Enhanced adaptive constraint of correction number precision star-ground fusion seamless positioning method and system, and medium

Abstract

The application discloses a kind of based on enhanced correction number precision self-adapting constraint satellite-ground fusion seamless positioning method, system and medium, belong to satellite navigation high-precision positioning technical field.Reference station network observation data and satellite-based precise correction information are obtained, and the precision information of the uncertainty of the observation domain comprehensive enhanced correction number and its representation is generated;Two kinds of correction information are used to correct user observation value and construct corresponding observation equation;Unified positioning model containing receiver position, residual atmospheric error and ambiguity is established, residual atmospheric error virtual pseudo-observation equation is constructed, and constraint variance is adaptively determined according to precision information;Joint multiple equations complete filtering solution and output positioning result.The supporting system includes the service end of multiple correction data and the user end of executing adaptive solution.The application can continuously adjust the constraint strength with the correction number credibility, realize network RTK and satellite-based PPP smooth transition, maintain positioning calculation coherent and stable in whole world, adapt to various mobile carrier long-time continuous high-precision positioning scene.

Description

Technical Field

[0001] This invention relates to the field of high-precision positioning technology for satellite navigation, specifically to a seamless satellite-ground fusion positioning method, system, and medium with enhanced correction accuracy adaptive constraints. Background Technology

[0002] GNSS high-precision positioning technology is a crucial foundation for fields such as intelligent transportation, low-altitude flight, unmanned systems, marine surveying, precision agriculture, and engineering monitoring. Currently, real-time high-precision positioning mainly relies on two technical approaches: ground-based augmentation and satellite-based augmentation. Ground-based network RTK generates regional augmentation corrections based on a continuously operating reference station network, enabling rapid convergence and centimeter-level positioning within the reference station network's coverage area. It boasts advantages such as high model strength and rapid ambiguity fixation. Satellite-based PPP or satellite-based PPP-RTK utilizes precise orbit, clock bias, and related deviation information broadcast by satellites for positioning. It features wide-area coverage and good service continuity, but its initialization speed, ambiguity fixation capability, and instantaneous centimeter-level positioning performance are generally weaker than ground-based network RTK.

[0003] In practical applications, user terminals are not always stably located within the augmentation network. Mobile platforms such as vehicles, ships, drones, and low-altitude carriers may frequently cross the boundaries between the augmentation network and its surrounding areas, or operate for extended periods at the edge of the reference network and in its extended regions. In such scenarios, ground-based augmentation corrections are not typically rendered unusable suddenly, but rather their accuracy gradually decreases as the user's location moves further away from the geometric center of the reference network, spatial interpolation conditions deteriorate, the age of the corrections increases, and the spatial correlation of atmospheric errors weakens. Therefore, the essence of the continuous positioning problem at the augmentation network boundary is not entirely due to the lack of corrections caused by communication interruptions, but rather a positioning model adaptation problem caused by the continuous change in correction uncertainty with spatial location and time delay.

[0004] Existing ground-based augmentation positioning methods typically use observation domain corrections generated by a reference station network directly to correct user-end observations. When the user is within the augmentation network and atmospheric modeling accuracy is high, this approach can fully utilize regional augmentation information, improving positioning model strength and ambiguity fixing efficiency. However, when the user is located at the augmentation network boundary or in the extended region outside the network, the augmentation corrections obtained through spatial interpolation or extrapolation may contain significant residual ionospheric and tropospheric errors. If these corrections are still used directly as high-confidence hard corrections, residual atmospheric errors may be absorbed into position parameters and carrier phase ambiguities, leading to decreased ambiguity fixing reliability, systematic biases in positioning results, and even position jumps during the transition between in-network and out-of-network conditions. On the other hand, satellite-based PPP models typically treat atmospheric errors as parameters to be estimated, maintaining good model unbiasedness over a wide area, but their model strength is relatively weak, with limited convergence speed and ambiguity fixing efficiency. If users completely abandon ground-based augmentation corrections in the augmentation network boundary area and directly switch to satellite-based PPP calculation, they will lose the regional augmentation information that still has a certain degree of accuracy, resulting in unnecessary increases in convergence time and decreases in positioning accuracy.

