A large-scale GNSS reference station network data automatic processing method and device

Abstract

This invention discloses an automatic processing method and apparatus for large-scale GNSS reference station network data, belonging to the field of earth science data processing technology. The method includes selecting IGS frame stations, performing coordinate frame transformation to generate frame station coordinate files, automatically downloading and updating auxiliary files; acquiring station observation files and performing receiver and antenna type checks, data thinning, and standardized naming; dividing the large-scale station network into multiple partitions, automatically configuring the solution parameters for each partition based on the frame station coordinate files and auxiliary files, and completing baseline calculation and network adjustment; automatically extracting the precise coordinates obtained from network adjustment and evaluating the solution accuracy; and setting timed tasks to achieve continuous automated processing. This invention is characterized by high efficiency, accuracy, and automation, and can provide strong technical support for large-scale geoscientific research and applications.

Description

Technical Field

[0001] This invention belongs to the field of Earth science data processing technology, specifically relating to a method and apparatus for automatic processing of large-scale GNSS reference station network data. Background Technology

[0002] With the continuous development of Global Navigation Satellite Systems (GNSS), their applications in fields such as Earth science, surveying and mapping engineering, and weather forecasting are becoming increasingly widespread. As a crucial infrastructure for acquiring high-precision position and time information, the data processing technology of GNSS reference station networks is of paramount importance.

[0003] Traditional GNSS data processing methods largely rely on manual operation, which is cumbersome and inefficient. Meanwhile, with the continuous expansion of GNSS reference station networks, the workload of data processing has increased dramatically, making traditional methods insufficient to meet the demands of large-scale data processing.

[0004] GAMIT software, as a widely used GNSS data processing tool, is characterized by high accuracy and stability. However, its operation is relatively complex and its degree of automation is low, which limits its application in large-scale data processing.

[0005] Therefore, developing an automatic data processing method for large-scale GNSS reference station networks has significant practical application value and scientific significance. Summary of the Invention

[0006] To address the aforementioned technical problems, this invention provides an automatic processing method and apparatus for large-scale GNSS reference station network data. Through automated processing, it improves data processing efficiency and quality, meeting the needs of large-scale geoscientific research and applications.

[0007] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0008] A method for automatic processing of large-scale GNSS reference station network data, the method comprising:

[0009] Step S1: Select the IGS frame station, perform coordinate frame transformation to generate the frame station coordinate file, and automatically download and update the auxiliary file;

[0010] Step S2: Obtain the station observation files and perform receiver and antenna type checks, data thinning, and standardized naming;

[0011] Step S3: Divide the large-scale station network into multiple partitions, and automatically configure the solution parameters for each partition based on the frame station coordinate file and auxiliary file, and complete the baseline solution and network adjustment;

[0012] Step S4: Automatically extract the precise coordinates obtained from the network adjustment and evaluate the solution accuracy. Set up a timed task to achieve continuous automated processing.

[0013] On the other hand, the present invention provides a large-scale GNSS reference station network data automatic processing device, comprising:

[0014] The preparation module is used to select IGS frame stations, perform coordinate frame transformation to generate frame station coordinate files, and automatically download and update auxiliary files;

[0015] The station data standardization processing module is used to acquire station observation files and perform receiver and antenna type checks, data thinning, and standardized naming.

[0016] The partitioning solution processing module is used to divide a large-scale station network into multiple partitions. Based on the frame station coordinate files and auxiliary files, it automatically configures the solution parameters of each partition and completes baseline solution and network adjustment.

[0017] The output module is used to automatically extract precise coordinates obtained from network adjustment and evaluate the solution accuracy, and to set up timed tasks to achieve continuous automated processing.

[0018] Thirdly, the present invention provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs; wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the aforementioned method for automatic processing of large-scale GNSS reference station network data.

[0019] Fourthly, the present invention provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, enable the processor to implement the aforementioned method for automatic processing of large-scale GNSS reference station network data.

