A RT-PPP / RTK fusion GNSS deformation monitoring method and system based on spatial reference dynamic unification, electronic equipment and storage medium

Abstract

The application discloses a kind of RT-PPP / RTK fusion GNSS deformation monitoring methods based on space reference dynamic unification, comprising the following steps: RTK resolving coordinates of monitoring station are epoch reduction and reference frame conversion, obtain the conversion coordinates under the same ITRF reference frame and reference epoch of RT-PPP, and RT-PPP positioning is solved with conversion coordinates as constraint, obtain the RT-PPP positioning resolving coordinates of monitoring station, RT-PPP coordinate variance information and RT-PPP resolving state information;According to the resolving state information corresponding to conversion coordinates and RT-PPP positioning resolving coordinates, optimal result is dynamically output using hierarchical decision mechanism.This application unifies coordinate reference to ITRF2020 observation epoch, eliminates the reference deviation of isomorphism data fusion.On the other hand, RT-PPP is constrained by RTK in real time, multi-modal positioning information is fused using hierarchical decision mechanism, optimal positioning data is automatically switched, and positioning accuracy and reliability are doubled improved.The application also discloses a system, electronic equipment and computer readable storage medium for implementing the above method.

Description

Technical Field

[0001] This invention relates to the field of BeiDou / GNSS positioning data processing technology, and in particular to a method, system, electronic device and storage medium for RT-PPP / RTK fusion GNSS deformation monitoring based on dynamic unification of spatial reference. Background Technology

[0002] Real-Time Precise Point Positioning (RT-PPP) is based on a non-differential observation model and relies on real-time precise orbit and clock error products provided by the International GNSS Service (IGS) and its Analysis Centers (ACs) to achieve high-precision real-time positioning of a single GNSS receiver over a wide area. Its spatial reference inherits the reference frame version and epoch of the precise ephemeris published by IGS; that is, the reference frame is ITRF2020, and the epoch is the observation epoch.

[0003] Real-time carrier phase dynamic differential (RTK) is based on a dual-difference observation model. Through collaborative observations between the base station and the rover, a carrier phase dual-difference observation equation is constructed to eliminate common errors, achieving real-time positioning with centimeter-level accuracy under short baseline conditions (typically ≤20 km). Since the known reference coordinates of the base station serve as the reference for differential correction, the spatial reference of the rover's RTK positioning solution directly inherits the reference frame and epoch attributes of the base station.

[0004] Ephemeris reduction and frame transformation are practical methods for achieving spatial benchmark unification in GNSS high-precision positioning. In GNSS deformation monitoring scenarios, they jointly address the positional deviations caused by tectonic plate movement and differences in reference frame versions. Ephemeris reduction is the process of correcting coordinates from different observation epochs to a unified reference epoch, or from different reference epochs to the observation epoch, based on a velocity field model, to eliminate coordinate offsets caused by tectonic plate movement. Frame transformation converts coordinates from one reference frame (such as ITRF2014) to another (such as ITRF2020), eliminating version differences and achieving frame benchmark unification for GNSS coordinates. Together, they construct a unified spatial benchmark system from epoch alignment to frame matching, providing reliable benchmark support for high-precision spatial data analysis.

[0005] Furthermore, while RT-PPP and RTK, the two core high-precision positioning technologies, each have their advantages, they both suffer from significant technical bottlenecks. Although RT-PPP boasts wide-area coverage, its relatively long convergence time (typically around 30 minutes) severely restricts applications with high real-time requirements and relies on the timeliness of precise ephemeris and satellite clock bias products. RTK, while capable of instantaneous centimeter-level positioning, is limited by short baseline distance requirements (generally no more than 10 kilometers) and depends on a dense network of reference stations and a stable two-way communication link. More critically, the coordinate space references used for positioning calculations by the two technologies are inconsistent, leading to deviations in positioning results. Moreover, the reliability of positioning calculations from a single technology has not been fully verified, directly impacting the credibility of monitoring results and the basis for decision-making. Summary of the Invention

[0006] To address the aforementioned problems in the existing technology, this invention provides a method, system, electronic device, and storage medium for RT-PPP / RTK fusion GNSS deformation monitoring based on dynamic unification of spatial reference. The technical problem to be solved by this invention is achieved through the following technical solution: The first aspect of this invention provides a method for RT-PPP / RTK fusion GNSS deformation monitoring based on dynamic unification of a spatial reference, comprising the following steps: The RTK solution coordinates of the monitoring station are reduced to epochs and the reference frame is transformed to obtain transformed coordinates under the same ITRF reference frame and reference epoch as RT-PPP. Based on the observation data of the monitoring station and the real-time precise orbit and satellite clock error correction product, and using the transformed coordinates as constraints, RT-PPP positioning calculation is performed to obtain the RT-PPP positioning calculation coordinates, RT-PPP coordinate variance information and RT-PPP calculation status information of the monitoring station. When the solution status information corresponding to the transformed coordinates and the RT-PPP positioning solution coordinates are both fixed ambiguity solutions, the transformed coordinates and the RT-PPP positioning solution coordinates are weighted and calculated based on the RTK coordinate variance information and the RT-PPP coordinate variance information to obtain the monitoring and positioning result; When the solution status information of the transformed coordinates is a fixed ambiguity solution, and the solution status information corresponding to the RT-PPP positioning solution coordinates is a floating ambiguity solution, the transformed coordinates are used as the monitoring positioning result. When the solution status information of the transformed coordinates is an ambiguity floating-point solution, and the solution status information corresponding to the RT-PPP positioning solution coordinates is an ambiguity floating-point solution, if the RT-PPP positioning solution coordinates have converged, then the RT-PPP positioning solution coordinates are used as the monitoring positioning result; otherwise, the transformed coordinates are used as the monitoring positioning result.