[0005] Therefore, how to make reasonable use of the observation domain comprehensive enhancement correction with gradually changing accuracy in the enhanced network boundary and extended regions outside the network to achieve a continuous transition between network RTK and satellite-based PPP rather than a hard handover is an urgent problem to be solved. Summary of the Invention

[0006] To address the aforementioned technical problems, this application discloses a seamless satellite-to-ground positioning method, system, and medium based on adaptive constraints for enhanced correction accuracy; the aforementioned seamless satellite-to-ground positioning method based on adaptive constraints for enhanced correction accuracy includes: Acquire reference station network observation data and satellite-based precision correction information. Under the unified benchmark of the satellite-based precision correction information, generate an observation domain comprehensive enhancement correction number based on the reference station network observation data, and generate the accuracy information of the observation domain comprehensive enhancement correction number. Based on the satellite-based precision correction information and the observation domain integrated enhancement correction number, the user terminal observation values ​​are corrected to obtain the corrected carrier phase observation equation; A unified positioning model is established, with receiver position, residual atmospheric error after enhancement correction, and carrier phase ambiguity as the parameters to be estimated in the unified positioning model. A pseudo-observation equation is constructed with the residual atmospheric error after the enhancement correction set to zero, and the constraint variance of the pseudo-observation equation is determined based on the accuracy information of the comprehensive enhancement correction number of the observation domain. Based on the unified positioning model, the modified observation equation, and the pseudo-observation equation, filtering estimation is performed to obtain the positioning result and output it.

[0007] Preferably, the step of generating the observation domain comprehensive enhancement correction based on the reference station network observation data includes: Based on the difference between the pseudorange observation value and the pseudorange calculation value at the reference station, a pseudorange comprehensive enhancement correction number is generated; Based on the difference between the carrier phase observation value and the calculated carrier phase value at the reference station, a carrier phase comprehensive enhancement correction number is generated; Both the pseudorange calculation value and the carrier phase calculation value are calculated based on the reference station prior information, the satellite-based precision correction information, and the modelable error correction. Within the same satellite system, a reference satellite is selected, and the pseudorange integrated enhancement correction and carrier phase integrated enhancement correction of the target satellite and the reference satellite are calculated separately for inter-satellite single difference to obtain the inter-satellite single difference observation domain integrated enhancement correction. A spatial interpolation model is constructed using the inter-satellite single-difference observation domain comprehensive enhancement corrections corresponding to multiple reference stations, and the interpolation solution is used to obtain the observation domain comprehensive enhancement corrections corresponding to the user terminal location.

[0008] Preferably, the accuracy information of the generated observation domain comprehensive enhancement correction includes: Generate the covariance matrix of the comprehensive enhancement corrections in the observation domain The covariance matrix consists of a spatial interpolation propagation error term, a correction age error term, and a fundamental noise term, and is expressed by the following formula:

[0009] in This is the spatial interpolation propagation error term; To correct for the age-related error term; This is the basic noise term.

[0010] Preferably, the spatial interpolation propagation error term and the correction age error term of the covariance matrix are specifically determined as follows: The correction number age error term is determined based on the time interval between the correction number generation time and the user terminal observation epoch, as well as the power spectral density or empirical growth coefficient of the correction number as it degrades over time. The spatial interpolation propagation error term is determined by the regional interpolation model prediction variance of the residual atmospheric correction; the residual atmospheric correction includes the residual ionospheric correction and the residual tropospheric correction; By establishing a regional interpolation model for any residual atmospheric correction, spatial interpolation model coefficients are calculated based on the spatial coordinate difference vectors corresponding to the baselines of multiple reference stations and the difference in residual atmospheric corrections. Based on the spatial interpolation model coefficients, the spatial coordinate difference vectors corresponding to the user end or interpolation point location, and the spatial interpolation unit weight error, the spatial interpolation standard deviation of the residual atmospheric correction at the user end or interpolation point location is calculated as the spatial interpolation propagation error term.

[0011] Preferably, the step of correcting the user-end observations to obtain the corrected observation equation includes: Obtain the raw pseudorange observations and raw carrier phase observations from the user terminal; Satellite-based precision correction information is used to correct satellite precision orbit errors and satellite clock errors. Then, the observation domain comprehensive enhancement correction is superimposed to compensate for path errors in pseudorange observations and carrier phase observations, respectively. Based on the compensated pseudorange observations, a corrected pseudorange observation equation is constructed, which includes receiver position terms, residual tropospheric error terms, and residual ionospheric error terms. Based on the compensated carrier phase observations, a corrected carrier phase observation equation is constructed, which includes a receiver position term, a residual tropospheric error term, a residual ionospheric error term, and a carrier phase integer ambiguity term.

