Beidou GNSS (Global Navigation Satellite System) deformation monitoring method for whole network adjustment of multiple base stations and multiple observation stations

Abstract

The invention discloses a Beidou GNSS (Global Navigation Satellite System) deformation monitoring method for whole network adjustment of multiple base stations and multiple observation stations, which belongs to the technical field of satellite navigation and engineering safety monitoring and comprises the following steps: S1, constructing a Beidou GNSS base station-monitoring station networking architecture, collecting original observation values and finishing preprocessing; s2, constructing an observation equation based on a Beidou multi-frequency original observation value, and carrying out the combined calibration of a system error; s3, based on the non-combined original observation value, a step-by-step strategy is adopted to complete integer ambiguity resolving and fixing; s4, constructing a robust networking adjustment model with reference station rigid constraint and performing iterative solution; and S5, extracting the deformation of the monitoring station from the adjustment result, carrying out significance test, and outputting a monitoring result. By adopting the method, the Beidou multi-frequency signals are fully utilized, the ambiguity fixing rate and the adjustment precision are improved, millimeter-level deformation monitoring is realized, the engineering cost is reduced, and the reliability and the practicability are higher.

Description

Technical Field

[0001] This invention relates to the field of satellite navigation and engineering safety monitoring technology, and in particular to a BeiDou GNSS deformation monitoring method for multi-base station and multi-station network adjustment. Background Technology

[0002] GNSS (Global Navigation Satellite System) deformation monitoring is one of the core technologies for current engineering safety monitoring. The mainstream approach is based on BeiDou / GPS dual-frequency receivers, using synchronous observations from a base station and a monitoring station. It employs an IF (Ionosphere-Free) linear combination to eliminate ionospheric influences, and extracts coordinate changes at the monitoring station after baseline calculation and network adjustment to achieve deformation identification. Integer ambiguity resolution often uses a wide-lane / narrow-lane combination method, and the adjustment process often uses the classic least squares algorithm. System error correction mainly relies on empirical tropospheric / ionospheric models. With the completion of the BeiDou-3 global network, multi-frequency signals (B1I / B2I / B3I, B1C / B2a) provide a data foundation for high-precision deformation monitoring. However, existing technologies fail to fully utilize the advantages of BeiDou multi-frequency signals, exhibiting significant shortcomings in accuracy and reliability. Specifically, the ionosphere-free linear combination model easily amplifies observation noise, and system error correction is incomplete (ignoring the DCB (Differential Code Bias) between the satellite and receiver ends). Bias and phase deviation, poor adaptability to the BeiDou GEO (Geostationary Earth Orbit) / IGSO (Inclined Geosynchronous Orbit) / MEO (Medium Earth Orbit) hybrid constellation leads to low ambiguity fixation rate, insufficient robustness of network adjustment and weak resistance to gross errors, rapid accuracy decay over long distances, and high engineering application costs, making it difficult to meet the actual engineering needs of millimeter-level deformation monitoring. Summary of the Invention

[0003] The purpose of this invention is to provide a BeiDou GNSS deformation monitoring method with multi-base station and multi-station network adjustment, thereby solving the above-mentioned technical problems.

[0004] To achieve the above objectives, this invention provides a BeiDou GNSS deformation monitoring method with multi-base station and multi-station network adjustment, comprising the following steps: S1. Construct a BeiDou GNSS base station-monitoring station network architecture, collect raw observation values ​​and complete preprocessing; S2. Construct observation equations based on BeiDou multi-frequency raw observations and perform joint calibration of system errors; S3. Based on the non-combined original observations, a step-by-step strategy is adopted to complete the integer ambiguity resolution and fixation; S4. Construct a robust network adjustment model with rigid constraints from the base station and solve iteratively; S5. Extract the deformation of the monitoring station from the adjustment results, perform a significance test, and output the monitoring results.