[0020] The beneficial effects of this invention are as follows:

[0021] This invention organically combines automation technology with advanced data processing algorithms to achieve fully automated data processing. Starting with data acquisition, through coordinate extraction, and culminating in accuracy assessment, this invention significantly improves the efficiency of the entire processing flow. During the data processing phase, it automatically downloads and updates necessary auxiliary files while refining observation files to ensure data integrity and accuracy. Furthermore, by employing a station zoning strategy, this invention effectively addresses the challenges of large-scale data processing, guaranteeing the efficiency and quality of the calculations. During parameter configuration and calculation, this invention automatically adjusts parameters according to the characteristics of each zone, ensuring the accuracy and stability of the calculations. This invention can also automatically extract precise coordinate information and automatically assess the accuracy of station locations by comparing them with the previous day's data, providing reliable data support for scientific research and practical applications. Finally, by setting scheduled tasks, this invention achieves real-time data processing and continuous monitoring, further enhancing the timeliness and reliability of data processing. Attached Figure Description

[0022] Figure 1 This is a flowchart of a large-scale GNSS reference station network data automatic processing method according to the present invention;

[0023] Figure 2 This is a schematic diagram of a large-scale GNSS reference station network data automatic processing device according to the present invention. Detailed Implementation

[0024] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0025] like Figure 1 As shown, the automatic processing method for large-scale GNSS reference station network data of the present invention includes the following steps:

[0026] Step S1: Automatically acquire frame station information and complete data preparation: Select the IGS frame station, perform coordinate frame transformation to generate frame station coordinate files, and automatically download and update auxiliary files; including:

[0027] Step S11: Obtain frame station information. Based on the station distribution information, select IGS stations with good surrounding distribution as frame stations to participate in subsequent calculations. Obtain the precise coordinate information of the IGS stations, and then perform coordinate frame transformation based on velocity information and coordinate information at a fixed epoch to obtain frame station coordinates that meet user requirements. Store this coordinates in a frame.txt file as the frame station coordinate file. The file format is:

[0028] <station><x_coord> <y_coord> <z_coord> <x_vel> <y_vel> <z_vel> <epoch>

[0029] The data, in the following order, includes: station name, x-coordinate at a specific frame epoch, y-coordinate at a specific frame epoch, z-coordinate at a specific frame epoch, x-velocity at a specific frame epoch, y-velocity at a specific frame epoch, z-velocity at a specific frame epoch, and the specific frame epoch. A sample document is provided below.

[0030] BADG_GPS -838281.93058 3865777.32617 4987624.58970 -0.027110.00017 -0.00355 2015.00

[0031] BJFS_GPS -2148744.39656 4426641.20084 4044655.84256 -0.03238-0.00603 -0.00714 2015.00

[0032] CHAN_GPS -2674427.51713 3757143.12333 4391521.57678 -0.02713-0.00925 -0.00965 2015.00

[0033] DAEJ_GPS -3120042.26632 4084614.75772 3764026.82989 -0.02701-0.01231 -0.00894 2015.00

[0034] OSN4_GPS -3068341.08234 4066863.87167 3824756.92050 -0.02627-0.00929 -0.00982 2015.00

[0035] SEJN_GPS -3110081.88381 4082093.94123 3775023.50558 -0.02786-0.01241 -0.00886 2015.00

[0036] SHAO_GPS -2831733.81522 4675665.82028 3275369.30342 -0.03025-0.01233 -0.01100 2015.00

[0037] SUWN_GPS -3062023.14578 4055447.88110 3841818.16774 -0.02796-0.01278 -0.00902 2015.00

[0038] Step S12: Precise File Download and Table File Update. Automatically download auxiliary files, including precise orbit files (SP3 files), broadcast ephemeris files (brdc files), and IGS frame station observation files, saving them all to a specific path. Download IGS frame station observation files based on the frame station names in the frame.txt file. Automatically convert all downloaded 'd' files to 'o' files using the CRX2RNX program, and then rename them all to the form {xxxx}{doy}0.{yr}o. Here, {xxxx} represents the lowercase four-digit station name, {doy} is the three-digit day-year sequence, and {yr} is the two-digit year. When updating the table files, automatically determine the current epoch and the last table file update date. If the table file update date is later than the current epoch, it will not be updated again.