[0012] Preferably, the step of constructing a pseudo-observation equation with the enhanced and corrected residual atmospheric error as zero, and determining the constraint variance of the pseudo-observation equation based on the accuracy information of the comprehensive enhanced correction number of the observation domain, includes: The enhanced and corrected residual atmospheric error includes the enhanced and corrected residual ionospheric error and the enhanced and corrected residual tropospheric error; a pseudo-observation equation for the residual ionospheric error is constructed with the enhanced and corrected residual ionospheric error as zero, and a pseudo-observation equation for the residual tropospheric error is constructed with the enhanced and corrected residual tropospheric error as zero. Based on the spatial interpolation propagation error term and the correction age error term, the residual ionospheric error constraint variance and the residual tropospheric error constraint variance are determined respectively through a mapping function, serving as the constraint variance of the pseudo-observation equation. When the constraint variance is in a small range, the enhanced and corrected residual atmospheric error is strongly constrained, and the unified positioning model approaches the network RTK model. When the constraint variance is in a large range, the enhanced and corrected residual atmospheric error is released from estimation, and the unified positioning model approaches the satellite-based PPP model.

[0013] Preferably, the step of performing filtering estimation based on the unified positioning model, the modified observation equation, and the pseudo-observation equation to obtain and output the positioning result includes: Based on the unified positioning model, the corrected observation equation, and the pseudo-observation equation, a filtering estimation is performed to obtain the floating-point solution and its covariance. The floating-point solution and covariance are fixed with integer ambiguity, and the ambiguity-fixed solution is output as the final positioning result.

[0014] A seamless satellite-ground fusion positioning system based on adaptive constraints for enhanced correction accuracy, the system comprising a server and a user terminal; The server acquires reference station network observation data and satellite-based precision correction information. Under the unified benchmark of satellite-based precision correction information, it generates observation domain comprehensive enhancement correction numbers based on reference station network observation data, and generates accuracy information of observation domain comprehensive enhancement correction numbers. Send satellite-based precision correction information, observation domain integrated enhancement corrections, and accuracy information to the user terminal; The user terminal is used to receive the satellite-based precision correction information, the observation domain comprehensive enhancement correction number and accuracy information, and to correct the user terminal observation values ​​based on the satellite-based precision correction information and the observation domain comprehensive enhancement correction number to obtain the corrected observation equation; By establishing a unified positioning model, the receiver position, the residual atmospheric error after enhancement correction, and the carrier phase ambiguity are used as parameters to be estimated. A pseudo-observation equation is constructed with the residual atmospheric error after enhancement correction as zero, and the constraint variance of the pseudo-observation equation is determined based on the accuracy information of the comprehensive enhancement correction in the observation domain. The positioning results are obtained and output by filtering estimation based on the unified positioning model, the modified observation equation, and the pseudo-observation equation.

[0015] A computer device, comprising: a memory and a processor; The memory and the processor are interconnected. The memory stores computer instructions, and the processor executes the computer instructions to perform any of the aforementioned satellite-ground fusion seamless positioning methods based on enhanced correction number accuracy adaptive constraints.

[0016] A computer-readable storage medium storing computer instructions for causing a computer to execute any of the satellite-ground fusion seamless positioning methods based on enhanced correction number accuracy adaptive constraints.

[0017] Compared with the prior art, the technical solution of this application has the following technical effects: This application can simultaneously generate comprehensive augmentation corrections and associated accuracy information for the observation domain, fully quantify the uncertainty inherent in the corrections themselves, provide a standardized and reliable reference for the positioning solution process, prevent the corrections from being directly used as fixed error-free parameters in the calculation, fully retain the error characteristics inherent in the corrections for subsequent constraint adjustment, and improve the data input foundation for satellite-ground fusion positioning.

[0018] This application explicitly introduces residual atmospheric error as a parameter to be estimated in the unified positioning model, simultaneously constructs corresponding virtual constraint equations, dynamically adjusts the constraint strength based on the correction accuracy information, realizes smooth and autonomous switching of the positioning model, maintains the stability and uniformity of the filtering solution framework throughout the process, ensures the continuity and uninterrupted positioning solution process, and maintains the consistency of the solution state during the movement of the carrier.

