Data quality inspection method based on Beidou third-generation satellite

Abstract

The invention relates to a data quality inspection method based on a Beidou third-generation satellite. The method comprises the following steps: acquiring original observation data of the Beidou third-generation satellite received by a base station; analyzing the original observation data to obtain an observation file; preprocessing the observation file to obtain a cycle slip number and a multi-hop error; if the obtained signal-to-noise ratio observation value is greater than a preset signal-to-noise ratio threshold value of the base station, indicating that the base station operates abnormally, and generating an operation maintenance signal; otherwise, calculating a base station monitoring coefficient based on the signal-to-noise ratio observation value, a preset base station signal-to-noise ratio threshold value, the cycle slip number and the multi-hop error; and judging a relationship between the reference station monitoring coefficient and a preset reference station monitoring coefficient threshold, and obtaining a data quality inspection result based on a judgment result.

Description

Technical Field

[0001] This invention relates to the field of data quality inspection technology, and mainly to a data quality inspection method based on BeiDou-3 satellites. Background Technology

[0002] With the accelerated modernization of global navigation satellite systems, the number of satellite signal frequency bands continues to increase. Especially in specialized fields such as power grid BeiDou systems, data quality directly affects the efficiency and stability of terminal fixed solution acquisition. Problems such as pseudorange deviation, carrier phase cycle slip, multipath interference, and abnormal signal-to-noise ratio in raw observation data and ephemeris data can directly lead to a decrease in positioning accuracy, slow convergence of fixed solutions, or even failure.

[0003] Chinese invention patent application CN119322813A discloses a data quality analysis and management system and method based on BeiDou reference station network observation data. The technical solution includes: a data conversion module for converting raw BeiDou observation data collected from the reference station; a data stitching module for stitching hourly files of observation data into a single daily file; a data verification module for storing data files in text format and verifying the file header for compliance; a data quality analysis module for reading GNSS observation data and navigation ephemeris data from the reference station to perform data quality analysis for BDS / GPS / Galileo / GLONASS navigation systems and all publicly available navigation frequencies; a visualization module for displaying reference station quality images and indicator values; and a data editing module for data editing operations. However, the aforementioned technical solutions focus on generalized quality analysis of multiple navigation systems (BDS / GPS / Galileo / GLONASS) and all publicly available frequency points, without specifically optimizing for the unique signal characteristics of BeiDou-3 satellites (such as the characteristics of newly added frequency points like B1C and B2a, and differences in observation data formats). They lack sufficient adaptation to new frequency points and protocols, and lack the ability to analyze BeiDou-3 new frequency point data. Furthermore, they do not fully adapt to the encoding rules of the new BeiDou system signals in the RTCM33 supplementary protocol. In addition, the aforementioned technical solutions have not established a linkage analysis mechanism; they lack both a signal-to-noise ratio threshold judgment rule for BeiDou-3 data and the ability to identify equipment malfunctions through the correlation between signal-to-noise ratio and core errors. Moreover, the aforementioned technical solutions have not designed a comprehensive evaluation model that integrates core error indicators for BeiDou-3 data, making it impossible to achieve accurate quantitative quality inspection of this type of data; they can only provide single-dimensional indicators or document-based normative conclusions. Summary of the Invention

[0004] To address the problems existing in the prior art, this invention proposes a data quality inspection method based on BeiDou-3 satellites.

[0005] The technical solution of the present invention is as follows: On the one hand, this invention proposes a data quality inspection method based on BeiDou-3 satellites, the method comprising: Obtain raw observation data from BeiDou-3 satellites received by the base station; The raw observation data is parsed to obtain the observation file; the observation file is preprocessed to obtain the number of cycle slips and the multi-slip error. If the obtained signal-to-noise ratio (SNR) observation value is greater than the preset base station SNR threshold, it indicates that the base station is operating abnormally and an operation and maintenance signal is generated; otherwise, the base station monitoring coefficient is calculated based on the SNR observation value, the preset base station SNR threshold, the number of cycle slips, and the multi-slip error. Determine the relationship between the baseline station monitoring coefficient and the preset baseline station monitoring coefficient threshold, and obtain the data quality inspection results based on the determination results.