[0005] Preferably, S1 specifically includes: S11. Deploy 3 or more base stations to form a fully connected network of base station sub-networks. The coordinates of the base stations adopt the CGCS2000 coordinate system and obtain millimeter-level known coordinates through static joint measurement. Deploy several monitoring stations, each of which has line of sight with at least 3 base stations. The distance from the monitoring station to the nearest base station is ≤25km. S12. All base stations and monitoring stations use BeiDou-3 tri-frequency receivers to synchronously collect raw pseudorange, carrier phase observations, satellite ephemeris and signal-to-noise ratio data at B1I, B2I and B3I frequencies. S13. Cycle slips are detected by combining MW combination and ionospheric residual combination. SNR weight constraint is introduced to reduce the weight of low-quality observations before detection. Polynomial fitting is used to repair the detected cycle slips. S14. Use the 3σ criterion and MAD method to remove outliers. First, calculate the median M and MAD of the observed value series, then remove outliers exceeding the range. The observed values, Scale factor; S15. Initialize the observation weight matrix, where the pseudorange observation weights are... and carrier phase observation weights They are respectively: ; ; in, The standard deviation of pseudorange observations. , The standard deviation of the carrier phase observations. , This is the pseudorange nominal observation noise. The nominal observation noise is the carrier phase. The nominal signal-to-noise ratio is... This is the measured signal-to-noise ratio.

[0006] Preferably, the baseline length between reference stations is ≤30km, and the BeiDou-3 tri-frequency receiver adopts continuous observation mode to collect observation data according to the preset sampling rate.

[0007] Preferably, S2 specifically includes: S21, For the measuring station ,satellite Frequency Construct the non-combined original observation equations, where the pseudorange observation equation and the carrier phase observation equation are respectively: ; ; in, , These are pseudorange and carrier phase observations, respectively. For the station To satellite geometric distance, The speed of light in a vacuum , These are receiver clock bias and satellite clock bias, respectively. For frequency point ionospheric slack delay, For tropospheric oblique delay, , These are the DCBs for the receiver and the satellite, respectively. , These are the phase deviations of the receiver and the satellite, respectively. For frequency point carrier wavelength, For carrier phase integer ambiguity, , These are the observation noises for pseudorange and carrier phase, respectively. S22. The Saastamoinen model is used to calculate the zenith static delay, which is then projected onto the oblique path through the VMF1 global mapping function. The zenith wet delay is included as a parameter to be estimated in the subsequent adjustment. S23. Pre-calibration using BeiDou satellite DCB products released by IGS Pre-calibration using IGS fractional period deviation products The DCB drift of BeiDou GEO satellites is estimated and corrected in real time using a sliding window. S24. Using one reference station in the reference station subnet as the reference station, and employing least squares adjustment with robust MAD estimation, solve for the values ​​of all reference stations using single-difference observations among the reference stations. and And it is applied to the correction of observations at monitoring stations; S25, Delay the ionosphere at the reference frequency B1I As a parameter to be estimated, ionospheric delay at other frequencies is passed through Conversion, among which, This is the B1I frequency point. For other frequency points.

[0008] Preferably, the pseudorange of the single-difference observation in the equation of single-difference observation between reference stations in S24 and single-difference carrier phase They are respectively: ; ; in, , Two base stations respectively , The single-difference pseudorange and single-difference carrier phase observations, for , To satellite The difference in geometric distance, for , The receiver clock error difference, for , The ionospheric oblique delay difference, for , The tropospheric oblique delay difference, for , DCB difference, for , The phase deviation difference, for , The carrier phase integer ambiguity difference, , These are the observation noises for single-difference pseudorange and single-difference carrier phase, respectively.

[0009] Preferably, in S24, when one reference station in the reference station subnet is used as the reference station, the DCB of the reference station is... and phase deviation All are set to 0.

