Method and system for survey result correction for engineering surveying device

Abstract

The application provides a measurement result correction method and system for an engineering surveying device, relates to the technical field of data processing, acquires N first distance measurement results and GPS satellite positioning information, constructs a meteorological simulation channel to analyze N communication time difference calibration values, performs error fitting to acquire N second distance measurement results and determine first positioning information, screens adjacent base stations to perform satellite positioning and deviation analysis, and performs error fitting on the first positioning information. The application solves the technical problem of low stability and accuracy in the prior art of engineering surveying error correction, which only performs positioning fitting of a mobile station through positioning information of a known position base station without considering environmental deviation of an actual scene, causes transmission time delay due to meteorological parameters, performs one-time measurement calibration, performs secondary calibration based on positioning deviation of a known adjacent base station to avoid complexity of a meteorological environment and stability and accuracy deviation existing in a measurement process, and improves accuracy of measurement results.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and more specifically to a method and system for correcting measurement results for engineering surveying devices. Background Technology

[0002] GPS surveying technology has been widely used in surveying engineering, meeting the needs of engineering surveying in complex environments and improving the stability and adaptability of surveying projects. Currently, traditional GPS engineering surveying error correction only uses the positioning information of known base stations to fit the measurement and positioning of the mobile station, without considering environmental deviations in the actual scene, resulting in low stability and accuracy. Summary of the Invention

[0003] This application provides a method and system for correcting measurement results of engineering surveying devices, which addresses the technical problem of low stability and accuracy in traditional GPS engineering surveying error correction, which only uses the positioning information of known base stations to fit the positioning of the mobile station without considering environmental deviations in the actual scene.

[0004] In view of the above problems, this application provides a method and system for correcting measurement results for engineering surveying devices.

[0005] In a first aspect, this application provides a method for correcting measurement results for engineering surveying equipment, the method comprising:

[0006] Establish communication status between the mobile station and N GPS satellites, and obtain N first distance measurement results and N GPS satellite positioning information;

[0007] Load meteorological monitoring information from N communication paths, construct N meteorological simulation channels to perform communication time difference analysis, and obtain N communication time difference calibration values;

[0008] Based on the N communication time difference calibration values, the N first distance measurement results are fitted with errors to obtain N second distance measurement results;

[0009] Based on the N second distance measurement results and the N GPS satellite positioning information, position optimization is performed to determine the first positioning information;

[0010] Filter the neighboring correction base stations of the mobile station, and obtain the second positioning information of the neighboring correction base stations based on the N GPS satellites;

[0011] Calculate the deviation between the second positioning information and the reference positioning information of the neighboring correction base station, perform error fitting on the first positioning information, and obtain the third positioning information;

[0012] The third positioning information is added to the engineering survey results of the mobile station monitoring point.

[0013] Secondly, this application provides a measurement result correction system for engineering surveying equipment, the system comprising:

[0014] The information acquisition module is used to establish the communication status between the mobile station and N GPS satellites, and to acquire N first distance measurement results and N GPS satellite positioning information.

[0015] The time difference analysis module is used to load meteorological monitoring information of N communication paths, construct N meteorological simulation channels to perform communication time difference analysis, and obtain N communication time difference calibration values.

[0016] An error fitting module is used to perform error fitting on the N first distance measurement results based on the N communication time difference calibration values ​​to obtain N second distance measurement results;

[0017] The first positioning information acquisition module is used to perform positioning optimization based on the N second distance measurement results and the N GPS satellite positioning information to determine the first positioning information;

[0018] The second positioning information acquisition module is used to filter the neighboring correction base stations of the mobile station and acquire the second positioning information of the neighboring correction base stations based on the N GPS satellites.

[0019] The third positioning information acquisition module is used to calculate the deviation between the second positioning information and the reference positioning information of the neighboring correction base station, perform error fitting on the first positioning information, and obtain the third positioning information.

[0020] An information adding module is used to add the third positioning information into the engineering survey results of the mobile station monitoring point.

[0021] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0022] The measurement result correction method for engineering surveying devices provided in this application embodiment establishes the communication status between a mobile station and N GPS satellites, obtains N first distance measurement results and N GPS satellite positioning information; loads N communication path meteorological monitoring information and constructs N meteorological simulation channels to perform communication time difference analysis, obtains N communication time difference calibration values, performs error fitting on the N first distance measurement results to obtain N second distance measurement results, performs positioning optimization in combination with the N GPS satellite positioning information to determine first positioning information; filters the neighboring correction base stations of the mobile station, obtains second positioning information based on the N GPS satellites, performs error fitting on the first positioning information in combination with the deviation of the benchmark positioning information of the neighboring correction base stations, obtains third positioning information, and adds it to the engineering surveying results of the mobile station monitoring points. This invention addresses the problem of low stability and accuracy in traditional GPS engineering surveying error correction technologies, which rely solely on the positioning information of known base stations to fit the measurement and positioning of the mobile station without considering environmental deviations in the actual scenario. The invention performs a first-stage measurement calibration to address transmission delays caused by meteorological parameters, and a second-stage calibration based on GPS positioning deviations from neighboring base stations. This combination of methods mitigates the complexity of meteorological environments and stability and accuracy deviations during the measurement process, thereby improving the accuracy of the measurement results. Attached Figure Description