[0019] This application generates user-end corrections by combining inter-satellite single-difference with spatial interpolation, eliminating interference caused by common bias at the receiver end, improving the spatial correlation of corrections at different locations, and accurately characterizing the variation law of correction accuracy by combining multi-dimensional error terms of hierarchical calculation, which is suitable for the actual use scenario where the accuracy of corrections continuously decays as users move away from the reference station network.

[0020] This application integrates multiple observation equations and virtual constraint equations to carry out joint filtering estimation, and outputs positioning results after fixing the carrier phase ambiguity. It makes full use of the dual advantages of ground-based augmentation information and satellite-based precision correction information, continuously ensuring the stable output of positioning solutions in different coverage areas and improving the overall operational reliability of positioning services. Attached Figure Description

[0021] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart illustrating the seamless satellite-to-ground fusion positioning method based on adaptive constraints of enhanced correction number accuracy according to the present invention. Figure 2 This is an architecture diagram of the satellite-ground fusion seamless positioning system based on adaptive constraints of enhanced correction accuracy, as per the present invention. Figure 3 This is a comparison chart of positioning errors under different constraint strengths under low-precision comprehensive correction conditions provided in the embodiments of the present invention; Figure 4 This is a comparison chart of positioning errors under different constraint intensities under high-precision comprehensive correction conditions provided in the embodiments of the present invention; Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. In the following description, specific details such as specific configurations and components are provided merely to help fully understand the embodiments of this application. Therefore, those skilled in the art should understand that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this application. In addition, for clarity and brevity, descriptions of known functions and structures are omitted in the embodiments.

[0024] It should be understood that the phrase "an embodiment" or "this embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, "an embodiment" or "this embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments.

[0025] Furthermore, reference numerals and / or letters may be repeated in different examples within this application. Such repetition is for the purpose of simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or settings discussed.

[0026] In this article, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, B exists alone, and A and B exist simultaneously. The term " / and" in this article describes another type of relationship between related objects, indicating that two relationships can exist. For example, A / and B can mean: A exists alone, and A and B exist alone. In addition, the character " / " in this article generally indicates that the related objects before and after it are in an "or" relationship.

[0027] In this article, the term "at least one" is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, "at least one of A and B" can mean: A exists alone, A and B exist simultaneously, or B exists alone.

[0028] It should also be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion.

[0029] Example 1 describes in detail a seamless satellite-to-ground positioning method based on adaptive constraints of enhanced correction accuracy, such as... Figure 1 As shown, it includes: Acquire reference station network observation data and satellite-based precision correction information. Under the unified benchmark of the satellite-based precision correction information, generate an observation domain comprehensive enhancement correction number based on the reference station network observation data, and generate the accuracy information of the observation domain comprehensive enhancement correction number. Based on the satellite-based precision correction information and the observation domain integrated enhancement correction number, the user terminal observation values ​​are corrected to obtain the corrected carrier phase observation equation; A unified positioning model is established, with receiver position, residual atmospheric error after enhancement correction, and carrier phase ambiguity as the parameters to be estimated in the unified positioning model. A pseudo-observation equation is constructed with the residual atmospheric error after the enhancement correction set to zero, and the constraint variance of the pseudo-observation equation is determined based on the accuracy information of the comprehensive enhancement correction number of the observation domain. Based on the unified positioning model, the modified observation equation, and the pseudo-observation equation, filtering estimation is performed to obtain the positioning result and output it.

[0030] Furthermore, the comprehensive enhancement correction and its accuracy information for the observation domain are generated, specifically as follows: The server acquires reference station network observation data and satellite-based precision correction information. Under the unified benchmark of the satellite-based precision correction information, it generates an observation domain comprehensive enhancement correction number based on the reference station network observation data, and generates the accuracy information of the observation domain comprehensive enhancement correction number. The accuracy information is used to characterize the uncertainty of the observation domain comprehensive enhancement correction number.