[0007] In one embodiment of the present invention, the step of performing epoch reduction and reference frame transformation on the RTK solution coordinates of the monitoring station to obtain transformed coordinates under the same ITRF reference frame and reference epoch as RT-PPP includes: The reference coordinates of the base station are calculated based on the observation data of the base station and the preset accuracy, and the ITRF reference frame and reference epoch information are obtained. Based on the reference coordinates, observation data and broadcast ephemeris of the base station, and observation data and broadcast ephemeris of the monitoring station, short baseline RTK calculation is performed to determine the RTK calculation coordinates, RTK coordinate variance information, RTK calculation status information and RTK spatial reference information of the monitoring station. Based on the RTK solution coordinates, the RTK spatial reference information, the ITRF reference frame, and the reference epoch information, the RTK solution coordinates are subjected to epoch reduction and reference frame transformation to obtain transformed coordinates under the same ITRF reference frame and reference epoch as RT-PPP.

[0008] In one embodiment of the present invention, the step of performing RT-PPP positioning calculation based on the observation data of the monitoring station and the real-time precise orbit and satellite clock error correction product, and using the transformed coordinates as constraints, to obtain the RT-PPP positioning calculation coordinates, RT-PPP coordinate variance information, and RT-PPP calculation status information of the monitoring station includes: The IF combined observation equation of RT-PPP is corrected and linearized based on real-time precise orbit and satellite clock error products, and the IF combined function model is obtained. Based on the IF combination function model and using the transformed coordinates as constraints for the IF combination error equation of RT-PPP, the IF combination error equation is solved to obtain the RT-PPP positioning solution coordinates, RT-PPP coordinate variance information, and RT-PPP solution status information of the monitoring station.

[0009] In one embodiment of the present invention, the IF combined observation equation is: in, Indicates the geometric distance between the monitoring station and the satellite. Indicates the tropospheric delay of the oblique path. Indicates satellite, Indicates a monitoring station. Indicates the clock difference at the monitoring station. Indicates satellite clock bias, This indicates the pseudorange hardware delay of the monitoring station for the IF combination. This represents the pseudorange hardware delay of the IF-combined satellites. This indicates the phase hardware delay of the monitoring station for the IF combination. This indicates the phase hardware delay of the satellites in the IF combination. Indicates the floating-point ambiguity of the IF combination. Indicates the combined wavelength of IF. This represents the sum of noise, multipath effects, and unmodeled errors in the pseudorange IF combined observations of the monitoring station. This represents the sum of noise, multipath effects, and unmodeled errors in the combined phase IF observations of the satellite.

[0010] In one embodiment of the present invention, the IF combination function model is as follows: in, OMC represents the pseudo-range IF combination. OMC representing the phase IF combination, This represents the vector from the satellite to the monitoring station. Indicates the coordinates calculated by RT-PPP positioning. This indicates that the clock bias parameters of the monitoring station have been absorbed from the UCD at the monitoring station. This indicates that the ambiguity parameters of UCD and UPD have been incorporated. Indicates monitoring station The zenith tropospheric delay, express At the monitoring station and satellite The projection coefficients on the oblique path.

[0011] In one embodiment of the present invention, the IF combination error equation is: in, in, Indicates the transformed coordinates, , Indicates the coordinates calculated by RT-PPP positioning. ， The vector matrix representing the distance from the satellite to the monitoring station. This is the tropospheric wet delay projection function. It is an identity matrix.

[0012] In one embodiment of the present invention, the step of performing epoch reduction and reference frame transformation on the RTK solution coordinates based on the RTK solution coordinates, the RTK spatial reference information, the ITRF reference frame, and the reference epoch information to obtain transformed coordinates under the same ITRF reference frame and reference epoch as RT-PPP includes: The movement speed of the monitoring station is determined based on the RTK-calculated coordinates and the micro-block Euler vector model. Based on the RTK calculated coordinates, the reference epoch, the motion velocity, and the observation epoch, the observation epoch is reduced to obtain the reduced coordinates; Based on the Helmert model and the reduced coordinates, the ITRF reference frame of the reduced coordinates is transformed to the same ITRF reference frame as RT-PPP to obtain the transformed coordinates.

[0013] A second aspect of this invention provides a dynamic unified RT-PPP / RTK fusion GNSS deformation monitoring system based on a spatial reference, comprising: The conversion module is used to perform epoch reduction and reference frame conversion on the RTK solution coordinates of the monitoring station to obtain the converted coordinates under the same ITRF reference frame and reference epoch as RT-PPP. The calculation module is used to perform RT-PPP positioning calculation based on the observation data of the monitoring station and the real-time precise orbit and satellite clock error correction product, and with the transformed coordinates as constraints, to obtain the RT-PPP positioning calculation coordinates, RT-PPP coordinate variance information and RT-PPP calculation status information of the monitoring station. The output module is used to perform a weighted calculation on the transformed coordinates and the RT-PPP positioning solution coordinates based on the RTK coordinate variance information and the RT-PPP coordinate variance information when the solution status information corresponding to the transformed coordinates and the RT-PPP positioning solution coordinates are both fixed ambiguity solutions, and to use this as the monitoring and positioning result. The output module is also used to use the transformed coordinates as the monitoring and positioning result when the solution status information of the transformed coordinates is a fixed ambiguity solution and the solution status information corresponding to the RT-PPP positioning solution coordinates is a floating ambiguity solution; The output module is further configured to, when the solution status information of the transformed coordinates is an ambiguity floating-point solution and the solution status information corresponding to the RT-PPP positioning solution coordinates is an ambiguity floating-point solution, if the RT-PPP positioning solution coordinates have converged, then use the RT-PPP positioning solution coordinates as the monitoring positioning result; otherwise, use the transformed coordinates as the monitoring positioning result.