[0006] Preferably, the BeiDou-3 satellites include at least one of the following satellite systems: GPS satellites, BDS satellites, GLONASS satellites, and QZSS satellites.

[0007] Preferably, the format of the raw observation data includes at least one of the following: RTCM3.0, RTCM3.1, RTCM3.2, RTCM3.3, RTCM2.3, RTCM2.4, and CMR format; The observation files are in rinex format.

[0008] Preferably, the preprocessing further includes: Based on the error between pseudorange and carrier phase in the original observation data, original observation data with errors exceeding a preset range are discarded.

[0009] Preferably, the specific steps for calculating the number of cycle slips are as follows: Extract pseudorange and carrier phase observations of designated satellites at preset frequency points from the preprocessed observation files; wherein the preset frequency points include at least the B1C, B2a and B3I frequency points of BeiDou-3. A combined observation sequence of frequency points B1C and B2a is constructed using the geometric distance-free combination method. If the difference between consecutive epochs in the combined observation sequence exceeds a preset first threshold, the cycle slip position is initially marked. Further, the cycle slip verification values ​​between the B1C, B2a and B3I frequency points were constructed using the three-frequency geometric distance-free combination method to verify the initially marked cycle slip positions; If the change in the cycle slip verification value between consecutive epochs exceeds a preset second threshold, a cycle slip is confirmed to have occurred; otherwise, the initially marked cycle slip position is revoked. Within a predetermined quality inspection time window, the total number of events confirmed to have occurred cycle slips is recorded as the cycle slip count.

[0010] Preferably, the specific steps for calculating the multi-hop error are as follows: Extract pseudorange and carrier phase observations of designated satellites at preset frequency points from the preprocessed observation files; wherein the preset frequency points include at least the B1C and B2a frequency points of BeiDou-3. Using the pseudorange observations of frequencies B1C and B2a, as well as the carrier phase, the dual-frequency observations are calculated as follows: ; ; In the formula, This represents observations from two frequency points; This represents the pseudorange observation value at frequency B1C; This indicates the carrier wavelength at frequency B1C; Indicates the carrier phase at frequency B1C; This represents the carrier wavelength at frequency point B2a; This indicates the carrier phase at frequency B2a; Indicates the center frequency coefficient; This indicates the center frequency of the B1C frequency point; This indicates the center frequency of frequency point B2a; The dual-frequency point observations are statistically analyzed within a preset time window, and their standard deviation is calculated as an indicator of the multipath error intensity of the specified satellite in the current epoch. The multi-hop error is obtained by weighted averaging of all multipath error intensity indices within the current epoch.

[0011] Preferably, the base station monitoring coefficient is calculated based on the signal-to-noise ratio observation value, the preset base station signal-to-noise ratio threshold, the number of cycle slips, and the multi-hop error. The calculation method is as follows: ; In the formula, Indicates the first The baseline station monitoring coefficient for each signal-to-noise ratio observation; Indicates the correction factor; Indicates the first proportionality coefficient; This represents the second proportionality coefficient; Indicates the third proportionality coefficient; Indicates the first One signal-to-noise ratio observation; This indicates the preset signal-to-noise ratio threshold for the base station; Indicates the number of cycle jumps; Indicates the total number of observed epochs; Indicates multi-hop error; If the monitoring coefficient of the base station is less than the threshold of the monitoring coefficient of the base station, the current signal-to-noise ratio observation value is deemed to be of acceptable quality. If the monitoring coefficient of the base station is greater than or equal to the threshold of the monitoring coefficient of the base station, the current signal-to-noise ratio observation value is deemed to be of unqualified quality and is discarded.