[0031] For reference station k, satellite s, and frequency point f, the pseudorange integrated enhancement correction and carrier phase integrated enhancement correction are expressed as follows:

[0032]

[0033] in, The pseudorange augmentation correction for satellite s at frequency point f is given by reference station k. The carrier phase enhancement correction for satellite s at frequency point f is given by reference station k. The pseudorange observation value is for the reference station; The carrier phase observation value is from the reference station; The pseudorange calculation value is obtained based on the known coordinates of the reference station, the satellite-based precise orbital clock error correction information, and the modelable error correction. The carrier phase is calculated based on the known coordinates of the reference station, the satellite-based precise orbit clock error correction information, and the modelable error correction.

[0034] The composite enhancement correction is the difference between the observed and calculated values ​​from the reference station. The calculated values ​​are based on the known precise coordinates of the reference station and high-precision satellite-based products; therefore, the residual includes unmodeled components such as atmospheric errors at the reference station. Modelable error corrections include antenna phase center correction, Earth rotation correction, relativistic effects, solid tides, and ocean tidal loads.

[0035] To mitigate the impact of receiver clock bias and receiver hardware deviations, a reference satellite j is selected within the same satellite system. An inter-satellite single-difference is performed on the combined enhancement corrections of satellite s and reference satellite j to obtain the inter-satellite single-difference combined enhancement correction for the observation domain:

[0036]

[0037] in, This is the comprehensive enhancement correction number for inter-satellite single-difference pseudorange; This is the inter-satellite single-difference carrier phase synthesis enhancement correction number.

[0038] The server establishes a spatial interpolation model based on the inter-satellite single-difference observation domain comprehensive enhancement corrections from multiple reference stations, generating observation domain comprehensive enhancement corrections at the user end or interpolation point location. Unlike traditional methods that only output corrections, this invention simultaneously generates the accuracy information of the observation domain comprehensive enhancement corrections, which is used to determine the residual atmospheric error constraint strength at the user end.

[0039] The accuracy information of the comprehensive enhancement correction in the observation domain is represented as a covariance matrix R_c, which consists of a spatial interpolation propagation error term, a correction age error term, and a fundamental noise term:

[0040] in, The covariance matrix of the comprehensive enhancement corrections for the observation domain characterizes the uncertainty of the corrections; The spatial interpolation propagation error term is used to characterize the correction uncertainty caused by the spatial modeling of the reference station network, the location of the user terminal or interpolation point, and the interpolation residual, and includes the boundary extrapolation uncertainty obtained from the propagation of the same spatial model. This is the age error term for the correction, used to characterize the increase in uncertainty of the correction over time. It is the basic noise term, used to characterize the reference station observation noise, unmodeled residual error, or minimum variance lower bound.

[0041] It should be noted that the physical meaning of decomposing the precision information into three terms lies in: the spatial interpolation propagation error term. This reflects the spatial relationship of the user's location relative to the reference network geometry. This term is smaller when the user is within the network and larger when the user is outside the network's extended area; (Correction for age error term) This reflects the timeliness of the correction; the longer the time, the greater the uncertainty; the fundamental noise term. The lower limit of the correction number's accuracy is determined by the reference station's observation noise and unmodeled residual errors.

[0042] The corrected age error term is expressed as follows:

[0043] in, The age error covariance matrix is ​​obtained by multiplying the product of the growth factor of the correction over time and the time interval by the identity matrix; The power spectral density or empirical growth factor of the correction degrades over time, describing the rate at which the correction degrades over time; Δt is the time interval between the correction generation time and the user-end observation epoch; I is the identity matrix, with the same dimension as the state vector.

[0044] For example, when the correction period is short, the age error term is small; when the correction period is long, the age error term will increase significantly and needs to be reflected in the constraint variance.

[0045] The spatial interpolation propagation error term is determined by the prediction variance of the regional interpolation model for the residual atmospheric correction. For any residual atmospheric correction A (A can be either an ionospheric correction or a tropospheric correction), a regional interpolation model is established:

[0046] Where A is the residual atmospheric correction, representing the ionospheric correction or the tropospheric correction; Let be the residual atmospheric correction difference corresponding to the baseline of the i-th reference station. Let i be the spatial coordinate difference vector corresponding to the baseline of the i-th reference station; These are the coefficients of the spatial interpolation model.

[0047] Based on the design matrix G_A composed of multiple reference station baselines and the residual atmospheric correction vector L_A, the spatial interpolation model coefficients are:

[0048] Where GA is the design matrix composed of multiple reference station baselines; LA is the residual atmospheric correction interpolation vector; This is the coefficient vector of the spatial interpolation model.

