maximum, minimum and standard deviation of the real-time environment;

[0025] Assume there are m measurement points, and the temperature, humidity, wind direction and other data of each measurement point are Ti, Hi, and Wsi respectively. Calculate the average temperature Where m is the number of measurement points, and the average humidity and average wind speed are calculated using the same method;

[0026] The average temperature, average humidity and average wind speed are weighted to obtain a comprehensive score of the real-time environment.

[0027] In a preferred embodiment, in step 3, the symmetry of the path and the real-time environment of the path are comprehensively analyzed to select the most suitable mapping path; the specific process of TOPSIS comprehensive analysis of the symmetry of the path and the real-time environment of the path is as follows:

[0028] P1: Determine the decision criteria; determine the decision criteria used to analyze and select the appropriate mapping path, including the symmetry of the mapping path and the real-time environment of the mapping path; the sample data is Z = (E, F); that is, the symmetry and real-time environment of each path, and the number of samples is the number of paths n;

[0029] P2: normalized data; E represents the symmetry coefficient of the mapping path, Where max(E) represents the maximum value of the symmetry coefficient E; F represents the comprehensive score of the path real-time environment, Where min(F) is the minimum value of F;

[0030] P3: Determine the ideal solution and the negative ideal solution;

[0031] P4: Calculate the similarity metric; use the Euclidean distance formula to calculate the distance ai between each path and the ideal solution +, and by calculating the distance between each path and the negative ideal solution, we get ai - ;

[0032] P5: Calculate the comprehensive score of the path; use the comprehensive score formula to calculate the comprehensive score of each path, specifically In the formula, ai + and ai - are the distances between the i-th path and the ideal solution and the negative ideal solution respectively;

[0033] P6: Interpret the results; sort the paths according to their comprehensive scores and select the path with the highest score as the mapping path.

[0034] In a preferred embodiment, in step 4, a zero drift rate threshold is set based on the historical zero drift rate, and the zero drift rate is monitored in real time. By comparing the real-time zero drift rate with the zero drift rate threshold, the time of the periodic calibration is further adjusted. The specific adjustment method is as follows:

[0035] Q1.1: Calculate the historical zero drift rate; collect historical zero drift rate data, and set the time of initial periodic calibration to t 初始 ; This is the initial value set based on the technical specifications of the gravimeter, historical data and the accuracy requirements of the surveying and mapping mission; Use the gravimeter to collect past t 初始 Zero drift rate data within 2 days, record the readings of the gravimeter at different time points and the specific time; calculate the past t based on the collected data 初始 Zero drift rate in days, assuming that the past t 初始 A total of N historical zero drift rates are collected within a day, and one data point refers to the historical zero drift rate at a moment;

[0036] Q1.2: Set the zero drift rate threshold; calculate the past t 初始 The mean μ and standard deviation σ of the zero drift rate within a day are used to obtain the central tendency and dispersion of the data; the zero drift rate threshold is then calculated as R1 = μ + k·σ; where k is the adjustment coefficient;

[0037] Q2: Real-time monitoring of zero drift rate; calculate the real-time zero drift rate during the surveying process, and calculate the real-time zero drift rate in the same way as Q1.1, and mark the real-time zero drift rate as R 实时 ;

[0038] Q3: Zero drift rate threshold comparison; if the real-time zero drift rate is greater than the zero drift rate threshold, the periodic calibration time is shortened; if the real-time zero drift rate is less than or equal to the zero drift rate threshold, the periodic calibration time is extended;

[0039] Q4: Dynamically adjust the periodic calibration time; mark the adjusted periodic calibration time as t new The formula is Where t new is the adjusted periodic calibration time, t初始 is the time for initial periodic correction, β is a parameter, and R1 is the set zero drift rate threshold.