[0023] Figure 1 This application provides a schematic flowchart of a measurement result correction method for engineering surveying equipment;

[0024] Figure 2 This application provides a schematic diagram of the first positioning information acquisition process in the measurement result correction method for engineering surveying equipment;

[0025] Figure 3 This application provides a schematic diagram of the second positioning information acquisition process in the measurement result correction method for engineering surveying equipment;

[0026] Figure 4 This application provides a schematic diagram of the structure of a measurement result correction system for an engineering surveying device.

[0027] Explanation of reference numerals in the attached diagram: Information acquisition module 11, Time difference analysis module 12, Error fitting module 13, First positioning information acquisition module 14, Second positioning information acquisition module 15, Third positioning information acquisition module 16, Information addition module 17. Detailed Implementation

[0028] This application provides a method and system for correcting measurement results for engineering surveying devices. It establishes the communication status between a mobile station and N GPS satellites, acquires N first distance measurement results and N GPS satellite positioning information, constructs N meteorological simulation channels to analyze and acquire N communication time difference calibration values, performs error fitting to acquire N second distance measurement results and determine first positioning information, filters nearby correction base stations and acquires second positioning information, calculates the deviation by combining it with benchmark positioning information, and performs error fitting on the first positioning information. This addresses the technical problem in existing GPS engineering surveying error correction methods, which only use the positioning information of known base stations to fit the measurement positioning of the mobile station, without considering environmental deviations in the actual scenario, resulting in low stability and accuracy.

[0029] Example 1

[0030] like Figure 1 As shown, this application provides a measurement result correction method for an engineering surveying device, applied to a measurement result correction system for an engineering surveying device. The system is communicatively connected to a correction base station and a mobile station, and includes:

[0031] Step S100: Establish communication status between the mobile station and N GPS satellites, and obtain N first distance measurement results and N GPS satellite positioning information;

[0032] Specifically, GPS surveying technology has been widely applied in surveying engineering, enabling the completion of engineering surveying needs in complex environments and improving the stability and adaptability of surveying projects. The measurement result correction method for engineering surveying equipment provided in this application performs a primary measurement calibration to address transmission delays caused by meteorological parameters; and a secondary calibration based on GPS positioning deviations from nearby base stations. The combination of these two methods mitigates the complexity of the meteorological environment and stability and accuracy deviations inherent in the measurement process, thereby improving the accuracy of the measurement results.

[0033] Specifically, the communication status between the mobile station and N GPS satellites is established, i.e., a relative communication connection is established between the mobile station and each GPS satellite. Based on the mobile station receiving the transmitted signals from the GPS satellites, the mobile station, as the target to be received and its position determined, does not need to transmit signals; instead, it uses passive positioning to determine the unknown target, i.e., the mobile station's positioning. The signals transmitted by the N GPS satellites are received, i.e., the positioning information of the N GPS satellites. The product of the transmission time of each GPS satellite and the speed of light in the N GPS signals is calculated as the first distance measurement result. The N first distance measurement results are integrated and acquired. This is then used as the positioning information of the N GPS satellites.

[0034] Step S200: Load meteorological monitoring information for N communication paths, construct N meteorological simulation channels to perform communication time difference analysis, and obtain N communication time difference calibration values;

[0035] Furthermore, by loading meteorological monitoring information from N communication paths, constructing N meteorological simulation channels for communication time difference analysis, and obtaining N communication time difference calibration values, step S200 of this application also includes:

[0036] Step S210: Based on the tropospheric meteorological monitoring attributes, obtain meteorological monitoring information for N first communication paths, wherein the tropospheric meteorological monitoring attributes include one or more of temperature, air pressure, humidity, wind speed, and wind direction;

[0037] Step S220: Based on the ionospheric meteorological monitoring attributes, obtain meteorological monitoring information for N second communication paths, wherein the ionospheric meteorological monitoring attributes include one or more of electron density, electron temperature, collision frequency, ion density, ion temperature, and ion composition;

[0038] Step S230: Based on the upper-air meteorological monitoring attributes, obtain meteorological monitoring information from N third communication paths, wherein the upper-air meteorological monitoring attributes include one or more of particulate matter concentration, particulate matter size, temperature, and humidity;

[0039] Step S240: Add the N first communication path meteorological monitoring information, the N second communication path meteorological monitoring information, and the N third communication path meteorological monitoring information into the N communication path meteorological monitoring information;

[0040] Step S250: Construct N meteorological simulation channels based on the meteorological monitoring information of the N communication paths, perform communication time difference analysis, and obtain N communication time difference calibration values.