[0049] The spatial interpolation standard deviation at the user end or interpolation point location is expressed as:

[0050] Where, σ_ A,sp,u The spatial interpolation standard deviation of the residual atmospheric correction at the user end or interpolation point location; This is the spatial coordinate difference vector corresponding to the user terminal or interpolation point location; The spatial interpolation unit weighted error (variance) reflects the model fitting quality.

[0051] In one possible implementation, the generation of the observation domain integrated enhancement correction number includes generating a pseudorange integrated enhancement correction number based on the difference between the pseudorange observation value and the pseudorange calculation value of the reference station, generating a carrier phase integrated enhancement correction number based on the difference between the carrier phase observation value and the carrier phase calculation value of the reference station, performing inter-satellite single difference on the correction numbers of the target satellite and the reference satellite, and performing spatial interpolation to obtain the correction number of the user terminal position.

[0052] In one possible implementation, the generation of accuracy information includes generating a covariance matrix. Among them, the age error term The spatial interpolation propagation error term is determined by the prediction variance of the regional interpolation model.

[0053] Furthermore, the user-end observations are corrected to obtain the corrected observation equation.

[0054] Specifically, after receiving the satellite-based precision correction information and the observation domain comprehensive enhancement correction, the user terminal uses the satellite-based precision correction information to correct the satellite orbit and satellite clock error, and uses the observation domain comprehensive enhancement correction to correct the pseudorange observation value and carrier phase observation value at the user terminal, thus obtaining the corrected pseudorange observation equation and the corrected carrier phase observation equation.

[0055] The inter-satellite single-difference pseudorange observation equation, corrected by the observation domain comprehensive enhancement correction, is as follows:

[0056] in, For receiver r, the inter-satellite single-difference pseudorange observations of satellite s and reference satellite j; The inter-satellite single-difference geometric distance is a nonlinear function that includes the receiver position; Z is an inter-satellite single-difference tropospheric mapping function that maps the zenith direction delay to an oblique path. res To enhance the corrected residual tropospheric error, the parameter to be estimated in the state vector is ; The ionospheric frequency coefficient; To enhance the corrected inter-satellite single-difference residual ionospheric error, is the parameter to be estimated in the state vector; This is pseudorange observation noise.

[0057] The inter-satellite single-difference carrier phase observation equation, corrected by the observation domain comprehensive enhancement correction, is as follows:

[0058] in, For receiver r, the inter-satellite single-difference carrier phase observations of satellite s and reference satellite j; This is the inter-satellite single-difference carrier phase synthesis enhancement correction number at the user terminal or interpolation point location; The carrier wavelength at frequency point f; Let be the inter-satellite single-difference carrier phase ambiguity, and be the parameter to be estimated in the state vector; This is carrier phase observation noise.

[0059] Furthermore, a unified positioning model is established, using receiver position, residual atmospheric error after enhancement correction, and carrier phase ambiguity as parameters to be estimated. Specifically, the user terminal establishes a unified positioning model integrating satellite and ground, whose state vector is represented as follows:

[0060] Where r is the receiver position vector. To enhance the corrected residual tropospheric error, To enhance the corrected residual ionospheric error, N represents the carrier phase ambiguity.

[0061] The key to this state design is that the terminal does not use the enhancement correction itself as a parameter to be estimated. Instead, after correcting the observations with the enhancement correction, it explicitly estimates the residual ionospheric error and residual tropospheric error that it could not completely eliminate.

[0062] Furthermore, a pseudo-observation equation is constructed with the enhanced and corrected residual atmospheric error set to zero, and the constraint variance is determined based on the accuracy information. Specifically, the user end constructs a pseudo-observation equation with both the enhanced and corrected residual ionospheric error and the enhanced and corrected residual tropospheric error set to zero:

[0063] in, This is pseudo-observation noise caused by inter-satellite single-difference residual ionospheric error. This refers to residual tropospheric error pseudo-observation noise. The zero-priority pseudo-observation variance of the residual atmospheric error is obtained by mapping the accuracy information of the observation domain comprehensive enhancement correction.

[0064] It should be noted that constructing a pseudo-observation equation with zero residual atmospheric error is a soft constraint mechanism. By adjusting the size of the constraint variance, it controls the estimator's confidence level in the prior belief that "the residual error is close to zero." This is not a real observation, but rather the introduction of prior information into the filtering framework in the form of an observation equation.