[0014] A third aspect of the present invention 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 the RT-PPP / RTK fusion GNSS deformation monitoring method based on dynamic unification of spatial reference provided in the first aspect of the present invention.

[0015] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements a method for RT-PPP / RTK fusion GNSS deformation monitoring based on dynamic unification of a spatial reference, as provided in the first aspect of the present invention.

[0016] The beneficial effects of this invention are: This invention, on the one hand, unifies the coordinate reference to the ITRF2020 observation epoch through reference epoch reduction and reference frame transformation, reducing systematic bias from sub-meter to millimeter level, eliminating reference bias caused by the fusion of heterogeneous data from the same source, and achieving dynamic unification of the spatial reference for multimodal coordinates. On the other hand, it accelerates the fixation of ambiguities and the convergence of static RT-PPP by using RTK in real time, achieving a dual improvement in positioning accuracy and reliability. Furthermore, it employs a hierarchical decision-making mechanism to fuse multimodal positioning information, automatically switching to the optimal positioning data to avoid error accumulation caused by the failure of a single positioning mode.

[0017] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings.

[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] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 A flowchart illustrating a method for RT-PPP / RTK fusion GNSS deformation monitoring based on dynamic unification of spatial reference, provided in an embodiment of the present invention; Figure 2 This is a block diagram of a fusion RT-PPP / RTK GNSS deformation monitoring system based on dynamic unification of spatial reference, provided for an embodiment of the present invention. Detailed Implementation

[0020] The present invention will be further described in detail below with reference to specific embodiments, but the implementation of the present invention is not limited thereto.

[0021] like Figure 1 As shown, the first aspect of this invention provides a method for RT-PPP / RTK fusion GNSS deformation monitoring based on dynamic unification of spatial reference, comprising the following steps: Step 11: Perform epoch reduction and reference frame transformation on the RTK solution coordinates of the monitoring station to obtain transformed coordinates under the same ITRF reference frame and reference epoch as RT-PPP.

[0022] Step 12: Based on the observation data of the monitoring station and the real-time precise orbit and satellite clock error correction product, and with the transformed coordinates as constraints, perform RT-PPP positioning calculation to obtain the RT-PPP positioning calculation coordinates, RT-PPP coordinate variance information and RT-PPP calculation status information of the monitoring station.

[0023] Step 13: When the solution status information corresponding to the transformed coordinates and the RT-PPP positioning solution coordinates are both fixed ambiguity solutions, the transformed coordinates and the RT-PPP positioning solution coordinates are weighted and calculated based on the RTK coordinate variance information and the RT-PPP coordinate variance information, and used as the monitoring and positioning result.

[0024] Step 14: When the solution status information of the transformed coordinates is a fixed ambiguity solution, and the solution status information corresponding to the RT-PPP positioning solution coordinates is a floating ambiguity solution, the transformed coordinates are used as the monitoring positioning result.

[0025] Step 15: When the solution status information of the transformed coordinates is an ambiguity floating-point solution, and the solution status information corresponding to the RT-PPP positioning solution coordinates is an ambiguity floating-point solution, if the RT-PPP positioning solution coordinates have converged, then the RT-PPP positioning solution coordinates are used as the monitoring positioning result; otherwise, the transformed coordinates are used as the monitoring positioning result.

[0026] In this embodiment, by reducing the reference epoch and transforming the reference frame, the coordinate reference is unified to the ITRF2020 observation epoch. The systematic deviation is reduced from the sub-meter level to the millimeter level, eliminating the reference deviation caused by the fusion of heterogeneous data from the same source, and realizing the dynamic unification of the spatial reference of multimodal coordinates. On the other hand, by using RTK to constrain RT-PPP in real time, the fixation speed of ambiguity is accelerated, and the convergence of static RT-PPP is accelerated, achieving a dual improvement in positioning accuracy and reliability. In addition, a hierarchical decision-making mechanism is adopted to fuse multimodal positioning information and automatically switch the optimal positioning data to avoid error accumulation caused by the failure of a single positioning mode.

[0027] This invention performs epoch reduction and frame transformation on two sets of coordinates calculated separately by RT-PPP and RTK, unifying the coordinates to the ITRF2020 frame and observation epoch. This eliminates the benchmark bias caused by fusing heterogeneous data from the same source, achieving dynamic unification of the spatial benchmark for multimodal coordinates. This invention introduces high-precision RTK position constraints and a multimodal adaptive fusion algorithm. By constructing a hierarchical decision model based on the positioning solution status and variance statistics, it dynamically and weightedly fuses the RT-PPP and RTK solution results, achieving a dual improvement in positioning accuracy and reliability compared to traditional techniques.