[0041] Furthermore, based on the meteorological monitoring information of the N communication paths, N meteorological simulation channels are constructed for communication time difference analysis to obtain N communication time difference calibration values. Step S250 of this application also includes:

[0042] Step S251: Construct the N meteorological simulation channels based on the meteorological monitoring information of the N communication paths;

[0043] Step S252: Perform communication simulation based on the N meteorological simulation channels to obtain N signal transmission refraction path diagrams;

[0044] Step S253: Connect the starting point and ending point of the N signal transmission refraction path diagrams to construct N communication path baselines;

[0045] Step S254: Perform communication time difference analysis based on the N communication path baselines and the N signal transmission refraction path diagrams to obtain N communication time difference calibration values.

[0046] Furthermore, based on the N communication path baselines and the N signal transmission refraction path diagrams, communication time difference analysis is performed to obtain N communication time difference calibration values. Step S254 of this application also includes:

[0047] Step S2541: Extract N vacuum signal segments from the N communication path baselines and set them as N reference baselines;

[0048] Step S2542: Based on the N GPS satellites, obtain the N reference propagation times of the N reference baselines, and determine the N theoretical propagation times, including,

[0049] Step S25421: Construct a formula for evaluating the theoretical propagation duration:

[0050] ;

[0051] in, Characterized by the theoretical propagation time from the nth GPS satellite to the mobile station. Characterizing the in-plot length of the nth reference baseline, The in-map length of the baseline of the nth communication path is represented. The reference propagation duration characterizing the nth reference baseline, n∈N, The system error coefficients characterizing the nth satellite;

[0052] Step S2543: Based on the theoretical propagation duration evaluation formula, determine the N theoretical propagation durations based on the N reference propagation durations;

[0053] Step S2544: Obtain the N actual propagation times of the N signal transmission refraction path diagrams, and obtain the N communication time difference calibration values ​​based on the N theoretical propagation times.

[0054] Specifically, signal transmission in different atmospheric layers is affected by the corresponding atmospheric characteristics, resulting in transmission direction deviations (including but not limited to reflections), leading to transmission delays. Therefore, the calculated first distance measurement result includes the time delay distance due to path changes. The N communication paths are the signal transmission paths of each GPS satellite. Meteorological monitoring information from these N communication paths, i.e., the attribute characteristics of different atmospheric layers, is loaded. Based on this, a corresponding meteorological simulation channel is constructed for communication time difference analysis to calibrate the corresponding first distance measurement result.

[0055] Specifically, different atmospheric layers have different influencing factors on signal transmission, requiring targeted monitoring and distance adjustments to maximize distance accuracy. Meteorological attributes of the troposphere are acquired to determine the characteristics affecting signal transmission, including one or more of temperature, air pressure, humidity, wind speed, and wind direction, which serve as meteorological monitoring information for the N first communication paths. For example, remote monitoring can be performed using remote sensing technology. Similarly, for the ionosphere, one or more of electron density, electron temperature, collision frequency, ion density, ion temperature, and ion composition are used as meteorological monitoring attributes. These attributes are monitored for each of the N first communication paths to obtain meteorological monitoring information for the N second communication paths. Similarly, one or more of particulate matter concentration, particulate matter size, temperature, and humidity are used as upper-air meteorological monitoring attributes. These attributes are monitored for each of the N first communication paths to obtain meteorological monitoring information for the N third communication paths.

[0056] Furthermore, the meteorological monitoring information of the N first communication paths, the N second communication paths, and the N third communication paths are mapped to correspondences. Based on atmospheric distribution, the meteorological monitoring information of the first, second, and third communication paths of each GPS satellite is spliced ​​and integrated to determine the meteorological monitoring information of the N communication paths corresponding to the N GPS satellites. Using the meteorological monitoring information of the N communication paths as the source data, the N meteorological simulation channels are constructed.

[0057] Specifically, based on the meteorological monitoring information of the N communication paths, N meteorological simulation channels are constructed. For example, a visualization simulation platform is connected, and the meteorological monitoring information of the N communication paths is used as simulation construction data to simulate and reconstruct the meteorological layer, generating meteorological simulation channels consistent with the actual signal transmission of the N GPS satellites. Further, within the N meteorological simulation channels, signal transmission simulation experiments are conducted, and the signal transmission paths are tracked to generate the N signal transmission refraction path maps, i.e., reconstructing the signal transmission path in the atmosphere. Further, the starting and ending points of the N signal transmission refraction path maps are connected, and the approximate straight-line path determined based on the relative distance between the starting and ending points is used as the baseline of the N communication paths.

[0058] Furthermore, since signal transmission within the vacuum signal segment does not exhibit directional changes, the simulated propagation time in the vacuum region is used as the reference baseline. The transmission paths of the signal within the vacuum signal segment at the relative distance between the starting and ending points, i.e., the N communication path baselines, are set as the N reference baselines. Further, based on the N reference baselines, the reference propagation time corresponding to the N GPS satellites is calculated. For example, using the speed of light as the transmission speed within the vacuum signal segment, the N reference baselines are divided by the speed of light to determine the N theoretical propagation times.