[0065] The residual atmospheric error zero-prior pseudo-observation variance is obtained by mapping the accuracy information of the observation domain comprehensive enhancement correction:

[0066] in, The variance constrained for the inter-satellite single-difference residual ionospheric error. The residual tropospheric error constraint variance, This represents the standard deviation of the inter-satellite single-difference residual ionospheric spatial interpolation. The standard deviation of the residual tropospheric spatial interpolation. and To correct the standard deviation corresponding to the age period, and These are mapping functions from the accuracy of the comprehensive enhancement correction in the observation domain to the standard deviation of the residual ionospheric error constraint and the standard deviation of the residual tropospheric error constraint, respectively.

[0067] The user end performs joint filtering estimation based on the modified pseudorange observation equation, the modified carrier phase observation equation, and the residual atmospheric error zero-priority pseudo-observation equation to obtain the satellite-ground fusion floating-point solution and its covariance, and outputs integer ambiguity fixation and continuous positioning results.

[0068] when and When the residual ionospheric error and residual tropospheric error are relatively small, the localization model is strongly constrained, and the localization model is equivalent to or approximately equivalent to the network RTK model; when and When the error is large, the residual ionospheric error and the residual tropospheric error are released and estimated, and the positioning model smoothly degenerates into a satellite-based PPP model.

[0069] For example, when the user is close to the center of the reference network and the correction data is fresh, both the spatial interpolation standard deviation and the age standard deviation are small, the constraint variance is small, and the residual atmospheric error is forced to zero, resulting in a positioning model that exhibits performance close to network RTK. However, when the user moves away from the reference network or the correction data age increases, the spatial interpolation standard deviation and the age standard deviation increase, the constraint variance increases, the residual atmospheric error is released from estimation, and the positioning model smoothly degenerates into a satellite-based PPP model. Because the constraint variance is continuously changing, the positioning model is also continuously adaptive, achieving a seamless transition between network RTK and PPP, rather than a binary switching.

[0070] In one possible implementation, the enhanced and corrected residual atmospheric error includes enhanced and corrected residual ionospheric error and enhanced and corrected residual tropospheric error. Pseudo-observation equations are constructed for each, and constraint variances are determined separately using mapping functions. When the constraint variance is small, the unified positioning model approximates the network RTK model; when the constraint variance is large, it approximates the satellite-based PPP model.

[0071] Furthermore, based on the unified positioning model, the corrected observation equation, and the pseudo-observation equation, filtering estimation is performed to obtain and output the positioning results. Specifically, the user terminal performs joint filtering estimation based on the modified pseudorange observation equation, the modified carrier phase observation equation, and the residual atmospheric error zero-priority pseudo-observation equation to obtain the satellite-ground fusion floating-point solution and its covariance, and outputs the integer ambiguity fixation and continuous positioning results.

[0072] The joint filtering estimation incorporates three types of equations—the modified pseudorange observation equation, the modified carrier phase observation equation, and the pseudo-observation equation—into the filtering framework, and performs state estimation through Kalman filtering or extended Kalman filtering. The floating-point solution and its covariance are the outputs of the filter, and then the ambiguity is fixed using an integer ambiguity search method to obtain a fixed solution as the final positioning result.

[0073] In one possible implementation, the filtering estimation includes performing joint filtering estimation based on the modified observation equation and the pseudo-observation equation to obtain a floating-point solution and its covariance, and then fixing the integer ambiguity of the floating-point solution and its covariance to obtain a fixed solution as the positioning result.

[0074] This embodiment simultaneously generates accuracy information for enhanced corrections and quantification uncertainties. Based on the accuracy data, it adaptively adjusts the virtual constraint strength of residual atmospheric errors, constructs a unified filtering framework to smoothly switch positioning calculation modes, retains atmospheric residuals as parameters to be estimated, accurately characterizes the variation law of correction accuracy through layered error calculation, integrates multiple types of observation equations and virtual constraints to complete fixed ambiguity resolution, adapts to user movement scenarios in and outside the reference station network, maintains consistent and unified solution logic throughout the process, continuously ensures stable and reliable positioning output under different coverage areas, and eliminates positioning offsets and drastic fluctuations caused by a single fixed constraint.

[0075] Example 2 describes in detail the satellite-to-ground fusion seamless positioning method based on adaptive constraints of enhanced correction number accuracy, such as... Figure 2 As shown, This includes server 101 and client 102.