[0010] Preferably, S3 specifically includes: S31. Perform inter-station-inter-satellite double difference on the reference station subnet. Combine the system error calibration results of S2 to solve the floating-point solution of double difference ambiguity. Reduce correlation through LAMBDA algorithm. Use ratio test to judge the fixation effectiveness. Fix MEO satellite ambiguity first, and then use it as a constraint to fix IGSO and GEO satellite ambiguity. S32. Using the fixed reference station subnet as a reference, construct the inter-station single-difference observation equation between the monitoring station and the reference station, and solve the floating-point solution of the non-difference ambiguity of the monitoring station. S33. Using an integer recovery clock model, combined with the fixed ambiguity of the base station, first fix the ambiguity of the B1I frequency point, and then fix the ambiguity of the B2I and B3I frequency points through the ionospheric ratio relationship between the frequency points. S34. For epochs where ambiguity fixation fails, a forward-backward smoothing method is adopted, utilizing the integer ambiguity characteristics of adjacent epochs to perform timing constraints.

[0011] Preferably, S4 specifically includes: S41. Construct the full parameter vector as follows: ; in, For the station The three-dimensional coordinates For receiver clock bias parameters, The ionospheric delay parameter at the reference frequency, This is the zenith wet delay parameter. S3 is a fixed integer ambiguity constant; S42. The Gauss-Markov error equation is constructed as follows: ; in, For the residual vector, To design the matrix, The constant term is the result of subtracting the known terms from the observed values. For parameter vectors; S43. Add rigid constraint equations for base station coordinates. The constrained normal equations are formed as follows: ; in, The coefficient matrix of the normal equations, , The vector of constant terms in the normal equation. , For designing a matrix The transpose of the matrix, The observation weight matrix is... The constraint coefficient matrix, For the relationship vector, For the coordinate parameter correction vector, For the constraint constant term vector; S44. The algorithm equations are iteratively solved using a combination of IGGIII robust weight functions and MAD outlier removal. The IGGIII weight function is set according to a preset threshold. Iteration converges after the unit weighted mean square error tends to stabilize. The covariance matrix of the parameters to be estimated ,in, For degrees of freedom, It is the inverse matrix of the normal equation.

[0012] Preferably, S5 specifically includes: S51. Using the adjusted coordinates of the initial epoch of the monitoring station as a reference, calculate the coordinates of each epoch. Three-dimensional deformation , , The three-dimensional deformation modulus value is obtained. for: ; ; ; ; in, , , The initial epoch three-dimensional coordinates, , , For the first Epochal three-dimensional coordinates; A sliding window Kalman filter was used to eliminate random noise in the deformation time series. S52, Adopting three-dimensional combination F The inspection specifically includes: S521. The original assumption was that the monitoring station did not experience significant deformation, and the deformation amount was 0. S522, Construction The test statistic is: ; in, The covariance matrix of the deformation The inverse matrix, Calculation based on the covariance matrix of the monitoring station coordinates obtained from adjustment; S523, when > At that time, the null hypothesis was rejected, and it was determined that significant three-dimensional deformation had occurred at the monitoring station. A third-order polynomial was used to fit the time series of significant deformation, and the fitting model was as follows: ; in, At the significance level, for F The critical value of the test, for F The first degree of freedom of the test, for F The second degree of freedom to be tested, The time-series fitted value of the three-dimensional deformation modulus of the monitoring station. For time, , , , These are the polynomial coefficients.

[0013] Preferably, the output monitoring results also include early warning information and a preset early warning threshold. When the deformation amount or deformation rate exceeds the early warning threshold, the early warning information is triggered and output.

[0014] Therefore, the present invention employs the above-mentioned method for monitoring BeiDou GNSS deformation through multi-base station and multi-station network adjustment, which has the following beneficial effects: 1. By constructing a collaborative networking architecture between BeiDou GNSS base stations and monitoring stations, the system errors of the satellite end and the receiver end can be accurately separated and calibrated.

[0015] 2. Combined with a step-by-step integer ambiguity resolution strategy for the BeiDou GEO / IGSO / MEO hybrid constellation and a robust network adjustment model with rigid constraints, it not only effectively avoids the problem of observation noise amplification, but also significantly improves the integrity of system error correction and the reliability of ambiguity fixation.