[0059] Furthermore, the theoretical propagation duration evaluation formula is constructed to calculate the theoretical propagation duration, and the expression is: ,in, Characterized by the theoretical propagation time from the nth GPS satellite to the mobile station. Characterizing the in-plot length of the nth reference baseline, The in-map length of the baseline of the nth communication path is represented. The reference propagation duration characterizing the nth reference baseline, n∈N, The system error coefficient characterizes the nth satellite. The above parameters can be obtained based on the processing in the early stage of the embodiments of this application. The system error coefficient is a quantitative parameter based on each GPS satellite and can be directly called.

[0060] Furthermore, by combining the theoretical propagation duration evaluation formula, the relevant parameters are substituted to calculate and obtain the N theoretical propagation durations. Then, the N actual propagation durations of the N signal transmission refraction path diagrams are obtained, mapped to the N theoretical propagation durations, and the differences are calculated. The propagation duration differences are used as the N communication time difference calibration values, that is, the signal transmission delay interval caused by meteorological characteristics.

[0061] Step S300: Perform error fitting on the N first distance measurement results based on the N communication time difference calibration values ​​to obtain N second distance measurement results;

[0062] Specifically, the N first distance measurement results include distances corresponding to communication time differences. A mapping is established between the N communication time difference calibration values ​​and the N first distance measurement results to determine multiple corresponding groups. Error fitting is performed on the corresponding first distance measurement results based on the communication time difference calibration values. For example, the communication time difference calibration value is multiplied by the speed of light, and the calculation result is used as the delay distance. The difference between the first distance measurement result and the delay distance is calculated and used as the second distance measurement result. Delay distance and difference calculations are performed for each of the N GPS satellites to obtain the N second distance measurement results. By analyzing and fitting the distance measurements, distance measurement errors caused by meteorological influences are eliminated, improving positioning accuracy.

[0063] Step S400: Based on the N second distance measurement results and the N GPS satellite positioning information, perform positioning optimization to determine the first positioning information;

[0064] Furthermore, such as Figure 2 As shown, based on the N second distance measurement results and the N GPS satellite positioning information, positioning optimization is performed to determine the first positioning information. Step S400 of this application further includes:

[0065] Step S410: Divide the N second distance measurement results into groups of four to obtain M division results;

[0066] Step S420: Traverse the M partitioning results to perform localization analysis and obtain M localization analysis results;

[0067] Step S430: Perform discrete value cleaning on the M positioning analysis results to obtain Q positioning analysis results;

[0068] Step S440: When the Q positioning analysis results have an intersection, the intersection positioning result is taken as the first positioning information;

[0069] Step S450: When the Q positioning analysis results do not have any intersection, take any one of the Q positioning analysis results as the first positioning information.

[0070] Specifically, positioning accuracy is determined by optimizing the positioning based on the N second distance measurement results and the N GPS satellite positioning information. For any given target, it must be within the coverage area of ​​at least four satellites to be located. Based on this, the N second distance measurement results are divided into groups of four, yielding M division results. Currently, the GPS satellite system has 24 operational satellites, essentially covering the entire globe; therefore, M is 6.

[0071] Furthermore, the positioning analysis is performed by traversing the M division results. For example, using four satellite positioning information, signal communication direction, and communication distance as input data, and the positioning results as output data, sample data is collected to train and generate a neural network model for fitting the second distance measurement results. The M division results are then further traversed, and each is input into the neural network model for analysis and processing. The corresponding positioning analysis results are output and integrated to obtain the M positioning analysis results.

[0072] Typically, further discrete value cleaning is performed on the M location analysis results to eliminate outlier data. Generally, the obtained location analysis results are quite similar. For example, mean clustering is performed on the M location analysis results. Multiple clustering results are iterated and re-clustered until convergence is reached. A threshold for the number of elements within each cluster is set, i.e., a custom-defined critical number of elements within each cluster used to measure discreteness. Clustering results that meet the threshold are extracted and identified as the Q location analysis results. Further, it is determined whether the Q location analyses have an intersection. If they do, the intersection location result is used as the first location information, i.e., the result with the highest accuracy among the Q location analysis results; if not, any one of the Q location analysis results is randomly selected as the first location information. GPS connection measurement and result analysis are performed to maximize positioning accuracy.

[0073] Step S500: Filter the neighboring correction base stations of the mobile station, and obtain the second positioning information of the neighboring correction base stations based on the N GPS satellites;

[0074] Furthermore, such as Figure 3 As shown, the process involves filtering the neighboring correction base stations of the mobile station and obtaining the second positioning information of the neighboring correction base stations based on the N GPS satellites. Step S500 of this application further includes:

[0075] Step S510: Delineate the neighborhood identification range with the mobile station as the center;

[0076] Step S520: Filter the corrected base station status information that meets the neighborhood identifier range, wherein the corrected base station status information includes base station environment monitoring results;

[0077] Step S530: Evaluate the open space coefficient based on the base station environment monitoring results and obtain the open space coefficient evaluation results;

[0078] Step S540: Select the correction base station with the minimum value of the openness coefficient evaluation result and set it as the neighboring correction base station. Based on the N GPS satellites, obtain the second positioning information of the neighboring correction base station.