[0012] On the other hand, the present invention also provides a data quality inspection system based on BeiDou-3 satellites, the system comprising: The data acquisition module acquires the raw observation data received by the base station from the BeiDou-3 satellites; The data processing module parses the raw observation data to obtain observation files; it preprocesses the observation files to obtain the number of cycle slips and multi-slip error. If the acquired signal-to-noise ratio (SNR) observation value is greater than the preset base station SNR threshold, it indicates that the base station is operating abnormally and generates an operation and maintenance signal; otherwise, the base station monitoring coefficient is calculated based on the SNR observation value, the preset base station SNR threshold, the number of cycle slips, and the multi-slip error. Determine the relationship between the baseline station monitoring coefficient and the preset baseline station monitoring coefficient threshold, and obtain the data quality inspection results based on the determination results.

[0013] In another aspect, the present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method described in the present invention.

[0014] In another aspect, the present invention also provides a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the method described in the present invention.

[0015] The present invention has the following beneficial effects: 1. This invention provides a data quality inspection method based on BeiDou-3 satellites. Based on the BeiDou-3 satellite system architecture, it is compatible with multiple satellite systems such as GPS, BDS, GLONASS, and QZSS, and adapts to a full range of data formats. At the same time, it specifically supports the new frequency points B1C, B2a, and B3I added by BeiDou-3, solves the problem of missing adaptation to new frequency points and new protocols, improves the compatibility range of multiple satellite systems and multiple data formats, and enhances the ability to analyze and inspect data from new frequency points of BeiDou-3. 2. This invention provides a data quality inspection method based on BeiDou-3 satellites. It employs a combination of dual-frequency preliminary marking and three-frequency verification to achieve accurate identification and error correction of cycle slips. This solves the problems of mismarking and omissions in traditional single-frequency / dual-frequency cycle slip detection, improving the accuracy of cycle slip detection, enhancing the precision of cycle slip position marking, and strengthening the robustness of cycle slip detection. Based on pseudorange observations, carrier phase, and center frequency coefficients of dual-frequency points, it quantifies the intensity of multipath errors, achieving accurate characterization of multipath errors and improving the accuracy of multipath error calculation. It also enhances the anti-interference capability of multipath errors under complex terrain conditions. 3. This invention provides a data quality inspection method based on BeiDou-3 satellites. It constructs a three-dimensional quality inspection model that integrates signal-to-noise ratio observations, cycle slip count, and multi-hop error to obtain the monitoring coefficient of the base station. This achieves collaborative quantitative evaluation of multi-dimensional indicators, breaks through the one-sidedness of traditional single-indicator quality inspection, improves the scientificity and comprehensiveness of data quality inspection results, and enhances the flexibility of quality inspection standards. Attached Figure Description

[0016] Figure 1 This is a detailed flowchart of an embodiment of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] It should be understood that the step numbers used in the text are for ease of description only and are not intended to limit the order in which the steps are performed.

[0019] It should be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0020] The terms “comprising” and “including” indicate the presence of the described feature, whole, step, operation, element and / or component, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0021] The term “and / or” refers to any combination of one or more of the associated listed items, as well as all possible combinations, and includes these combinations.