[0028] Based on the first aspect of the present invention, the second aspect of the present invention provides a more detailed description of an RT-PPP / RTK fused GNSS deformation monitoring method based on dynamic unification of a spatial reference. The second aspect of the present invention provides an RT-PPP / RTK fused GNSS deformation monitoring method based on dynamic unification of a spatial reference, comprising the following steps: Step 21: Calculate the reference coordinates of the base station based on the observation data and preset accuracy, and obtain the ITRF reference frame and reference epoch information.

[0029] In this step, observation data from the base station terminal is collected. If the required accuracy is at the millimeter level, the reference coordinates of the base station are obtained using the GAMIT periodic solution; if the required accuracy is at the centimeter level, the reference coordinates of the base station are obtained based on the post-hoc static solution of PPP. Simultaneously, the ITRF reference frame and reference epoch information for the reference coordinates are acquired.

[0030] Step 22: Based on the reference coordinates, observation data and broadcast ephemeris from the base station, and observation data and broadcast ephemeris from the monitoring station, perform short-baseline RTK calculations to determine the RTK calculation coordinates, RTK coordinate variance information, RTK calculation status information, and RTK spatial reference information of the monitoring station. Short-baseline RTK is typically a baseline less than 10 km long.

[0031] Step 22 includes steps 221-224: Step 221, obtain the RTK double-difference observation equation as follows: , They are reference stars and non-reference stars, respectively. , , These represent the monitoring station, the reference station, and the signal frequency, respectively. This represents the double-difference geometric distance between the receiver (reference station and monitoring station) and the satellite (reference satellite and non-reference satellite); The double-difference tropospheric delay indicates the oblique path; Indicates the double-difference ionospheric delay of the slant path; For signal frequency carrier wavelength; The ambiguity is a double-difference integer ambiguity. and These represent pseudorange measurement error and carrier phase measurement error, respectively.

[0032] In addition, GNSS observations are also affected by other error sources, such as relativistic effects, tidal effects, phase entanglement, antenna phase center changes, and antenna phase center offsets. These error terms can be accurately corrected using existing models. Here, it is assumed that all of the above error terms have been corrected.

[0033] Under short baseline conditions, the spatial correlation of the double-difference observation model is strong, and the ionospheric and tropospheric delays are strongly correlated. Most common errors can be eliminated through double-difference observations between stations (reference station and monitoring station) and between satellites (reference satellite and non-reference satellite). The tropospheric delay is almost completely eliminated after double-difference due to the small elevation difference between the two stations. In short baseline conditions, the residual ionospheric error after double-difference is extremely small, and it can be further weakened, especially in dual-frequency observations, through ionospheric-free combinations.

[0034] Step 222: Linearize the RTK double-difference observation equation to obtain the RTK function model, which can be expressed as: in, The OMC (Observed Minus Computed) value is obtained by subtracting the calculated value from the pseudorange observation value. The OMC is obtained by subtracting the calculated value from the phase observation value; Indicates satellite Vector and satellite to receiver (monitoring station) The difference in vectors to the receiver (monitoring station), This represents the coordinates to be estimated, which are also the RTK calculated coordinates of the monitoring station. .

[0035] Step 223, construct the RTK error equation: in, , It is an identity matrix.

[0036] Step 224: Solve the RTK error equation using Kalman filtering to obtain the RTK coordinates of the monitoring station. RTK coordinate variance information, RTK solution status information, and RTK spatial reference information.

[0037] Step 23: Based on the RTK solution coordinates, RTK spatial reference information, ITRF reference frame, and reference epoch information, perform epoch reduction and reference frame transformation on the RTK solution coordinates to obtain transformed coordinates under the same ITRF reference frame and the same reference epoch as RT-PPP.

[0038] In this step, the reference epoch is reduced to the dynamic epoch of the observation time, and the reference frame is converted to be consistent with the latest ITRF version to strictly align the RT-PPP spatial reference.

[0039] Step 23 includes steps 231-233: Step 231: Determine the movement speed of the monitoring station based on the RTK-calculated coordinates and the Eulerian vector model of the micro-block.

[0040] Here, based on high-precision RTK coordinate calculation, a micro-bulk Euler vector model is used to calculate the crustal movement velocity: First, calculate the monitoring station With all reference stations (total) (one) European distance The Euclidean distance is calculated as follows: Here, using replace To simplify the formula. Indicates the first The coordinates of each reference station.

[0041] Secondly, filter out the nearest neighbors. Each reference station is considered to have an index from 1 to... .

[0042] Next, the observation equations are constructed. . Speed ​​of each reference station As observation vector .

[0043] in, Then, the Euler vector is solved using the least squares method. ; Finally, the velocity of the monitoring station was calculated based on the Euler vector. .

[0044] Step 232: Based on the RTK-calculated coordinates, reference epoch, motion velocity, and observation epoch, perform observation epoch reduction to obtain the reduced coordinates.

[0045] In this step, the calculated velocity and epoch of the monitoring station are reduced to the observation epoch to eliminate positional deviations caused by plate tectonics. The calculation formula is as follows: in, Represents the reduced coordinates after epoch reduction; It represents the time difference between the reference epoch and the observed epoch.

[0046] Step 233: Based on the Helmert model and the reduced coordinates, transform the ITRF reference frame of the reduced coordinates to the same ITRF reference frame as RT-PPP to obtain the transformed coordinates.