[0079] Furthermore, based on the base station environment monitoring results, an openness coefficient is evaluated to obtain an openness coefficient assessment result. Step S530 of this application also includes:

[0080] Step S531: Construct the evaluation formula for the openness coefficient:

[0081] ;

[0082] in, The openness coefficient characterizes any base station. This represents the distance between the i-th building or mountain that exceeds the height threshold and the base station. This represents the total number of buildings or mountains exceeding a height threshold. This represents the height of the i-th building or mountain that is above the height threshold. A custom height threshold that can affect signal propagation. and Characterized by the normalization adjustment coefficient, Characterizing the first preset weight, Characterizing the second preset weight, Characterizing the third preset weight, Characterizes the level of electromagnetic interference near a preset base station. ;

[0083] Step S532: Based on the open space coefficient evaluation formula and the base station environment monitoring results, evaluate the open space coefficient and obtain the open space coefficient evaluation result.

[0084] Specifically, using the mobile station as the reference location, nearby correction base stations with consistent meteorological data are selected. These nearby correction base stations are base stations whose geographical locations, such as latitude and longitude, have been determined before, and are used to verify the first positioning information.

[0085] Specifically, using the mobile station as the center and meteorological data consistency as the regional delineation standard, the neighborhood identification range is defined. Correction base stations within the neighborhood identification range are identified, and the results of rapid environmental monitoring are used as the status information of the correction base stations. To reduce errors caused by the ground environment, base stations within the neighborhood identification range are screened, prioritizing adjacent base stations in relatively open areas. The base station environmental monitoring results are used as the source data for the screening judgment, and an openness coefficient is evaluated using the openness coefficient evaluation formula.

[0086] Specifically, obtain the formula for evaluating the openness coefficient: ,in, The openness coefficient characterizes any base station. This represents the distance between the i-th building or mountain that exceeds the height threshold and the base station. This represents the total number of buildings or mountains exceeding a height threshold. This represents the height of the i-th building or mountain that is above the height threshold. A custom height threshold that can affect signal propagation. and Characterized by the normalization adjustment coefficient, Characterizing the first preset weight, Characterizing the second preset weight, Characterizing the third preset weight, Characterizes the level of electromagnetic interference near a preset base station. The height threshold is a custom-defined measurement standard based on regional differences, and the configuration weight is set based on the degree of influence. These parameters can be determined directly through measurement or by calling regional data. Furthermore, based on the open space coefficient evaluation formula, the open space coefficient is calculated by iterating through the base station environmental monitoring results to obtain the open space coefficient evaluation result.

[0087] The smaller the openness coefficient evaluation result, the less the positioning result between the calibration base station and the mobile station is affected by the differences in the ground environment. The openness coefficient evaluation results are sorted in a forward sequence, and the calibration base station corresponding to the smallest openness coefficient is selected as the nearest calibration base station. Similarly, based on the N GPS satellites, the nearest calibration base station is positioned using the same method as the mobile station positioning method described in this embodiment, obtaining the second positioning information of the nearest calibration base station.

[0088] Step S600: Calculate the deviation between the second positioning information and the reference positioning information of the neighboring correction base station, perform error fitting on the first positioning information, and obtain the third positioning information;

[0089] Step S700: Add the third positioning information to the engineering survey results of the mobile station monitoring point.

[0090] Specifically, the reference positioning information of the nearby calibration base station is retrieved, which is positioning information that meets both accuracy and authority. The difference between the second positioning information and the reference positioning information is calculated, and the determined positioning information deviation is the positioning deviation existing in positioning based on GPS satellite joint measurement, including the latitude and longitude deviation direction and deviation distance. Based on the positioning information deviation as the adjustment standard, the first positioning information is error-corrected to obtain the third positioning information. The third positioning information is then added to the engineering survey results of the mobile station monitoring power.

[0091] The measurement result correction method for engineering surveying equipment provided in this application has the following technical advantages:

[0092] 1. To address the impact of meteorological environment on satellite signal transmission, a meteorological simulation channel is constructed for simulation analysis to eliminate communication time difference caused by path refraction; by conducting GPS joint measurement and result processing and screening, deviations in distance measurement results are avoided, and the impact of meteorological transmission on the first positioning result is avoided.

[0093] 2. Screening of nearby correction base stations and satellite positioning are performed. Based on the positioning results and the reference positioning information of nearby correction base stations, deviation measurement is performed to determine the deviation in the satellite positioning process. The first positioning result is then calibrated to maximize the accuracy of the positioning result.