[0022] Example 1: See Figure 1 This invention provides a data quality inspection method based on BeiDou-3 satellites, the method comprising: S1. Obtain the raw observation data of BeiDou-3 satellites received by the base station; The BeiDou-3 satellites include at least one of the following satellite systems: GPS satellites, BDS satellites, GLONASS satellites, and QZSS satellites; The original observation data shall include at least one of the following formats: RTCM3.0, RTCM3.1, RTCM3.2, RTCM3.3, RTCM2.3, RTCM2.4, and CMR format; S2. Parse the raw observation data to obtain the observation file; the observation file is in rinex format. The observation file is a file output by a satellite navigation receiver or data analysis system that records the original observation data in a standardized format. Essentially, it is a set of digital measurement values ​​that can be directly used for positioning calculations after the satellite radio frequency signals captured by the receiver antenna have undergone frequency conversion, analog-to-digital conversion, correlator processing, and demodulation. The contents of the observation file include For BeiDou-3, the core content includes: pseudorange observations, which are the approximate distance of the signal propagation from the satellite to the receiver antenna; carrier phase observations, which are highly accurate phase measurements; Doppler shift, which reflects the relative velocity between the satellite and the receiver; and signal-to-noise ratio, which reflects the signal reception quality. The header information includes metadata such as receiver type, antenna information, approximate coordinates, observation start time, observation interval, and a list of observed frequency points (for BeiDou-3, B1C, B2a, B3I, etc. will be explicitly listed). S3. Preprocess the observation files to obtain the number of cycle slips and multi-slip error; S31, The preprocessing further includes: Based on the error between pseudorange and carrier phase in the original observation data, original observation data with errors exceeding the preset range are discarded; S32. The specific steps for calculating the number of cycle slips are as follows: Extract pseudorange and carrier phase observations of designated satellites at preset frequency points from the preprocessed observation files; wherein the preset frequency points include at least the B1C, B2a and B3I frequency points of BeiDou-3. The combined observation sequence of frequency points B1C and B2a is constructed using the geometric distance-free combination method. The calculation method is as follows: ; In the formula, Represents a sequence of combined observations; This indicates the carrier wavelength at frequency B1C; Indicates the carrier phase at frequency B1C; This represents the carrier wavelength at frequency point B2a; This indicates the carrier phase at frequency B2a; If the difference between consecutive epochs in the combined observation sequence exceeds a preset first threshold, the cycle slip position is initially marked. Further, the cycle slip verification values ​​between frequency points B1C, B2a, and B3I are constructed using the three-frequency geometric distance-free combination method to verify the initially marked cycle slip positions. The calculation method is as follows: ; In the formula, Indicates the cycle slip verification value; This represents the first elimination coefficient, set based on frequency relationships, to eliminate the effects of ionospheric delay; Indicates the second elimination coefficient; Indicates the third elimination coefficient; This indicates the carrier wavelength at frequency B3I; This indicates the carrier phase at frequency B3I; If the change in the cycle slip verification value between consecutive epochs exceeds a preset second threshold, a cycle slip is confirmed to have occurred; otherwise, the initially marked cycle slip position is revoked. Within a predetermined quality inspection time window, the total number of events confirmed to have occurred cycle slips is recorded as the cycle slip count. S33. The specific calculation steps for the multi-hop error are as follows: Extract pseudorange and carrier phase observations of designated satellites at preset frequency points from the preprocessed observation files; wherein the preset frequency points include at least the B1C and B2a frequency points of BeiDou-3. Using the pseudorange observations of the B1C and B2a frequencies and the carrier phase, the dual-frequency observations are calculated as follows: ; ; In the formula, This represents observations from two frequency points; This represents the pseudorange observation value at frequency B1C; Indicates the center frequency coefficient; This indicates the center frequency of the B1C frequency point; This indicates the center frequency of frequency point B2a; The dual-frequency point observations are statistically analyzed within a preset time window, and their standard deviation is calculated as an indicator of the multipath error intensity of the specified satellite in the current epoch. The multihop error is obtained by weighted averaging of all multipath error intensity indices within the current epoch. The calculation method is as follows: ; In the formula, Indicates multi-hop error; Indicates the number of multipath error intensity indicators; Indicates the first The weights of each multipath error intensity index; Indicates the first One multipath error strength index; S4. If the obtained signal-to-noise ratio observation value is greater than the preset base station signal-to-noise ratio threshold, it indicates that the base station is operating abnormally and an operation and maintenance signal is generated; otherwise, the base station monitoring coefficient is calculated based on the signal-to-noise ratio observation value, the preset base station signal-to-noise ratio threshold, the number of cycle slips, and the multi-slip error. The base station monitoring coefficient is calculated based on the observed signal-to-noise ratio (SNR), the preset base station SNR threshold, the number of cycle slips, and the multi-slip error. The calculation method is as follows: ; In the formula, Indicates the first The baseline station monitoring coefficient for each signal-to-noise ratio observation; Indicates the correction factor; Indicates the first proportionality coefficient; This represents the second proportionality coefficient; Indicates the third proportionality coefficient; Indicates the first One signal-to-noise ratio observation; This indicates the preset signal-to-noise ratio threshold for the base station; Indicates the number of cycle jumps; Indicates the total number of observed epochs; S5. Determine the relationship between the base station monitoring coefficient and the preset base station monitoring coefficient threshold, and obtain the data quality inspection result based on the determination result; If the monitoring coefficient of the base station is less than the threshold of the monitoring coefficient of the base station, the current signal-to-noise ratio observation value is deemed to be of acceptable quality. If the monitoring coefficient of the base station is greater than or equal to the threshold of the monitoring coefficient of the base station, the current signal-to-noise ratio observation value is deemed to be of unqualified quality and is discarded.