[0040] The technical effects and advantages of the geodetic mapping method based on the two-way round-trip zero drift rate correction of the gravimeter of the present invention are as follows:

[0041] The present invention can effectively improve the accuracy and reliability of gravity measurement data by monitoring the zero drift rate of the gravimeter in real time, setting a reasonable threshold and dynamically adjusting the periodic correction time according to the zero drift rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 A logic diagram of a geodetic surveying and mapping method based on two-way round-trip zero drift rate correction of a gravimeter according to the present invention;

[0043] Figure 2 The present invention is a flow chart of the geodetic surveying and mapping method based on the two-way round-trip zero drift rate correction of the gravimeter. DETAILED DESCRIPTION

[0044] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0045] Example 1, Figure 1 A method for selecting a suitable surveying and mapping path logic diagram and dynamically adjusting the periodic correction time is given. Figure 2 A flow chart of the geodetic mapping method based on the two-way round-trip zero drift rate correction of the gravimeter is given, which specifically includes the following steps:

[0046] Step 1: Collect the analytical data required to select a suitable surveying and mapping path, including the symmetry of the path and the real-time environment of the path, ensure the accuracy and consistency of the data, pre-process the data and store it in the database.

[0047] Step 2: Retrieve data from the database to evaluate the path symmetry and real-time environment.

[0048] Step 3: Use TOPSIS to comprehensively analyze the symmetry of the path and the real-time environment of the path to select a suitable mapping path.

[0049] Step 4: Set the zero drift rate threshold based on the historical zero drift rate, compare it with the real-time zero drift rate, and adjust and calculate the periodic correction time.

[0050] Specifically, in step 1, the survey path refers to the specific measurement route planned and executed during geodetic surveying to obtain geographic, topographic, or gravity data within an area. The survey path is an important component of surveying, and its rationality and scientific nature directly impact the quality of the measured data and the efficiency of the surveying work.

[0051] The symmetry of a path refers to the degree of geometric symmetry of the surveying path relative to a reference point or reference line (such as the geometric center of the path). Symmetry can help optimize the surveying path and improve measurement accuracy and data reliability.

[0052] The real-time environment of a route refers to the immediate environmental conditions of the area through which the route passes during geodetic mapping, including temperature, humidity, wind speed, and other factors. Various sensors, such as temperature, humidity, and wind speed and direction sensors, are installed on surveying equipment or vehicles to collect real-time environmental information.

[0053] Specifically, in step 2, the geometric center of each path is calculated to further determine the symmetry coefficient and, ultimately, the path's symmetry. In surveying and geometry, the geometric center (also called the centroid) refers to the average position of a multi-point system. In geodetic surveying, the geometric center is typically the average position of all measured points along a survey path. Calculating the geometric center helps analyze the distribution of measured points and is used to assess the symmetry of a path.

[0054] The specific process of calculating the symmetry of the path is as follows:

[0055] S1: Data Preparation. Assume that there are n mapping routes to be selected, and each route has m measurement points (measurement points are locations on the mapping route that are planned or actually used. The data collected at these locations is used to determine the Earth's gravity field or other geographic information).

[0056] Use tools such as global navigation satellite systems, total stations, and laser scanners to collect the coordinate data of m measurement points on these n paths (coordinate data refers to the numerical value that describes the position of the measurement point in space, which is usually expressed in the form of three-dimensional coordinates) and mark it as (x ij ,y ij , z ij ); where i is the path number, j is the measurement point number, and x ij Represents the horizontal coordinate of the jth measurement point of the i-th surveying path.

[0057] S2: Calculate the geometric center of each path. For all measurement points on each path, calculate its geometric center (xc i , yc i , zc i ); specifically Where m is the number of measurement points.

[0058] S3: Calculate the symmetric point and deviation of each measurement point. For each measurement point on each path, calculate its symmetric point (x ci ,y ci , z ci )=(2xc i -x ij , 2yc i -y ij , 2zc i -z ij ); then calculate the distance deviation between each measurement point and its symmetrical point where x cij are the coordinates of the symmetrical point of the jth measurement point on the i-th path relative to the geometric center.