[0039] Step S2, Station Data Standardization Processing: Obtain station observation files and perform receiver and antenna type checks, data thinning, and standardized naming; including:

[0040] Obtain the required station's standard observation files in RINEX format. First, check the receiver and antenna types and rename the files accordingly. For some private stations, the observation files may lack receiver and antenna types. Locate the corresponding antenna and receiver types by station name. Automatically update the receiver information in the "REC # / TYPE / VERS" line and the antenna type in the "ANT # / TYPE" line, ensuring character alignment. For data with a 1-second sampling interval, perform data thinning to 30 seconds. After decompressing the data, rename all station observation files to the format {xxxx}{doy}0.{yr}o. Here, {xxxx} represents the lowercase four-digit station name, {doy} is the three-digit day-year sequence, and {yr} is the two-digit year.

[0041] Step S3, Partitioning and Solving: The large-scale station network is divided into multiple partitions, frame station coordinate files and auxiliary files are generated, and the calculation parameters for each partition are automatically configured, and baseline calculation and network adjustment are completed; including:

[0042] Step S31: Station Partitioning. For large-scale GNSS reference station networks, first determine the number of stations. If the number of stations is no more than 60, no partitioning is needed, and the calculation can be performed directly. Otherwise, station partitioning is required. Each region should have no more than 60 stations, and the region should be divided into N partitions. The station names should be stored in N files respectively.

[0043] Step S32: Automatic parameter configuration for each partition. Based on the generated N partition files, N project files are automatically created. The corresponding observation files are sequentially placed into the rinex files under each of the N projects. The auxiliary files (precision product files and table files) generated in step S12 are copied sequentially. Parameter configuration is performed for each partition in a loop. The station coordinates in the lfile file are updated (if this is not the first calculation, the lfile file automatically updated during the previous calculation is used). Descriptions of fixed stations are provided in the sites.defaults file. Parameters in the sittbl file are automatically set according to user requirements. Log records are generated and saved in a specific path.

[0044] Step S33: Baseline Calculation and Network Adjustment. The `sh_gamit` command is invoked to perform baseline calculations partition by partition. All automatically generated .h files for each partition are automatically copied to the first partition's folder, with the file extension changed to prevent duplication. Based on user requirements, the parameters in the gsoln cmd configuration file are automatically configured to perform unified adjustment calculations across multiple networks.

[0045] Step S4, Result Evaluation and Automated Execution: Automatically extract precise coordinates and evaluate the solution accuracy; set up scheduled tasks to achieve continuous automated processing; including:

[0046] Step S41: Precise Coordinate Extraction and Automatic Update of lfile. Based on the org result file calculated in step S33, obtain the coordinates of all stations involved in the calculation. The precise coordinates of all stations to be calculated are placed in the file station_coord_{year}{doy}.txt. Based on the station names in the frame.txt file, extract the precise coordinate information of all frame stations after calculation and compare it with the actual frame station coordinates in frame.txt to obtain the frame station accuracy. This accurate coordinate information is named frame_accu_{year}{doy}.txt, which can be used to simply evaluate the accuracy of the calculation. Here, {year} represents the four-digit year, and {doy} represents the three-digit day of the year. The final obtained precise coordinates are automatically updated in the lfile file to ensure the highest accuracy of the initial coordinates, thus guaranteeing the stability of subsequent calculations. An example of the frame_accu_{year}{doy}.txt file is as follows:

[0047] chan 0.00060 -0.00293 0.00849 -2674427.75989 3757143.042784391521.50052 -2674427.76049 3757143.04571 4391521.49203