[0047] In this step, based on the Helmert model, the ITRF of the reduced coordinates is transformed to an RT-PPP aligned version to eliminate systematic positional bias caused by frame differences.

[0048] The Helmert model is as follows: Wherein, the parameter varies with time The change is corrected by the rate term: In the formula, Indicates the transformed coordinates after the frame transformation; , and These represent the translation parameters in three directions (unit: meters). , , Indicates the corresponding rate; , , Represents rotation parameters in three directions (unit: meters). , , Indicates the corresponding rate; Represents the scale factor (dimensionless). Its rate of change; This serves as the reference epoch for the ITRF transformation parameters. The dynamic epoch (observation epoch) is the time of observation, and the unit is decimal years.

[0049] Step 24: Based on the observation data of the monitoring station and the real-time precise orbit and satellite clock error correction product, and with the transformed coordinates as constraints, perform RT-PPP positioning calculation to obtain the RT-PPP positioning calculation coordinates, RT-PPP coordinate variance information and RT-PPP calculation status information of the monitoring station.

[0050] In this step, based on the monitoring station terminal observation data and the precision orbit and satellite clock error correction products in the form of real-time SSR data streams provided by third-party institutions, the RT-PPP coordinate parameters to be estimated are constrained by the RTK high-precision coordinates after the spatial reference is unified, and the RT-PPP positioning solution is performed.

[0051] Step 24 includes steps 241-243: Step 241, obtain the combined observation equations for the RT-PPP ionosphere-free IF system. The combined IF observation equations are as follows: in, Indicates the geometric distance between the monitoring station and the satellite. Indicates the tropospheric delay of the oblique path. Indicates satellite, , Indicates a monitoring station. Indicates the clock difference at the monitoring station. Indicates satellite clock bias, This indicates the pseudorange hardware delay of the monitoring station for the IF combination. This represents the pseudorange hardware delay of the IF-combined satellites. This indicates the phase hardware delay of the monitoring station for the IF combination. This indicates the phase hardware delay of the satellites in the IF combination. Indicates the floating-point ambiguity of the IF combination. Indicates the combined wavelength of IF. This represents the sum of noise, multipath effects, and unmodeled errors in the pseudorange IF combined observations of the monitoring station. This represents the sum of noise, multipath effects, and unmodeled errors in the combined phase IF observations of the satellite.

[0052] Step 242: Correct and linearize the IF combined observation equation of RT-PPP based on real-time precise orbit and satellite clock error products to obtain the IF combined function model.

[0053] The IF combined function model can be represented as: in, OMC represents the pseudo-range IF combination. OMC representing the phase IF combination, This represents the standard vector along the line of sight (i.e., the vector from the satellite to the monitoring station). This represents the coordinates to be determined, which are also the coordinates calculated using RT-PPP positioning. , This indicates that the clock bias parameters of the monitoring station have been absorbed from the UCD at the monitoring station. This indicates that the ambiguity parameters of UCD and UPD have been incorporated. Indicates receiver The zenith tropospheric delay at the (monitoring station) for At the receiver (Monitoring stations) and satellites The projection coefficients on the oblique path.

[0054] Step 243: Based on the IF combination function model and using the transformed coordinates as constraints of the IF combination error equation of RT-PPP, solve the IF combination error equation to obtain the RT-PPP positioning solution coordinates, RT-PPP coordinate variance information, and RT-PPP solution status information of the monitoring station.

[0055] The IF combination error equation is: in, in, Indicates coordinate transformation. Indicates the coordinates calculated by RT-PPP positioning. ， The vector matrix representing the distance from the satellite to the monitoring station. This is the tropospheric wet delay projection function. It is an identity matrix.

[0056] Step 25: Based on the solution status information corresponding to the transformed coordinates and RT-PPP positioning solution coordinates, a hierarchical decision-making mechanism is adopted to dynamically output the optimal result.

[0057] Step 25 includes steps 251-253: Step 251: When the solution state information corresponding to the transformed coordinates and the RT-PPP positioning solution coordinates are both fixed ambiguity solutions, a weighted fusion calculation is performed on the transformed coordinates and the RT-PPP positioning solution coordinates based on the RTK coordinate variance information and the RT-PPP coordinate variance information. The fusion calculation result is used as the monitoring and positioning result. .

[0058] In this step, with Taking coordinate calculation as an example, the fusion calculation formula is as follows: in, This indicates the variance information of the RTK coordinates during the coordinate transformation. This represents the RT-PPP coordinate variance information of the RT-PPP positioning solution coordinates. The above formula... Replace with or Then the remaining two coordinates are calculated.

[0059] In this embodiment, the results of RT-PPP and RTK calculations are dynamically weighted and fused to achieve a dual improvement in positioning accuracy and reliability.

[0060] Step 252: When the solution status information of the transformed coordinates is a fixed ambiguity solution and the solution status information corresponding to the RT-PPP positioning solution coordinates is a floating ambiguity solution, the transformed coordinates are used as the monitoring positioning result.

[0061] Step 253: When the solution status information of the transformed coordinates is an ambiguity floating-point solution, and the solution status information corresponding to the RT-PPP positioning solution coordinates is an ambiguity floating-point solution, if the RT-PPP positioning solution coordinates have converged, then the RT-PPP positioning solution coordinates are used as the monitoring positioning result; otherwise, the transformed coordinates are used as the monitoring positioning result.