[0094] Example 2

[0095] Based on the same inventive concept as the measurement result correction method for engineering surveying devices in the foregoing embodiments, such as Figure 4 As shown, this application provides a measurement result correction system for engineering surveying equipment, the system comprising:

[0096] Information acquisition module 11, the information acquisition module 11 is used to establish the communication status between the mobile station and N GPS satellites, and acquire N first distance measurement results and N GPS satellite positioning information;

[0097] Time difference analysis module 12 is used to load meteorological monitoring information of N communication paths, construct N meteorological simulation channels to perform communication time difference analysis, and obtain N communication time difference calibration values;

[0098] Error fitting module 13 is used to perform error fitting on the N first distance measurement results based on the N communication time difference calibration values ​​to obtain N second distance measurement results;

[0099] The first positioning information acquisition module 14 is used to perform positioning optimization based on the N second distance measurement results and the N GPS satellite positioning information to determine the first positioning information;

[0100] The second positioning information acquisition module 15 is used to filter the neighboring correction base stations of the mobile station and acquire the second positioning information of the neighboring correction base stations based on the N GPS satellites.

[0101] The third positioning information acquisition module 16 is used to calculate the deviation between the second positioning information and the reference positioning information of the neighboring correction base station, perform error fitting on the first positioning information, and obtain the third positioning information.

[0102] Information adding module 17, which is used to add the third positioning information into the engineering surveying results of the mobile station monitoring point.

[0103] Furthermore, the time difference analysis module 12 also includes:

[0104] The first communication path meteorological monitoring information acquisition module is used to acquire N first communication path meteorological monitoring information based on tropospheric meteorological monitoring attributes, wherein the tropospheric meteorological monitoring attributes include one or more of temperature, air pressure, humidity, wind speed and wind direction;

[0105] The second communication path meteorological monitoring information acquisition module is used to acquire N second communication path meteorological monitoring information based on ionospheric meteorological monitoring attributes, wherein the ionospheric meteorological monitoring attributes include one or more of electron density, electron temperature, collision frequency, ion density, ion temperature and ion composition;

[0106] The third communication path meteorological monitoring information acquisition module is used to acquire N third communication path meteorological monitoring information based on upper-air meteorological monitoring attributes, wherein the upper-air meteorological monitoring attributes include one or more of particulate matter concentration, particulate matter size, temperature and humidity.

[0107] A meteorological monitoring information adding module is used to add the meteorological monitoring information of the N first communication paths, the meteorological monitoring information of the N second communication paths, and the meteorological monitoring information of the N third communication paths into the meteorological monitoring information of the N communication paths.

[0108] The communication time difference calibration value acquisition module is used to construct N meteorological simulation channels based on the meteorological monitoring information of the N communication paths, perform communication time difference analysis, and acquire N communication time difference calibration values.

[0109] Furthermore, the communication time difference calibration value acquisition module also includes:

[0110] A meteorological simulation channel construction module is used to construct the N meteorological simulation channels based on the meteorological monitoring information of the N communication paths.

[0111] The path map acquisition module is used to perform communication simulation based on the N meteorological simulation channels and acquire N signal transmission refraction path maps.

[0112] A communication path baseline construction module is used to connect the start and end points of the N signal transmission refraction path diagrams to construct N communication path baselines.

[0113] The communication time difference analysis module is used to perform communication time difference analysis based on the N communication path baselines and the N signal transmission refraction path diagrams to obtain N communication time difference calibration values.

[0114] Furthermore, the communication time difference analysis module also includes:

[0115] A reference baseline setting module is used to extract N vacuum signal segments from the N communication path baselines and set them as N reference baselines.

[0116] The theoretical propagation duration determination module is used to obtain N reference propagation durations for the N reference baselines based on the N GPS satellites, and determine N theoretical propagation durations, including:

[0117] Formula construction module, which is used to construct the theoretical propagation duration evaluation formula:

[0118] ;

[0119] in, Characterized by the theoretical propagation time from the nth GPS satellite to the mobile station. Characterizing the in-plot length of the nth reference baseline, The in-map length of the baseline of the nth communication path is represented. The reference propagation duration characterizing the nth reference baseline, n∈N, The system error coefficients characterizing the nth satellite;

[0120] The duration determination module is used to determine the N theoretical propagation duration based on the N reference propagation durations according to the theoretical propagation duration evaluation formula.

[0121] The calibration value acquisition module is used to acquire N actual propagation times of the N signal transmission refraction path diagrams, and acquire N communication time difference calibration values ​​based on the N theoretical propagation times.

[0122] Furthermore, the first location information acquisition module 14 also includes:

[0123] The result division module is used to divide the N second distance measurement results into groups of four to obtain M division results;

[0124] A positioning analysis result acquisition module is used to traverse the M division results to perform positioning analysis and acquire M positioning analysis results;

[0125] A discrete value cleaning module is used to perform discrete value cleaning on the M positioning analysis results to obtain Q positioning analysis results.

[0126] An intersection setting module, wherein when the Q positioning analysis results have an intersection, the intersection positioning result is used as the first positioning information;

[0127] A non-intersection setting module is used to take any one of the Q positioning analysis results as the first positioning information when the Q positioning analysis results do not have an intersection.