[0059] S4: Calculate the total deviation and average deviation of each path. For each path, calculate the total deviation Di and average deviation of all measurement points Specifically

[0060] S5: Calculate the symmetry coefficient of each path. Use the formula to calculate the symmetry of each path, the formula is Where D max is the maximum deviation value among all paths, and Ei is the symmetry coefficient of the i-th mapping path. The value range of the symmetry coefficient is 0 to 1.

[0061] The closer the symmetry coefficient of each path is to 1, the better the symmetry of the path; the closer the symmetry coefficient of each path is to 0, the worse the symmetry of the path.

[0062] When only considering the symmetry factor of the path, the symmetry coefficients of the n paths can be compared and the path with the best symmetry can be selected, that is, the symmetry of the selected path is E=max(E1, E2, ..., En).

[0063] The real-time environment for calculating the path is as follows:

[0064] First, temperature sensors, humidity sensors, wind speed and direction sensors, and other sensors are installed on the surveying equipment or vehicle. Each sensor records environmental data at each measurement point along the survey route. The data at each measurement point is then preprocessed, including outlier removal and data cleaning.

[0065] Perform statistical analysis on the environmental data collected at each measurement point and calculate the average, maximum, minimum and standard deviation of the real-time environment.

[0066] Assume that there are m measurement points in total, and the temperature, humidity, wind direction and other data of each measurement point are Ti, Hi, and Wsi respectively. The average temperature is calculated as Where m is the number of measurement points, and the average humidity and average wind speed are calculated using the same method.

[0067] Finally, the average temperature, average humidity and average wind speed are calculated using weighted calculation to get the real-time environment. Where F is the comprehensive score of the real-time environment, α is the weight coefficient, and α1+α2+α3=1. The specific establishment of the weight coefficient needs to be determined according to the professional knowledge in the relevant field and the specific situation, which will not be elaborated here.

[0068] Generally speaking, temperatures that are too high or too low can affect the normal operation of surveying and mapping equipment. Moderate temperatures are generally most beneficial for the surveying process. High humidity may cause condensation inside the equipment, affecting surveying accuracy and equipment life. High wind speeds may cause instability in the surveying equipment or vehicle, thereby affecting data accuracy. A lower comprehensive score (F) indicates a more suitable environment and higher accuracy and reliability of the surveying and mapping data. Therefore, among n surveying and mapping paths, the path with the lowest comprehensive score (F) is selected.

[0069] Specifically, in step 3, a comprehensive analysis of the path symmetry and the path's real-time environment is required to select the most appropriate mapping path. TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is a multi-criteria decision analysis method used to evaluate the pros and cons of candidate solutions relative to a set of specific attributes. This embodiment uses TOPSIS to conduct a comprehensive analysis of the path's symmetry and the path's real-time environment. The specific process is as follows:

[0070] P1: Determine the decision criteria. The decision criteria for analyzing and selecting appropriate mapping paths include the symmetry of the mapping paths and the real-time environment of the mapping paths. The sample data is Z = (E, F); this refers to the symmetry and real-time environment of each path. The number of samples is the number of paths, n.

[0071] P2: Normalized data. E represents the symmetry coefficient of the mapping path. The larger the symmetry coefficient, the better the symmetry. Therefore, the following formula can be used for normalization processing, specifically: Where max(E) represents the maximum value of the symmetry coefficient E. F represents the comprehensive score of the path real-time environment. The smaller F is, the better the path real-time environment is. Therefore, the formula can be used for normalization processing, specifically: Where min(F) is the minimum value of F.