[0023] Example 2: This embodiment provides a data quality inspection system based on BeiDou-3 satellites, the system comprising: The data acquisition module acquires the raw observation data received by the base station from the BeiDou-3 satellites; The data processing module parses the raw observation data to obtain observation files; it preprocesses the observation files to obtain the number of cycle slips and multi-slip error. If the acquired signal-to-noise ratio (SNR) observation value is greater than the preset base station SNR threshold, it indicates that the base station is operating abnormally and generates an operation and maintenance signal; otherwise, the base station monitoring coefficient is calculated based on the SNR observation value, the preset base station SNR threshold, the number of cycle slips, and the multi-slip error. Determine the relationship between the baseline station monitoring coefficient and the preset baseline station monitoring coefficient threshold, and obtain the data quality inspection results based on the determination results.

[0024] Example 3: This embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements a data quality inspection method based on BeiDou-3 satellites as described in any one of Embodiment 1.

[0025] Example 4: This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements a data quality inspection method based on BeiDou-3 satellites as described in any one of Embodiment 1.

[0026] In this application embodiment, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent the existence of A alone, A and B simultaneously, or B alone. A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one of a, b, and c can represent: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, and c can be single or multiple.

[0027] Those skilled in the art will recognize that the units and algorithm steps described in the embodiments disclosed herein can be implemented using electronic hardware, computer software, or a combination of electronic hardware and software. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art 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.

[0028] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0029] In the several embodiments provided in this application, any function, if implemented as a software functional unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0030] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A data quality inspection method based on BeiDou-3 satellites, characterized in that, The method includes: Obtain raw observation data from BeiDou-3 satellites received by the base station; The raw observation data is parsed to obtain the observation file; the observation file is preprocessed to obtain the number of cycle slips and the multi-slip error. If the obtained signal-to-noise ratio (SNR) observation value is greater than the preset base station SNR threshold, it indicates that the base station is operating abnormally and an operation and maintenance signal is generated; otherwise, the base station monitoring coefficient is calculated based on the SNR observation value, the preset base station SNR threshold, the number of cycle slips, and the multi-slip error. Determine the relationship between the baseline station monitoring coefficient and the preset baseline station monitoring coefficient threshold, and obtain the data quality inspection results based on the determination results.

2. The data quality inspection method based on BeiDou-3 satellites according to claim 1, characterized in that, The BeiDou-3 satellites include at least one of the following satellite systems: GPS satellites, BDS satellites, GLONASS satellites, and QZSS satellites.

3. The data quality inspection method based on BeiDou-3 satellites according to claim 1, characterized in that, The original observation data shall include at least one of the following formats: RTCM3.0, RTCM3.1, RTCM3.2, RTCM3.3, RTCM2.3, RTCM2.4, and CMR format; The observation files are in rinex format.

4. The data quality inspection method based on BeiDou-3 satellites according to claim 1, characterized in that, The preprocessing also includes: Based on the error between pseudorange and carrier phase in the original observation data, original observation data with errors exceeding a preset range are discarded.