[0048] daej -0.00320 0.00291 0.00120 -3120042.51719 4084614.643173764026.75855 -3120042.51399 4084614.64026 3764026.75735

[0049] sejn 0.00118 -0.00077 -0.00068 -3110082.11696 4082093.833723775023.43254 -3110082.11814 4082093.83449 3775023.43322

[0050] shao -0.00151 0.00018 -0.00316 -2831734.07597 4675665.71499 3275369.21367 -2831734.07446 4675665.71481 3275369.21683

[0051] wuhn 0.00137 0.00899 0.00220 -2267750.06152 5009154.19136 3221290.56811 -2267750.06289 5009154.18237 3221290.56591

[0052] Step S42: Automatic evaluation of coordinate accuracy for a large-scale GNSS reference station network. The precise coordinates of all stations to be measured are automatically subtracted from the precise coordinates obtained the previous day and compared. The resulting coordinate accuracy is stored in the file station_accu_{year}{doy}.txt, which can be used as a reference for evaluating the accuracy and stability of station positions. A sample document is provided below.

[0053] CHAN 0.00139 -0.00568 -0.00451 -2674427.75979 3757143.045084391521.48780 -2674427.76118 3757143.05076 4391521.49231

[0054] D074 -0.00212 -0.00021 -0.00295 -2730539.19386 4278471.945463849707.52792 -2730539.19174 4278471.94567 3849707.53087

[0055] DAEJ -0.00141 0.00034 -0.00177 -3120042.51250 4084614.637483764026.75566 -3120042.51109 4084614.63714 3764026.75743

[0056] SHAO -0.00088 -0.00635 -0.00477 -2831734.07271 4675665.704943275369.21732 -2831734.07183 4675665.71129 3275369.22209

[0057] Step S43: Execute the scheduled task. The scheduled task is executed automatically at 0:30 AM every day to automatically acquire the accuracy information of the frame station and the station to be calculated, completing the automatic calculation of the large-scale GNSS reference station network and making full use of server resources.

[0058] In summary, this invention not only automatically downloads and updates relevant auxiliary files but also performs meticulous processing of observation files, ensuring data integrity and accuracy. During parameter configuration and calculation, it automatically adjusts parameters based on the characteristics of different zones, ensuring the accuracy and stability of the calculations. It automatically extracts precise coordinate information and, by comparing it with the previous day's data, automatically assesses the accuracy of the station's location, providing strong data support for scientific research and practical applications. Through the setting of timed tasks, it achieves real-time data processing and continuous monitoring, further improving the timeliness and reliability of data processing.

[0059] On the other hand, such as Figure 2 As shown, the present invention provides an automatic data processing device for a large-scale GNSS reference station network, which includes modules capable of implementing the steps of the aforementioned method, specifically including:

[0060] The preparation module is used to select IGS frame stations, perform coordinate frame transformation to generate frame station coordinate files, and automatically download and update auxiliary files;

[0061] The station data standardization processing module is used to acquire station observation files and perform receiver and antenna type checks, data thinning, and standardized naming.

[0062] The partitioning solution processing module is used to divide a large-scale station network into multiple partitions. Based on the frame station coordinate files and auxiliary files, it automatically configures the solution parameters of each partition and completes baseline solution and network adjustment.

[0063] The output module is used to automatically extract precise coordinates obtained from network adjustment and evaluate the solution accuracy, and to set up timed tasks to achieve continuous automated processing.

[0064] Thirdly, the present invention provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs; wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the aforementioned method for automatic processing of large-scale GNSS reference station network data.

[0065] Fourthly, the present invention provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, enable the processor to implement the aforementioned method for automatic processing of large-scale GNSS reference station network data.