[0016] 3. It enhances the ability to resist gross errors and adapt to complex scenarios in network adjustment, and can still maintain millimeter-level monitoring accuracy in long baseline networks, significantly reducing the number of reference stations and lowering engineering construction and operation and maintenance costs.

[0017] 4. It realizes the integrated processing of the entire process from observation data preprocessing, error calibration, ambiguity resolution, adjustment calculation to deformation analysis and early warning, adapting to the static / dynamic deformation monitoring needs of various projects, and has the advantages of high precision, high reliability and strong practicality.

[0018] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0019] Figure 1 This is an overall flowchart of the BeiDou GNSS deformation monitoring method of the present invention; Figure 2 This is a schematic diagram of the base station-monitoring station networking architecture of the present invention; Figure 3 This is a block diagram illustrating the principle of joint calibration of system errors. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages disclosed in the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the embodiments of the present invention and are not intended to limit the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of this application. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout.

[0021] It should be noted that the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, such as a process, method, system, product, or server that includes a series of steps or units, not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such process, method, product, or device.

[0022] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0023] like Figures 1-3 As shown, the present invention provides a BeiDou GNSS deformation monitoring method for multi-base station and multi-station network adjustment, comprising the following steps: S1, constructing a BeiDou GNSS base station-monitoring station network architecture, collecting raw observation values ​​and completing preprocessing; S2, constructing observation equations based on BeiDou multi-frequency raw observation values, and jointly calibrating system errors; S3, based on non-combined raw observation values, using a step-by-step strategy to complete integer ambiguity resolution and fixation; S4, constructing a robust network adjustment model with rigid constraints of reference stations and iteratively solving it; S5, extracting the deformation of monitoring stations from the adjustment results, performing significance testing, and outputting the monitoring results.

[0024] Specifically, S11, first deploy 3 or more reference stations to form a fully connected mesh reference station subnet, with the baseline length between reference stations ≤30km. The reference station coordinates adopt the CGCS2000 coordinate system and obtain millimeter-level known coordinates through static joint measurement. At the same time, deploy several monitoring stations to ensure that each monitoring station has line of sight with at least 3 reference stations and the distance from the monitoring station to the nearest reference station is ≤25km; S12, after completing the BeiDou GNSS base station-monitoring station network architecture, use a BeiDou-3 tri-frequency receiver to continuously observe 24 hours a day at a sampling rate of 1Hz, and synchronously collect B1I data. S11: Raw pseudorange, carrier phase observations, satellite ephemeris, and signal-to-noise ratio data for B2I and B3I frequencies; S12: Preprocess the raw observations by first using a combination of MW and ionospheric residuals to detect cycle slips and then introducing SNR weight constraints to reduce the weight of low-quality observations before detection. Polynomial fitting is used to repair the detected cycle slips; S13: Outliers are then removed using a combination of the 3σ criterion and the MAD method. The median M and MAD of the observation sequence are calculated, and observations exceeding M ± MAD × 1.4826 are removed, where 1.4826 is the scale factor. Specific values; S15, Initialize the observation weight matrix, where the pseudorange observation weights and carrier phase observation weights They are respectively: ; ; in, The standard deviation of pseudorange observations. , The standard deviation of the carrier phase observations. , The pseudorange nominal observation noise is taken as 0.3m. The nominal observation noise for the carrier phase is taken as 0.003m. For the nominal signal-to-noise ratio, take 45dBHz. This is the measured signal-to-noise ratio.