[0128] Furthermore, the second location information acquisition module 15 also includes:

[0129] The range delineation module is used to delineate the neighborhood identification range with the mobile station as the center;

[0130] A base station status information filtering module is used to filter base station status information that meets the neighborhood identifier range, wherein the base station status information includes base station environment monitoring results;

[0131] A space coefficient evaluation module is used to evaluate the space coefficient based on the base station environment monitoring results and obtain the space coefficient evaluation results.

[0132] The base station information filtering module is used to filter the correction base station with the minimum value of the openness coefficient evaluation result, which is set as the neighboring correction base station, and to obtain the second positioning information of the neighboring correction base station based on the N GPS satellites.

[0133] Furthermore, the openness coefficient evaluation module also includes:

[0134] A module for constructing a formula for evaluating open space coefficients, used to construct the formula for evaluating open space coefficients:

[0135] ;

[0136] in, The openness coefficient characterizes any base station. This represents the distance between the i-th building or mountain that exceeds the height threshold and the base station. This represents the total number of buildings or mountains exceeding a height threshold. This represents the height of the i-th building or mountain that is above the height threshold. A custom height threshold that can affect signal propagation. and Characterized by the normalization adjustment coefficient, Characterizing the first preset weight, Characterizing the second preset weight, Characterizing the third preset weight, Characterizes the level of electromagnetic interference near a preset base station. ;

[0137] The module for obtaining the open space coefficient evaluation result is used to evaluate the open space coefficient based on the base station environment monitoring results according to the open space coefficient evaluation formula, and obtain the open space coefficient evaluation result.

[0138] Through the foregoing detailed description of the measurement result correction method for engineering surveying equipment, those skilled in the art can clearly understand the measurement result correction method and system for engineering surveying equipment in this embodiment. As for the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and relevant parts can be referred to the method section description.

[0139] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method of correcting a measurement result of an engineering surveying apparatus, characterized by, The application is applied to a measurement result correction system for an engineering surveying device, the system is in communication connection with a correction base station and a mobile station, and comprises: A communication state between the mobile station and N GPS satellites is established, N first distance measurement results and N GPS satellite positioning information are obtained; N communication path meteorological monitoring information is loaded, N meteorological simulation channels are constructed for communication time difference analysis, and N communication time difference calibration values are obtained; Error fitting is performed on the N first distance measurement results according to the N communication time difference calibration values, and N second distance measurement results are obtained; Positioning optimization is performed according to the N second distance measurement results and the N GPS satellite positioning information, and first positioning information is determined; Adjacent correction base stations of the mobile station are screened, second positioning information of the adjacent correction base stations is obtained based on the N GPS satellites; The deviation between the second positioning information and the reference positioning information of the adjacent correction base station is calculated, error fitting is performed on the first positioning information, and third positioning information is obtained; The third positioning information is added to the engineering surveying result of the mobile station monitoring point; N communication path meteorological monitoring information is loaded, N meteorological simulation channels are constructed for communication time difference analysis, and N communication time difference calibration values are obtained, comprising: According to the tropospheric meteorological monitoring attribute, N first communication path meteorological monitoring information is obtained, wherein the tropospheric meteorological monitoring attribute comprises one or more of temperature, pressure, humidity, wind speed and wind direction; According to the ionospheric meteorological monitoring attribute, N second communication path meteorological monitoring information is obtained, wherein the ionospheric meteorological monitoring attribute comprises one or more of electron density, electron temperature, collision frequency, ion density, ion temperature and ion composition; According to the upper air meteorological monitoring attribute, N third communication path meteorological monitoring information is obtained, wherein the upper air meteorological monitoring attribute comprises one or more of particle concentration, particle size, temperature and humidity; The N first communication path meteorological monitoring information, the N second communication path meteorological monitoring information and the N third communication path meteorological monitoring information are added to the N communication path meteorological monitoring information; According to the N communication path meteorological monitoring information, N meteorological simulation channels are constructed for communication time difference analysis, and N communication time difference calibration values are obtained, comprising: According to the N communication path meteorological monitoring information, the N meteorological simulation channels are constructed; Based on the N meteorological simulation channels, communication simulation is performed, and N signal transmission refraction path graphs are obtained; The starting point and the ending point of the N signal transmission refraction path graphs are connected to construct N communication path baselines; According to the N communication path baselines and the N signal transmission refraction path graphs, communication time difference analysis is performed to obtain N communication time difference calibration values, comprising: On the N communication path baselines, N vacuum signal segments are extracted and set as N reference baselines; According to the N GPS satellites, N reference propagation time lengths of the N reference baselines are obtained, and N theoretical propagation time lengths are determined, comprising: A theoretical propagation time length evaluation formula is constructed: ； wherein, characterizing a theoretical propagation duration of the n-th GPS satellite to the mobile station, characterizing an in-map length of the n-th reference baseline, characterizing an in-map length of the n-th communication path baseline, characterizing a reference propagation duration of the n-th reference baseline, n ∈ N, characterizing a systematic error coefficient of the n-th satellite; Based on the theoretical propagation duration evaluation formula, the N theoretical propagation durations are determined based on the N reference propagation durations. Obtain the N actual propagation times of the N signal transmission refraction path diagrams, and based on the N theoretical propagation times, obtain the N communication time difference calibration values.