[0066] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present invention can be implemented using various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0067] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0068] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0069] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0070] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0071] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.< / epoch> < / station>

Claims

1. A method for automatic processing of large-scale GNSS reference station network data, characterized in that, The method includes: Step S1: Select the IGS frame station, perform coordinate frame transformation to generate the frame station coordinate file, and automatically download and update the auxiliary file; Step S2: Obtain the station observation files and perform receiver and antenna type checks, data thinning, and standardized naming; Step S3: Divide the large-scale station network into multiple partitions. Based on the frame station coordinate file and auxiliary file, automatically configure the solution parameters for each partition and complete baseline calculation and network adjustment; including: Step S31: Divide the large-scale station network into N partitions, and store the station names in N files respectively; Step S32: Automatically create project files for each partition, copy auxiliary files and automatically configure solution parameters, including updating the coordinates of the lfile file and setting parameters for the sites.defaults and sittbl files; Step S33: Call the sh_gamit command for baseline calculation on a partition-by-partition basis, automatically merge the h files of each partition, and configure gsoln parameters to complete the unified adjustment of multiple networks; Step S4: Automatically extract the precise coordinates obtained from the network adjustment and evaluate the solution accuracy. Set up a timed task to achieve continuous automated processing. The automatic extraction of precise coordinates and evaluation of solution accuracy includes: obtaining the coordinates of all stations involved in the solution based on the org result file calculated in step S33; extracting the precise coordinate information of all frame stations after solution based on the station names in the frame.txt file; and comparing it with the frame station coordinates in frame.txt to obtain the frame station accuracy.

2. The method for automatic processing of large-scale GNSS reference station network data according to claim 1, characterized in that, In step S1, the generation of the frame station coordinate file includes: selecting surrounding IGS stations as frame stations based on the station distribution; obtaining the precise coordinates and velocity information of the IGS stations; and generating a frame station coordinate file in frame.txt format containing station name, coordinates, velocity, and epoch information through coordinate frame transformation.

3. The method for automatic processing of large-scale GNSS reference station network data according to claim 1, characterized in that, In step S1, the auxiliary files include precise orbit files, broadcast ephemeris files, and IGS frame station observation files. The IGS frame station observation files are downloaded based on the frame.txt format frame station coordinate file name. The downloaded d files are automatically converted to .o files using the CRX2RNX program, and then all are renamed to include station, year, and year information.

4. The method for automatic processing of large-scale GNSS reference station network data according to claim 1, characterized in that, Step S2 includes: automatically supplementing station observation files with missing receiver and antenna type information; thinning the 1-second sampling interval data; and renaming all station observation files to include station, year, and year information.

5. The method for automatic processing of large-scale GNSS reference station network data according to claim 1, characterized in that, Step S4 further includes: automatically comparing the precise coordinates of all stations to be measured with the precise coordinates of the stations to be measured obtained the previous day to obtain the coordinate accuracy and evaluate the station position accuracy and stability.

6. A large-scale GNSS reference station network data automatic processing device, applied to the method described in any one of claims 1-5, characterized in that, include: The preparation module is used to select IGS frame stations, perform coordinate frame transformation to generate frame station coordinate files, and automatically download and update auxiliary files; The station data standardization processing module is used to acquire station observation files and perform receiver and antenna type checks, data thinning, and standardized naming. The partitioning solution processing module is used to divide a large-scale station network into multiple partitions. Based on the frame station coordinate files and auxiliary files, it automatically configures the solution parameters of each partition and completes baseline solution and network adjustment. The output module is used to automatically extract precise coordinates obtained from network adjustment and evaluate the solution accuracy, and to set up timed tasks to achieve continuous automated processing.

7. An electronic device, characterized in that, include: One or more processors; Memory, used to store one or more programs; When one or more programs are executed by the one or more processors, the one or more processors implement the automatic processing method for large-scale GNSS reference station network data as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, It stores executable instructions that, when executed by a processor, enable the processor to implement the automatic processing method for large-scale GNSS reference station network data as described in any one of claims 1-5.

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