[0025] S2 specifically includes: S21, for monitoring stations ,satellite Frequency Construct the non-combined original observation equations, where the pseudorange observation equation and the carrier phase observation equation are respectively: ; ; in, , These are pseudorange and carrier phase observations, respectively. For the station To satellite geometric distance, The speed of light in a vacuum , These are receiver clock bias and satellite clock bias, respectively. For frequency point ionospheric slack delay, For tropospheric oblique delay, , These are the DCBs for the receiver and the satellite, respectively. , These are the phase deviations of the receiver and the satellite, respectively. For frequency point carrier wavelength, For carrier phase integer ambiguity, , S22. Observation noise for pseudorange and carrier phase, respectively; S23. Joint calibration of system errors: First, the Saastamoinen model is used to calculate the zenith static delay, which is then projected onto the slant path using the VMF1 global mapping function, and the zenith wet delay is included as an estimated parameter in subsequent adjustment; S24. Pre-calibration is then performed using the BeiDou satellite DCB product released by IGS. Pre-calibration using IGS fractional period deviation products For BeiDou GEO satellites, a 24-hour sliding window is used to estimate and correct the DCB drift in real time; S24, taking one reference station in the reference station subnet as the reference station, the DCB of that reference station is... and phase deviation All values ​​are set to 0. Using single-difference observations between reference stations, least squares adjustment with robust MAD estimation is employed to solve for the values ​​at all reference stations. and It is also applied to the correction of observations at monitoring stations, including the pseudorange of the single difference in the equation of single difference observations between reference stations. and single-difference carrier phase They are respectively: ; ; in, , Two base stations respectively , The single-difference pseudorange and single-difference carrier phase observations, for , To satellite The difference in geometric distance, for , The receiver clock error difference, for , The ionospheric oblique delay difference, for , The tropospheric oblique delay difference, for , DCB difference, for , The phase deviation difference, for , The carrier phase integer ambiguity difference, , These are the observation noises for single-difference pseudorange and single-difference carrier phase, respectively; S25, the ionospheric delay of the reference frequency B1I. As a parameter to be estimated, ionospheric delay at other frequencies is passed through Conversion, among which, This is the B1I frequency point. For other frequency points.

[0026] S3 specifically includes: S31, based on the non-combined original observations, a step-by-step strategy is adopted for the BeiDou GEO / IGSO / MEO hybrid constellation to complete the integer ambiguity resolution and fixation. First, inter-station-inter-satellite double difference is performed on the reference station subnet. Combined with the system error calibration results, the double difference ambiguity floating-point solution is calculated. After reducing correlation using the LAMBDA algorithm, the fixation effectiveness is judged by ratio test with a ratio test threshold of 3.0. The MEO satellite ambiguity is fixed first, and then the IGSO and GEO satellite ambiguities are fixed using it as a constraint; S32, with the fixed Using the established reference station subnet as a benchmark, an inter-station single-difference observation equation between the monitoring station and the reference station is constructed, and the floating-point solution of the non-difference ambiguity of the monitoring station is solved; S33, then an integer recovery clock model is used, and the ambiguity of the B1I frequency point is fixed first, combined with the fixed ambiguity of the reference station, and then the ambiguity of the B2I and B3I frequency points is fixed through the ionospheric ratio relationship between the frequency points; S34, finally, for epochs where ambiguity fixation fails, a forward-backward smoothing method is used, and the integer characteristics of ambiguity in adjacent epochs are used as temporal constraints to ensure that the ambiguity fixation rate of consecutive epochs is ≥98%; S4 specifically includes: S41, constructing the full parameter vector as follows: ; in, For the station The three-dimensional coordinates For receiver clock bias parameters, The ionospheric delay parameter at the reference frequency, This is the zenith wet delay parameter. S3 is a fixed integer ambiguity constant; S42, construct the Gauss-Markov error equation as follows: ; in, For the residual vector, To design the matrix, The constant term is the result of subtracting the known terms from the observed values. For parameter vectors; S43, add rigid constraint equations for base station coordinates. By incorporating the engineering constraints of the base station's stability into the adjustment solution, the constrained normal equations are formed as follows: ; in, The coefficient matrix of the normal equations, , The vector of constant terms in the normal equation. , For designing a matrix The transpose of the matrix, The observation weight matrix is... The constraint coefficient matrix, For the relationship vector, This is a vector of coordinate parameter corrections, with the base station coordinate correction being 0. To constrain the constant term vector; S44, set a preset threshold for the IGGIII weight function, and iterate until convergence occurs when the change in unit weight error is less than 0.1 mm, and the unit weight error... The covariance matrix of the parameters to be estimated ,in, For degrees of freedom, It is the inverse matrix of the normal equation.