[0072] P3: Determine the ideal solution and the negative ideal solution. The ideal solution is the solution that obtains the best value on each decision criterion, and the negative ideal solution is the solution that obtains the worst value on each decision criterion. Generally speaking, the larger the symmetry coefficient, the better the symmetry of the path, and the greater the possibility of selecting the surveying path. The two-way round-trip zero drift correction method relies on repeated measurements on the same path. The better the symmetry of the path, the closer the measurement points on the round-trip path and the real-time environment, and the higher the accuracy of the correction calculation. The smaller the comprehensive score of the real-time environment of the path, the better the real-time environment of the path, and the greater the possibility of selecting the surveying path. This is because when measurements are taken under good environmental conditions, the quality of the surveying data is higher, and the difficulty of data correction will also be reduced. Therefore, the ideal solution is the maximum value of the path symmetry and the minimum value of the path real-time environment, that is, A + =[E max ,F min ]; Similarly, the negative ideal solution is the minimum value of the path symmetry and the maximum value of the path real-time environment, that is, A - =[E min ,F max ].

[0073] P4: Calculate the similarity metric. Use the Euclidean distance formula to calculate the distance between each path and the ideal solution. In the formula, ai + is the distance between the i-th path and the ideal solution, Z ij is the actual value of the i-th path on the j-th decision criterion, A + The ideal solution is [E max ,F min ], γ is the number of decision criteria is 2, namely the symmetry of the path and the real-time environment of the path. Similarly, by calculating the distance between each path and the negative ideal solution, we can get ai - .

[0074] P5: Calculate the comprehensive score of the path. Use the comprehensive score formula to calculate the comprehensive score of each path, specifically: In the formula, ai + and ai - are the distances between the i-th path and the ideal solution and the negative ideal solution, respectively.

[0075] P6: Interpret the results. Paths are sorted based on their comprehensive scores, with higher-scoring paths ranked higher. The path with the highest score is selected as the mapping path. If alternative mapping paths are needed in actual geodetic surveying, the paths can be selected based on the ranking of the paths from highest to lowest comprehensive scores. The specific selection process depends on the actual situation and is not described here.

[0076] Specifically, in step 4, the zero drift rate threshold is set based on the historical zero drift rate. The zero drift rate is then monitored in real time. By comparing the real-time zero drift rate with the zero drift rate threshold, the periodic calibration time is further adjusted. Periodic calibration time refers to the predetermined intervals between instrument calibration and correction during geodetic surveying based on round-trip zero drift rate correction of gravimeters to ensure high accuracy and reliability.

[0077] The specific adjustment methods are as follows:

[0078] Q1.1: Calculate the historical zero drift rate. Collect historical zero drift rate data (zero drift rate change data of the gravimeter in historical surveying and mapping missions). This data should include zero drift rates in different time periods and under different environmental conditions. Zero drift refers to the change in the output reading of the gravimeter over time when there is no external gravity change. Zero drift rate refers to the rate of change of the zero drift of the gravimeter output reading over time, which is usually used to measure the degree of baseline drift of the gravimeter. Assume that the time of the initial periodic calibration is t 初始 ; This is the initial value set based on the gravimeter's technical specifications, historical data, and the accuracy requirements of the surveying and mapping mission. 初始 Zero drift rate data for the past t days, record the readings of the gravimeter at different time points and the specific time. Based on the collected data, calculate the past t 初始 The zero drift rate within a day is as follows: Where D(t) is the gravimeter reading at time t, D(t+Δt) is the reading at time t+Δt, Δt is the time interval, and R is the historical zero drift rate. 初始 A total of N historical zero drift rates are collected within a day, and one data point refers to the historical zero drift rate at a moment.

[0079] Q1.2: Set the zero drift rate threshold. Calculate the past t 初始 The mean μ and standard deviation σ of the zero drift rate within a day are used to obtain the central tendency and dispersion of the data. Where N is the number of historical zero drift rate data, i.e., the number of past t 初始 The total number of zero-drift rate data points within a day, Ri, is the zero-drift rate of the i-th data point. The zero-drift rate threshold is then calculated as R1 = μ + k·σ; where k is the adjustment coefficient, typically between 1 and 3.