[0062] In this step, when the solution status information of the transformed coordinates is an ambiguity floating-point solution, and the solution status information corresponding to the RT-PPP positioning solution coordinates is also an ambiguity floating-point solution, if the RT-PPP floating-point solution has converged to a stable state, then the RT-PPP positioning solution coordinates are taken as the monitoring and positioning result; if the RT-PPP floating-point solution has not converged to a stable state, then the transformed coordinates are taken as the monitoring and positioning result.

[0063] In this embodiment, the Earth's plate tectonics is dynamically corrected using a micro-block Euler vector model, and the ITRF reference frame transformation is achieved by combining it with the Helmert model, eliminating systematic coordinate deviations caused by differences in Earth's plate tectonics and coordinate frames. The unified benchmark RTK coordinates are used as strong constraints for the static RT-PPP Kalman filter, accelerating the convergence of the static RT-PPP. Based on the fixed ambiguity state (fixed solution / floating-point solution) and variance statistics, the optimal solution is dynamically selected to fully utilize the advantages of the two positioning algorithms, maintain the benchmark consistency of the positioning results, and effectively provide users with high-precision and high-reliability location information.

[0064] like Figure 2 As shown, a third aspect of the present invention provides an RT-PPP / RTK fusion GNSS deformation monitoring system based on dynamic unification of spatial reference, comprising: The conversion module 31 is used to perform epoch reduction and reference frame conversion on the RTK solution coordinates of the monitoring station to obtain the converted coordinates under the same ITRF reference frame and reference epoch as RT-PPP. The calculation module 32 is used to perform RT-PPP positioning calculation based on the observation data of the monitoring station and the real-time precise orbit and satellite clock error correction product, and with the transformed coordinates as constraints, to obtain the RT-PPP positioning calculation coordinates, RT-PPP coordinate variance information and RT-PPP calculation status information of the monitoring station. Output module 33 is used to perform weighted calculation on the transformed coordinates and RT-PPP positioning solution coordinates based on RTK coordinate variance information and RT-PPP coordinate variance information when the solution status information corresponding to the transformed coordinates and RT-PPP positioning solution coordinates are both fixed ambiguity solutions, and use the result as the monitoring and positioning result. The output module 33 is also used to take the transformed coordinates as the monitoring and positioning result when the solution status information of the transformed coordinates is a fixed ambiguity solution and the solution status information corresponding to the RT-PPP positioning solution coordinates is a floating ambiguity solution. The output module 33 is also used to take the RT-PPP positioning solution coordinates as the monitoring positioning result when the solution status information of the transformed coordinates is an ambiguity floating-point solution and the solution status information corresponding to the RT-PPP positioning solution coordinates is an ambiguity floating-point solution, if the RT-PPP positioning solution coordinates have converged, otherwise, take the transformed coordinates as the monitoring positioning result.

[0065] In one embodiment of the present invention, epoch reduction and reference frame transformation are performed on the RTK calculated coordinates of the monitoring station to obtain transformed coordinates under the same ITRF reference frame and reference epoch as RT-PPP, including: The reference coordinates of the base station are calculated based on the observation data of the base station and the preset accuracy, and the ITRF reference frame and reference epoch information are obtained. Based on the reference coordinates, observation data and broadcast ephemeris of the base station, and observation data and broadcast ephemeris of the monitoring station, short baseline RTK calculation is performed to determine the RTK calculation coordinates, RTK coordinate variance information, RTK calculation status information and RTK spatial reference information of the monitoring station. Based on the RTK solution coordinates, RTK spatial reference information, ITRF reference frame and reference epoch information, the RTK solution coordinates are reduced to epochs and transformed to obtain transformed coordinates under the same ITRF reference frame and reference epoch as RT-PPP.

[0066] In one embodiment of the present invention, based on the observation data of the monitoring station and the real-time precise orbit and satellite clock error correction product, and using the transformed coordinates as constraints, RT-PPP positioning calculation is performed to obtain the RT-PPP positioning calculation coordinates, RT-PPP coordinate variance information, and RT-PPP calculation status information of the monitoring station, including: The IF combined observation equation of RT-PPP is corrected and linearized based on real-time precise orbit and satellite clock error products, and the IF combined function model is obtained. Based on the IF combination function model and using the transformed coordinates as constraints on the IF combination error equation of RT-PPP, the IF combination error equation is solved to obtain the RT-PPP positioning solution coordinates, RT-PPP coordinate variance information, and RT-PPP solution status information of the monitoring station.

[0067] In one embodiment of the present invention, the IF combined observation equation is: in, Indicates the geometric distance between the monitoring station and the satellite. Indicates the tropospheric delay of the oblique path. Indicates satellite, Indicates a monitoring station. Indicates the clock difference at the monitoring station. Indicates satellite clock bias, This indicates the pseudorange hardware delay of the monitoring station for the IF combination. This represents the pseudorange hardware delay of the IF-combined satellites. This indicates the phase hardware delay of the monitoring station for the IF combination. This indicates the phase hardware delay of the satellites in the IF combination. Indicates the floating-point ambiguity of the IF combination. Indicates the combined wavelength of IF. This represents the sum of noise, multipath effects, and unmodeled errors in the pseudorange IF combined observations of the monitoring station. This represents the sum of noise, multipath effects, and unmodeled errors in the combined phase IF observations of the satellite.