[0027] S5 specifically includes: S51, using the adjusted coordinates of the initial epoch of the monitoring station as a reference, calculating the values ​​for each epoch. Three-dimensional deformation , , The three-dimensional deformation modulus value is obtained. for: ; ; ; ; in, , , The initial epoch three-dimensional coordinates, , , For the first Epochal 3D coordinates; a 10-epoch sliding window Kalman filter is used to eliminate random noise in the deformation time series; S52, 3D joint... FThe verification specifically includes: S521, the null hypothesis is that the monitoring station did not undergo significant deformation, and the deformation amount is 0; S522, constructing... The test statistic is: ; in, The covariance matrix of the deformation The inverse matrix, Calculation of the covariance matrix of the monitoring station coordinates obtained from adjustment; S523, when > At that time, the null hypothesis was rejected, and it was determined that significant three-dimensional deformation had occurred at the monitoring station. A third-order polynomial was used to fit the time series of significant deformation, and the fitting model was as follows: ; in, At the significance level, for F The critical value of the test, for F The first degree of freedom of the test, for F The second degree of freedom to be tested, The time-series fitted value of the three-dimensional deformation modulus of the monitoring station. For time, , , , Let be the polynomial coefficients, and take . It is 0.05, that is > When the null hypothesis is rejected, the output monitoring results also include early warning information. A preset early warning threshold is set, and when the deformation amount or deformation rate exceeds the early warning threshold, an early warning information is triggered and output.

[0028] This invention, through the aforementioned method, abandons the traditional linear combination model without ionosphere, fully leverages the advantages of BeiDou multi-frequency signals, effectively avoids the problem of observation noise amplification, and controls system errors to an extremely low range. The coordinate calculation accuracy of monitoring stations reaches ±1mm for plane and ±2mm for elevation. At the same time, it improves the ambiguity fixation rate under the BeiDou hybrid constellation to over 98%, enhances the resistance to gross errors and environmental adaptability of network adjustment, and can still maintain millimeter-level monitoring accuracy under a 30km long baseline network. It can reduce the number of reference stations by 30% to 50%, significantly reducing engineering construction and operation and maintenance costs. Moreover, it realizes the integrated processing of the entire process of network preprocessing, error calibration, ambiguity calculation, adjustment calculation, deformation analysis and early warning. It is suitable for static / dynamic deformation monitoring of various projects such as dams, bridges, and slopes, and has high engineering practicality and automation.

[0029] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for monitoring deformation of BeiDou GNSS systems through multi-base station and multi-station network adjustment, characterized in that, Includes the following steps: S1. Construct a BeiDou GNSS base station-monitoring station network architecture, collect raw observation values ​​and complete preprocessing; S2. Construct observation equations based on BeiDou multi-frequency raw observations and perform joint calibration of system errors; S3. Based on the non-combined original observations, a step-by-step strategy is adopted to complete the integer ambiguity resolution and fixation; S4. Construct a robust network adjustment model with rigid constraints from the base station and solve iteratively; S5. Extract the deformation of the monitoring station from the adjustment results, perform a significance test, and output the monitoring results.