[0080] Q2: Real-time monitoring of zero drift rate. In the process of surveying and mapping, the same method is used to calculate the real-time zero drift rate. The real-time zero drift rate can be obtained by calculation in the same way as Q1.1. The real-time zero drift rate is marked as R 实时 ; It should be noted that the real-time zero drift rate is calculated here, so the collected data needs to be real-time, which will not be described in detail here.

[0081] Q3: Zero drift rate threshold comparison. If the real-time zero drift rate is greater than the zero drift rate threshold, shorten the periodic calibration time and start the next calibration as soon as possible. If the real-time zero drift rate is less than or equal to the zero drift rate threshold, extend the periodic calibration time appropriately.

[0082] Q4: Dynamically adjust the periodic calibration time. Mark the adjusted periodic calibration time as t new ; There is a calculation formula Where t new is the adjusted periodic calibration time, t 初始 is the time for the initial periodic correction, β is a parameter, usually between 0 and 1, and R1 is the set zero drift rate threshold.

[0083] By real-time monitoring of the zero drift rate of the gravimeter, setting a reasonable threshold and dynamically adjusting the periodic correction time according to the zero drift rate, the accuracy and reliability of gravity measurement data can be effectively improved.

[0084] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0085] The above embodiments may be implemented in whole or in part through software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0086] Those skilled in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application of the technical solution and the invention constraints. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0087] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0088] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0089] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A geodetic mapping method based on a two-way round-trip zero drift rate correction of a gravimeter, characterized in that: The following steps are involved: Step 1: Collect the analytical data required for mapping the path, including the symmetry of the path and the real-time environment of the path, and pre-process the collected analytical data and store them in the database; Step 2: Retrieve data from the database to evaluate the path symmetry and real-time environment; Step 3: Use TOPSIS to comprehensively analyze the symmetry of the path and the real-time environment of the path to select the appropriate mapping path; Step 4: Set the zero drift rate threshold based on the historical zero drift rate, compare it with the real-time zero drift rate, and adjust and calculate the regular correction time; In step 4, a zero drift rate threshold is set based on the historical zero drift rate, and the zero drift rate is monitored in real time. By comparing the real-time zero drift rate with the zero drift rate threshold, the time for periodic calibration is further adjusted. The specific adjustment method is as follows: Q1.1: Calculate the historical zero drift rate; collect historical zero drift rate data, and set the time of initial periodic calibration to t 初始 ; This is the initial value set based on the gravimeter's technical specifications, historical data, and the accuracy requirements of the surveying and mapping mission; Use the gravimeter to collect past 初始 Zero drift rate data within 2 days, record the readings of the gravimeter at different time points and the specific time; calculate the past t based on the collected data 初始 Zero drift rate in days, assuming that the past t 初始 A total of N historical zero drift rates are collected within a day, and one data point refers to the historical zero drift rate at a moment; Q1.2: Set the zero drift rate threshold; calculate the past t 初始 The mean μ and standard deviation σ of the zero drift rate within a day are used to obtain the central tendency and dispersion of the data; the zero drift rate threshold is then calculated as R1 = μ + k·σ; where k is the adjustment coefficient; Q2: Real-time monitoring of zero drift rate; calculate the real-time zero drift rate during the surveying process, and calculate the real-time zero drift rate in the same way as Q1.1, and mark the real-time zero drift rate as R 实时 ; Q3: Zero drift rate threshold comparison; If the real-time zero drift rate is greater than the zero drift rate threshold, the periodic calibration time is shortened; if the real-time zero drift rate is less than or equal to the zero drift rate threshold, the periodic calibration time is extended; Q4: Dynamically adjust the periodic calibration time; mark the adjusted periodic calibration time as t new The formula is Where t new is the adjusted periodic calibration time, t 初始 is the time for initial periodic correction, β is a parameter, and R1 is the set zero drift rate threshold.