[0068] In one embodiment of the present invention, the IF combination function model is as follows: in, OMC represents the pseudo-range IF combination. OMC representing the phase IF combination, This represents the vector from the satellite to the monitoring station. Indicates the coordinates calculated by RT-PPP positioning. This indicates that the clock bias parameters of the monitoring station have been absorbed from the UCD at the monitoring station. This indicates that the ambiguity parameters of UCD and UPD have been incorporated. Indicates monitoring station The zenith tropospheric delay, express At the monitoring station and satellite The projection coefficients on the oblique path.

[0069] In one embodiment of the present invention, the IF combination error equation is: in, in, Indicates the transformed coordinates, , Indicates the coordinates calculated by RT-PPP positioning. ， The vector matrix representing the distance from the satellite to the monitoring station. This is the tropospheric wet delay projection function. It is an identity matrix.

[0070] In one embodiment of the present invention, the step of performing epoch reduction and reference frame transformation on the RTK solution coordinates based on the RTK solution coordinates, the RTK spatial reference information, the ITRF reference frame, and the reference epoch information to obtain transformed coordinates under the same ITRF reference frame and reference epoch as RT-PPP includes: The movement speed of the monitoring station is determined based on the RTK-calculated coordinates and the micro-block Euler vector model. Based on the RTK calculated coordinates, the reference epoch, the motion velocity, and the observation epoch, the observation epoch is reduced to obtain the reduced coordinates; Based on the Helmert model and the reduced coordinates, the ITRF reference frame of the reduced coordinates is transformed to the same ITRF reference frame as RT-PPP to obtain the transformed coordinates.

[0071] A fourth aspect of the present invention 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 the above-described RT-PPP / RTK fusion GNSS deformation monitoring method based on dynamic unification of spatial reference provided by the present invention.

[0072] The fifth aspect of this invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the above-described RT-PPP / RTK fusion GNSS deformation monitoring method based on dynamic unification of spatial reference provided by this invention.

[0073] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0074] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware systems.

[0075] The method provided in this invention can be applied to electronic devices. Specifically, the electronic device can be a desktop computer, a portable computer, a smart mobile terminal, a server, etc. No limitation is made herein; any electronic device that can implement this invention falls within the protection scope of this invention.

[0076] For system / electronic device embodiments, since they are basically similar to method embodiments, the description is relatively simple, and relevant parts can be found in the description of the method embodiments.

[0077] 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 system that specifies functions in one or more boxes.

[0078] 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, the instruction system being implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0079] 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.

[0080] 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.

Claims

1. A method for RT-PPP / RTK fusion GNSS deformation monitoring based on dynamic unification of spatial reference, characterized in that, Includes the following steps: The RTK solution coordinates of the monitoring station are reduced to epochs and the reference frame is transformed to obtain transformed coordinates under the same ITRF reference frame and reference epoch as RT-PPP. Based on the observation data of the monitoring station and the real-time precise orbit and satellite clock error correction product, and using the transformed coordinates as constraints, RT-PPP positioning calculation is performed to obtain the RT-PPP positioning calculation coordinates, RT-PPP coordinate variance information and RT-PPP calculation status information of the monitoring station. When the solution status information corresponding to the transformed coordinates and the RT-PPP positioning solution coordinates are both fixed ambiguity solutions, the transformed coordinates and the RT-PPP positioning solution coordinates are weighted and calculated based on the RTK coordinate variance information and the RT-PPP coordinate variance information to obtain the monitoring and positioning result; When the solution status information of the transformed coordinates is a fixed ambiguity solution, and the solution status information corresponding to the RT-PPP positioning solution coordinates is a floating ambiguity solution, the transformed coordinates are used as the monitoring positioning result. When the solution status information of the transformed coordinates is an ambiguity floating-point solution, and the solution status information corresponding to the RT-PPP positioning solution coordinates is an ambiguity floating-point solution, if the RT-PPP positioning solution coordinates have converged, then the RT-PPP positioning solution coordinates are used as the monitoring positioning result; otherwise, the transformed coordinates are used as the monitoring positioning result. The process of performing epoch reduction and reference frame transformation on the RTK coordinates of the monitoring station to obtain transformed coordinates under the same ITRF reference frame and reference epoch as RT-PPP includes: The reference coordinates of the base station are calculated based on the observation data of the base station and the preset accuracy, and the ITRF reference frame and reference epoch information are obtained. Based on the reference coordinates, observation data and broadcast ephemeris of the base station, and observation data and broadcast ephemeris of the monitoring station, short baseline RTK calculation is performed to determine the RTK calculation coordinates, RTK coordinate variance information, RTK calculation status information and RTK spatial reference information of the monitoring station. Based on the RTK solution coordinates, the RTK spatial reference information, the ITRF reference frame, and the reference epoch information, the RTK solution coordinates are subjected to epoch reduction and reference frame transformation to obtain transformed coordinates under the same ITRF reference frame and reference epoch as RT-PPP.

2. The method as described in claim 1, characterized in that, The process involves using the observation data from the monitoring station and real-time precise orbit and satellite clock error correction products, along with RT-PPP positioning calculations constrained by the transformed coordinates, to obtain the RT-PPP positioning coordinates, RT-PPP coordinate variance information, and RT-PPP calculation status information of the monitoring station, including: The IF combined observation equation of RT-PPP is corrected and linearized based on real-time precise orbit and satellite clock error products, and the IF combined function model is obtained. Based on the IF combination function model and using the transformed coordinates as constraints for the IF combination error equation of RT-PPP, the IF combination error equation is solved to obtain the RT-PPP positioning solution coordinates, RT-PPP coordinate variance information, and RT-PPP solution status information of the monitoring station.