2. The BeiDou GNSS deformation monitoring method for multi-base station and multi-station network adjustment according to claim 1, characterized in that, S1 specifically includes: S11. Deploy 3 or more base stations to form a fully connected network of base station sub-networks. The coordinates of the base stations adopt the CGCS2000 coordinate system and obtain millimeter-level known coordinates through static joint measurement. Deploy several monitoring stations, each of which has line of sight with at least 3 base stations. The distance from the monitoring station to the nearest base station is ≤25km. S12. All base stations and monitoring stations use BeiDou-3 tri-frequency receivers to synchronously collect raw pseudorange, carrier phase observations, satellite ephemeris and signal-to-noise ratio data at B1I, B2I and B3I frequencies. S13. Cycle slips are detected by combining MW combination and ionospheric residual combination. SNR weight constraint is introduced to reduce the weight of low-quality observations before detection. Polynomial fitting is used to repair the detected cycle slips. S14. Use the 3σ criterion and MAD method to remove outliers. First, calculate the median M and MAD of the observed value series, then remove outliers exceeding the range. The observed values, Scale factor; S15. Initialize the observation weight matrix, where the pseudorange observation weights are... and carrier phase observation weights They are respectively: ； ； in, The standard deviation of pseudorange observations. , The standard deviation of the carrier phase observations. , This is the pseudorange nominal observation noise. The nominal observation noise is the carrier phase. The nominal signal-to-noise ratio is... This is the measured signal-to-noise ratio.

3. The BeiDou GNSS deformation monitoring method for multi-base station and multi-station network adjustment according to claim 2, characterized in that: The baseline length between the reference stations is ≤30km. The BeiDou-3 tri-frequency receiver adopts continuous observation mode and collects observation data according to the preset sampling rate.

4. The BeiDou GNSS deformation monitoring method for multi-base station and multi-station network adjustment according to claim 3, characterized in that, S2 specifically includes: S21, For the measuring station ,satellite Frequency Construct the non-combined original observation equations, where the pseudorange observation equation and the carrier phase observation equation are respectively: ； ； in, , These are pseudorange and carrier phase observations, respectively. For the station To satellite geometric distance, The speed of light in a vacuum , These are receiver clock bias and satellite clock bias, respectively. For frequency point ionospheric slack delay, For tropospheric oblique delay, , These are the DCBs for the receiver and the satellite, respectively. , These are the phase deviations of the receiver and the satellite, respectively. For frequency point carrier wavelength, For carrier phase integer ambiguity, , These are the observation noises for pseudorange and carrier phase, respectively. S22. The Saastamoinen model is used to calculate the zenith static delay, which is then projected onto the oblique path through the VMF1 global mapping function. The zenith wet delay is included as a parameter to be estimated in the subsequent adjustment. S23. Pre-calibration using BeiDou satellite DCB products released by IGS Pre-calibration using IGS fractional period deviation products The DCB drift of BeiDou GEO satellites is estimated and corrected in real time using a sliding window. S24. Using one reference station in the reference station subnet as the reference station, and employing least squares adjustment with robust MAD estimation, solve for the values ​​of all reference stations using single-difference observations among the reference stations. and And it is applied to the correction of observations at monitoring stations; S25, Delay the ionosphere at the reference frequency B1I As a parameter to be estimated, ionospheric delay at other frequencies is passed through Conversion, among which, This is the B1I frequency point. For other frequency points.

5. The BeiDou GNSS deformation monitoring method for multi-base station and multi-station network adjustment according to claim 4, characterized in that: The pseudorange of the single difference observation in the inter-base station single difference observation equation in S24 and single-difference carrier phase They are respectively: ； ； in, , Two base stations respectively , The single-difference pseudorange and single-difference carrier phase observations, for , To satellite The difference in geometric distance, for , The receiver clock error difference, for , The ionospheric oblique delay difference, for , The tropospheric oblique delay difference, for , DCB difference, for , The phase deviation difference, for , The carrier phase integer ambiguity difference, , These are the observation noises for single-difference pseudorange and single-difference carrier phase, respectively.

6. The BeiDou GNSS deformation monitoring method for multi-base station and multi-station network adjustment according to claim 5, characterized in that: In S24, when one reference station in the reference station subnet is used as the reference station, the DCB of that reference station is... and phase deviation All are set to 0.