2. The geodetic mapping method based on gravimeter two-way round-trip zero drift rate correction according to claim 1, characterized in that: In step 2, the symmetry coefficient is obtained by calculating the geometric center of each path, and finally the symmetry of the path is obtained. The specific process of calculating the symmetry of the path is as follows: S1: Data preparation; suppose there are n surveying and mapping paths to be selected, and there are m measurement points on each path; Collect the coordinate data of m measurement points on the n paths and mark them as (x ij ,y ij , z ij ); Where i is the path number, j is the measurement point number, and x ij The horizontal coordinate of the jth measurement point of the i-th mapping path; S2: Calculate the geometric center of each path; for all measurement points on each path, calculate its geometric center (xc i , yc i , zc i ); Where m is the number of measurement points; S3: Calculate the symmetric point and deviation of each measurement point; for each measurement point on each path, calculate its symmetric point (x ci ,y ci , z ci )=(2xc i -x ij , 2yc i -y ij , 2zc i -z ij ); then calculate the distance deviation between each measurement point and its symmetrical point where x cij is the coordinate of the symmetrical point of the jth measurement point on the i-th path relative to the geometric center; S4: Calculate the total deviation and average deviation of each path; For each path, calculate the total deviation Di and the average deviation of all measurement points S5: Calculate the symmetry coefficient of each path; to calculate the symmetry of each path, Where D max is the maximum deviation value among all paths, Ei is the symmetry coefficient of the i-th mapping path; the value range of the symmetry coefficient is 0 to 1; The symmetry coefficients of the n paths are compared, and the path with the best symmetry is selected, that is, the symmetry of the selected path is E=max(E1, E2, ..., En).

3. The geodetic mapping method based on gravimeter two-way round-trip zero drift rate correction according to claim 2, characterized in that: In step S2, the real-time environment for calculating the path is as follows: Preprocess the data of each measurement point, including removing outliers and data cleaning; Perform statistical analysis on the environmental data collected at each measurement point and calculate the average, maximum, minimum and standard deviation of the real-time environment; Assume there are m measurement points, and the temperature, humidity, wind direction and other data of each measurement point are Ti, Hi, and Wsi respectively. Calculate the average temperature Where m is the number of measurement points, and the average humidity and average wind speed are calculated using the same method; The average temperature, average humidity and average wind speed are weighted to obtain a comprehensive score of the real-time environment.

4. The geodetic mapping method based on the two-way round-trip zero drift rate correction of the gravimeter according to claim 1, characterized in that ； In step 3, the symmetry of the path and the real-time environment of the path are comprehensively analyzed to select the most appropriate mapping path. The specific process of TOPSIS comprehensive analysis of the symmetry of the path and the real-time environment of the path is as follows: P1: Determine the decision criteria; determine the decision criteria used to analyze and select the appropriate mapping path, including the symmetry of the mapping path and the real-time environment of the mapping path; the sample data is Z = (E, F); that is, the symmetry and real-time environment of each path, and the number of samples is the number of paths n; P2: normalized data; E represents the symmetry coefficient of the mapping path, Where max(E) represents the maximum value of the symmetry coefficient E; F represents the comprehensive score of the path real-time environment, Where min(F) is the minimum value of F; P3: Determine the ideal solution and the negative ideal solution; P4: Calculate the similarity metric; use the Euclidean distance formula to calculate the distance ai between each path and the ideal solution + , and by calculating the distance between each path and the negative ideal solution, we get ai - ; P5: Calculate the comprehensive score of the path; use the comprehensive score formula to calculate the comprehensive score of each path, specifically In the formula, ai + and ai - are the distances between the i-th path and the ideal solution and the negative ideal solution respectively; P6: Interpret the results; sort the paths according to their comprehensive scores and select the path with the highest score as the mapping path.

Images