3. The method as described in claim 2, characterized in that, The IF combined observation equation is: in, Indicates the geometric distance between the monitoring station and the satellite. Indicates the tropospheric delay of the oblique path. Indicates satellite, Indicates a monitoring station. Indicates the clock difference at the monitoring station. Indicates satellite clock bias, This indicates the pseudorange hardware delay of the monitoring station for the IF combination. This represents the pseudorange hardware delay of the IF-combined satellites. This indicates the phase hardware delay of the monitoring station for the IF combination. This indicates the phase hardware delay of the satellites in the IF combination. Indicates the floating-point ambiguity of the IF combination. Indicates the combined wavelength of IF. This represents the sum of noise, multipath effects, and unmodeled errors in the pseudorange IF combined observations of the monitoring station. This represents the sum of noise, multipath effects, and unmodeled errors in the combined phase IF observations of the satellite.

4. The method as described in claim 3, characterized in that, The IF combination function model is as follows: in, OMC represents the pseudo-range IF combination. OMC representing the phase IF combination, This represents the vector from the satellite to the monitoring station. Indicates the coordinates calculated by RT-PPP positioning. This indicates that the clock bias parameters of the monitoring station have been absorbed from the UCD at the monitoring station. This indicates that the ambiguity parameters of UCD and UPD have been incorporated. Indicates monitoring station The zenith tropospheric delay, express At the monitoring station and satellite The projection coefficients on the oblique path.

5. The method as described in claim 4, characterized in that, The IF combination error equation is as follows: in, in, Indicates the transformed coordinates, , Indicates the coordinates calculated by RT-PPP positioning. ， The vector matrix representing the distance from the satellite to the monitoring station. This is the tropospheric wet delay projection function. It is an identity matrix.

6. The method as described in claim 5, characterized in that, The step of performing epoch reduction and reference frame transformation on the RTK solution coordinates based on the RTK solution coordinates, the RTK spatial reference information, the ITRF reference frame, and the reference epoch information to obtain transformed coordinates under the same ITRF reference frame and reference epoch as RT-PPP includes: The movement speed of the monitoring station is determined based on the RTK-calculated coordinates and the micro-block Euler vector model. Based on the RTK calculated coordinates, the reference epoch, the motion velocity, and the observation epoch, the observation epoch is reduced to obtain the reduced coordinates; Based on the Helmert model and the reduced coordinates, the ITRF reference frame of the reduced coordinates is transformed to the same ITRF reference frame as RT-PPP to obtain the transformed coordinates.

7. A fusion RT-PPP / RTK GNSS deformation monitoring system based on dynamic unification of spatial reference, characterized in that, include: The conversion module is used to perform epoch reduction and reference frame conversion on the RTK solution coordinates of the monitoring station to obtain the converted coordinates under the same ITRF reference frame and reference epoch as RT-PPP. The calculation module is used to perform RT-PPP positioning calculation based on the observation data of the monitoring station and the real-time precise orbit and satellite clock error correction product, and with the transformed coordinates as constraints, to obtain the RT-PPP positioning calculation coordinates, RT-PPP coordinate variance information and RT-PPP calculation status information of the monitoring station. The output module is used to perform a weighted calculation on the transformed coordinates and the RT-PPP positioning solution coordinates based on the RTK coordinate variance information and the RT-PPP coordinate variance information when the solution status information corresponding to the transformed coordinates and the RT-PPP positioning solution coordinates are both fixed ambiguity solutions, and to use this as the monitoring and positioning result. The output module is also used to use the transformed coordinates as the monitoring and positioning result when the solution status information of the transformed coordinates is a fixed ambiguity solution and the solution status information corresponding to the RT-PPP positioning solution coordinates is a floating ambiguity solution; The output module is further configured to, when the solution status information of the transformed coordinates is an ambiguity floating-point solution and the solution status information corresponding to the RT-PPP positioning solution coordinates is an ambiguity floating-point solution, if the RT-PPP positioning solution coordinates have converged, then use the RT-PPP positioning solution coordinates as the monitoring positioning result; otherwise, use the transformed coordinates as the monitoring positioning result. The process of performing epoch reduction and reference frame transformation on the RTK coordinates of the monitoring station to obtain transformed coordinates under the same ITRF reference frame and reference epoch as RT-PPP includes: The reference coordinates of the base station are calculated based on the observation data of the base station and the preset accuracy, and the ITRF reference frame and reference epoch information are obtained. Based on the reference coordinates, observation data and broadcast ephemeris of the base station, and observation data and broadcast ephemeris of the monitoring station, short baseline RTK calculation is performed to determine the RTK calculation coordinates, RTK coordinate variance information, RTK calculation status information and RTK spatial reference information of the monitoring station. Based on the RTK solution coordinates, the RTK spatial reference information, the ITRF reference frame, and the reference epoch information, the RTK solution coordinates are subjected to epoch reduction and reference frame transformation to obtain transformed coordinates under the same ITRF reference frame and reference epoch as RT-PPP.

8. 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 RT-PPP / RTK fusion GNSS deformation monitoring method based on dynamic unification of spatial reference as described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the RT-PPP / RTK fusion GNSS deformation monitoring method based on dynamic unification of spatial reference as described in any one of claims 1 to 6.

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