2. The method of claim 1, wherein, Based on the N second distance measurement results and the N GPS satellite positioning information, positioning optimization is performed to determine the first positioning information, including: The N second distance measurement results are divided into groups of four to obtain M division results; The M partitioning results are traversed for localization analysis to obtain M localization analysis results; Discrete value cleaning is performed on the M positioning analysis results to obtain Q positioning analysis results; When the Q positioning analysis results have an intersection, the intersection positioning result is taken as the first positioning information; When the Q positioning analysis results do not overlap, any one of the Q positioning analysis results shall be taken as the first positioning information.

3. A measurement result correction system for an engineering surveying apparatus, characterized by, The system communicates with the correction base station and the mobile station, including: The information acquisition module is used to establish the communication status between the mobile station and N GPS satellites, and to acquire N first distance measurement results and N GPS satellite positioning information. The time difference analysis module is used to load meteorological monitoring information of N communication paths, construct N meteorological simulation channels to perform communication time difference analysis, and obtain N communication time difference calibration values. An error fitting module is used to perform error fitting on the N first distance measurement results based on the N communication time difference calibration values ​​to obtain N second distance measurement results; The first positioning information acquisition module is used to perform positioning optimization based on the N second distance measurement results and the N GPS satellite positioning information to determine the first positioning information; The second positioning information acquisition module is used to filter the neighboring correction base stations of the mobile station and acquire the second positioning information of the neighboring correction base stations based on the N GPS satellites. The third positioning information acquisition module is used to calculate the deviation between the second positioning information and the reference positioning information of the neighboring correction base station, perform error fitting on the first positioning information, and obtain the third positioning information. An information adding module is used to add the third positioning information into the engineering surveying results of the mobile station monitoring point; The time difference analysis module also includes: The first communication path meteorological monitoring information acquisition module is used to acquire N first communication path meteorological monitoring information based on tropospheric meteorological monitoring attributes, wherein the tropospheric meteorological monitoring attributes include one or more of temperature, air pressure, humidity, wind speed and wind direction; The second communication path meteorological monitoring information acquisition module is used to acquire N second communication path meteorological monitoring information based on ionospheric meteorological monitoring attributes, wherein the ionospheric meteorological monitoring attributes include one or more of electron density, electron temperature, collision frequency, ion density, ion temperature and ion composition; The third communication path meteorological monitoring information acquisition module is used to acquire N third communication path meteorological monitoring information based on upper-air meteorological monitoring attributes, wherein the upper-air meteorological monitoring attributes include one or more of particulate matter concentration, particulate matter size, temperature and humidity. A meteorological monitoring information adding module is used to add the meteorological monitoring information of the N first communication paths, the meteorological monitoring information of the N second communication paths, and the meteorological monitoring information of the N third communication paths into the meteorological monitoring information of the N communication paths. A communication time difference calibration value acquisition module is used to construct N meteorological simulation channels based on the meteorological monitoring information of the N communication paths, perform communication time difference analysis, and acquire N communication time difference calibration values. The communication time difference calibration value acquisition module further includes: A meteorological simulation channel construction module is used to construct the N meteorological simulation channels based on the meteorological monitoring information of the N communication paths. The path map acquisition module is used to perform communication simulation based on the N meteorological simulation channels and acquire N signal transmission refraction path maps. A communication path baseline construction module is used to connect the start and end points of the N signal transmission refraction path diagrams to construct N communication path baselines. A communication time difference analysis module is used to perform communication time difference analysis based on the N communication path baselines and the N signal transmission refraction path diagrams to obtain N communication time difference calibration values. The communication time difference analysis module also includes: A reference baseline setting module is used to extract N vacuum signal segments from the N communication path baselines and set them as N reference baselines. The theoretical propagation duration determination module is used to obtain N reference propagation durations of the N reference baselines based on the N GPS satellites, and determine N theoretical propagation durations, including: Formula construction module, which is used to construct the theoretical propagation duration evaluation formula: ； wherein, characterizing a theoretical propagation duration of the n-th GPS satellite to the mobile station, characterizing an in-map length of the n-th reference baseline, characterizing an in-map length of the n-th communication path baseline, characterizing a reference propagation duration of the n-th reference baseline, n ∈ N, characterizing a systematic error coefficient of the n-th satellite; The duration determination module is used to determine the N theoretical propagation duration based on the N reference propagation durations according to the theoretical propagation duration evaluation formula. The calibration value acquisition module is used to acquire N actual propagation times of the N signal transmission refraction path diagrams, and acquire N communication time difference calibration values ​​based on the N theoretical propagation times.

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