7. The BeiDou GNSS deformation monitoring method for multi-base station and multi-station network adjustment according to claim 6, characterized in that, S3 specifically includes: S31. Perform inter-station-inter-satellite double difference on the reference station subnet. Combine the system error calibration results of S2 to solve the floating-point solution of double difference ambiguity. Reduce correlation through LAMBDA algorithm. Use ratio test to judge the fixation effectiveness. Fix MEO satellite ambiguity first, and then use it as a constraint to fix IGSO and GEO satellite ambiguity. S32. Using the fixed reference station subnet as a reference, construct the inter-station single-difference observation equation between the monitoring station and the reference station, and solve the floating-point solution of the non-difference ambiguity of the monitoring station. S33. Using an integer recovery clock model, combined with the fixed ambiguity of the base station, first fix the ambiguity of the B1I frequency point, and then fix the ambiguity of the B2I and B3I frequency points through the ionospheric ratio relationship between the frequency points. S34. For epochs where ambiguity fixation fails, a forward-backward smoothing method is adopted, utilizing the integer ambiguity characteristics of adjacent epochs to perform timing constraints.

8. The BeiDou GNSS deformation monitoring method for multi-base station and multi-station network adjustment according to claim 7, characterized in that, S4 specifically includes: S41. Construct the full parameter vector as follows: ； in, For the station The three-dimensional coordinates For receiver clock bias parameters, The ionospheric delay parameter at the reference frequency, This is the zenith wet delay parameter. S3 is a fixed integer ambiguity constant; S42. The Gauss-Markov error equation is constructed as follows: ； in, For the residual vector, To design the matrix, The constant term is the result of subtracting the known terms from the observed values. For parameter vectors; S43. Add rigid constraint equations for base station coordinates. The constrained normal equations are formed as follows: ； in, The coefficient matrix of the normal equations, , The vector of constant terms in the normal equation. , For designing a matrix The transpose of the matrix, The observation weight matrix is... The constraint coefficient matrix, For the relationship vector, For the coordinate parameter correction vector, For the constraint constant term vector; S44. The algorithm equations are iteratively solved using a combination of IGGIII robust weight functions and MAD outlier removal. The IGGIII weight function is set according to a preset threshold. Iteration converges after the unit weighted mean square error tends to stabilize. The covariance matrix of the parameters to be estimated ,in, For degrees of freedom, It is the inverse matrix of the normal equation.

9. The BeiDou GNSS deformation monitoring method for multi-base station and multi-station network adjustment according to claim 8, characterized in that, S5 specifically includes: S51. Using the adjusted coordinates of the initial epoch of the monitoring station as a reference, calculate the coordinates of each epoch. Three-dimensional deformation , , The three-dimensional deformation modulus value is obtained. for: ； ； ； ； in, , , The initial epoch three-dimensional coordinates, , , For the first Epochal three-dimensional coordinates; A sliding window Kalman filter was used to eliminate random noise in the deformation time series. S52, Adopting three-dimensional combination F The inspection specifically includes: S521. The original assumption was that the monitoring station did not experience significant deformation, and the deformation amount was 0. S522, Construction The test statistic is: ； in, The covariance matrix of the deformation The inverse matrix, Calculation based on the covariance matrix of the monitoring station coordinates obtained from adjustment; S523, when > At that time, the null hypothesis was rejected, and it was determined that significant three-dimensional deformation had occurred at the monitoring station. A third-order polynomial was used to fit the time series of significant deformation, and the fitting model was as follows: ； in, At the significance level, for F The critical value of the test, for F The first degree of freedom of the test, for F The second degree of freedom to be tested, The time-series fitted value of the three-dimensional deformation modulus of the monitoring station. For time, , , , These are the polynomial coefficients.

10. The BeiDou GNSS deformation monitoring method for multi-base station and multi-station network adjustment according to claim 9, characterized in that: The output monitoring results also include early warning information and preset early warning thresholds. When the deformation amount or deformation rate exceeds the early warning threshold, the early warning information is triggered and output.

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