5. A data quality inspection method based on BeiDou-3 satellites according to claim 1, characterized in that, The specific steps for calculating the number of cycle slips are as follows: Extract pseudorange and carrier phase observations of designated satellites at preset frequency points from the preprocessed observation files; wherein the preset frequency points include at least the B1C, B2a and B3I frequency points of BeiDou-3. A combined observation sequence of frequency points B1C and B2a is constructed using the geometric distance-free combination method. If the difference between consecutive epochs in the combined observation sequence exceeds a preset first threshold, the cycle slip position is initially marked. Further, the cycle slip verification values ​​between the B1C, B2a and B3I frequency points were constructed using the three-frequency geometric distance-free combination method to verify the initially marked cycle slip positions; If the change in the cycle slip verification value between consecutive epochs exceeds a preset second threshold, a cycle slip is confirmed to have occurred; otherwise, the initially marked cycle slip position is revoked. Within a predetermined quality inspection time window, the total number of events confirmed to have occurred cycle slips is recorded as the cycle slip count.

6. A data quality inspection method based on BeiDou-3 satellites according to claim 5, characterized in that, The specific steps for calculating the multi-hop error are as follows: Extract pseudorange and carrier phase observations of designated satellites at preset frequency points from the preprocessed observation files; wherein the preset frequency points include at least the B1C and B2a frequency points of BeiDou-3. Using the pseudorange observations of frequencies B1C and B2a, as well as the carrier phase, the dual-frequency observations are calculated as follows: ； ； In the formula, This represents observations from two frequency points; This represents the pseudorange observation value at frequency B1C; This indicates the carrier wavelength at frequency B1C; Indicates the carrier phase at frequency B1C; This represents the carrier wavelength at frequency point B2a; This indicates the carrier phase at frequency B2a; Indicates the center frequency coefficient; This indicates the center frequency of the B1C frequency point; This indicates the center frequency of frequency point B2a; The dual-frequency point observations are statistically analyzed within a preset time window, and their standard deviation is calculated as an indicator of the multipath error intensity of the specified satellite in the current epoch. The multi-hop error is obtained by weighted averaging of all multipath error intensity indices within the current epoch.

7. A data quality inspection method based on BeiDou-3 satellites according to claim 6, characterized in that, The base station monitoring coefficient is calculated based on the observed signal-to-noise ratio (SNR), the preset base station SNR threshold, the number of cycle slips, and the multi-slip error. The calculation method is as follows: ； In the formula, Indicates the first The baseline station monitoring coefficient for each signal-to-noise ratio observation; Indicates the correction factor; Indicates the first proportionality coefficient; This represents the second proportionality coefficient; Indicates the third proportionality coefficient; Indicates the first One signal-to-noise ratio observation; This indicates the preset signal-to-noise ratio threshold for the base station; Indicates the number of cycle jumps; Indicates the total number of observed epochs; Indicates multi-hop error; If the monitoring coefficient of the base station is less than the threshold of the monitoring coefficient of the base station, the current signal-to-noise ratio observation value is deemed to be of acceptable quality. If the monitoring coefficient of the base station is greater than or equal to the threshold of the monitoring coefficient of the base station, the current signal-to-noise ratio observation value is deemed to be of unqualified quality and is discarded.

8. A data quality inspection system based on BeiDou-3 satellites, characterized in that, The system includes: The data acquisition module acquires the raw observation data received by the base station from the BeiDou-3 satellites; The data processing module parses the raw observation data to obtain observation files; it preprocesses the observation files to obtain the number of cycle slips and multi-slip error. If the acquired signal-to-noise ratio (SNR) observation value is greater than the preset base station SNR threshold, it indicates that the base station is operating abnormally and generates an operation and maintenance signal; otherwise, the base station monitoring coefficient is calculated based on the SNR observation value, the preset base station SNR threshold, the number of cycle slips, and the multi-slip error. Determine the relationship between the baseline station monitoring coefficient and the preset baseline station monitoring coefficient threshold, and obtain the data quality inspection results based on the determination results.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1 to 7.

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