[0076] Server 101 includes a reference station network and an augmentation service system. It acquires reference station network observation data and satellite-based precise correction information, generates integrated augmentation corrections and their accuracy information for the observation domain under a unified benchmark, and transmits these corrections and accuracy information to user terminal 102 via a communication link. User terminal 102 is a mobile platform equipped with a GNSS receiver. After receiving the satellite-based precise correction information, the integrated augmentation corrections for the observation domain, and the accuracy information, it corrects the observations, establishes a unified positioning model to estimate residual atmospheric errors, constructs adaptive zero-prior constraints, performs joint filtering estimation, and outputs continuous positioning results. When user terminal 102 is within the reference station network, the correction accuracy is high, the residual atmospheric error is strongly constrained, and the positioning model approximates the network RTK model. When user terminal 102 crosses the augmentation network boundary or is in the extended region outside the network, the correction accuracy gradually decreases, the residual atmospheric error is gradually released and estimated, and the positioning model smoothly degenerates into a satellite-based PPP model.

[0077] The server is used to acquire reference station network observation data and satellite-based precision correction information. Under the unified benchmark of the satellite-based precision correction information, it generates an observation domain comprehensive enhancement correction number based on the reference station network observation data, and generates the accuracy information of the observation domain comprehensive enhancement correction number. The accuracy information is used to characterize the uncertainty of the observation domain comprehensive enhancement correction number. The server also sends the satellite-based precision correction information, the observation domain comprehensive enhancement correction number, and the accuracy information to the user terminal.

[0078] Specifically, the server side includes a reference station network and an augmentation service system. The reference station network consists of multiple continuously operating reference stations, each equipped with a dual-frequency or multi-frequency GNSS receiver to acquire pseudorange and carrier phase observation data at a fixed sampling rate. The augmentation service system acquires satellite-based precision correction information (including precise orbit and clock bias products), calculates pseudorange and carrier phase values ​​based on the known precise coordinates of the reference stations under a unified reference, and extracts the integrated residuals to generate the observation domain integrated augmentation correction. Simultaneously, the augmentation service system generates an accuracy information covariance matrix based on the spatial interpolation propagation error of the reference station network and the age error of the correction, and broadcasts these three types of information—satellite-based precision correction information, observation domain integrated augmentation correction, and accuracy information—to the user terminal via a communication link.

[0079] It should be noted that sending all three types of information simultaneously by the server is one of the key design features of this invention. Traditional solutions only broadcast the correction value itself, and the user cannot know the uncertainty of the correction value, so it can only be used as an error-free hard correction. This invention broadcasts accuracy information simultaneously, enabling the user to adaptively adjust the constraint strength according to the actual accuracy of the correction value.

[0080] In one possible implementation, the server generates a pseudorange integrated enhancement correction number based on the difference between the pseudorange observation value and the pseudorange calculation value of the reference station, generates a carrier phase integrated enhancement correction number based on the difference between the carrier phase observation value and the carrier phase calculation value of the reference station, performs inter-satellite single difference on the correction numbers of the target satellite and the reference satellite, and performs spatial interpolation based on the inter-satellite single difference observation domain integrated enhancement correction numbers of multiple reference stations to obtain the observation domain integrated enhancement correction number at the user terminal or the interpolation point location.

[0081] In one possible implementation, the server generates a covariance matrix of the observation domain's comprehensive enhancement correction as accuracy information. The covariance matrix consists of a spatial interpolation propagation error term, a correction age error term, and a fundamental noise term.

[0082] In one possible implementation, the correction age error term is determined based on the time interval between the correction generation time and the user-end observation epoch, as well as the power spectral density or empirical growth coefficient of the correction as it degrades over time; the spatial interpolation propagation error term is determined by the regional interpolation model prediction variance of the residual atmospheric correction.

[0083] The user terminal receives the satellite-based precision correction information, the observation domain integrated enhancement correction number, and the accuracy information. Based on the satellite-based precision correction information and the observation domain integrated enhancement correction number, it corrects the user terminal observation values ​​to obtain the corrected observation equation. A unified positioning model is established, using the receiver position, the enhanced and corrected residual atmospheric error, and the carrier phase ambiguity as parameters to be estimated. A pseudo-observation equation is constructed with the enhanced and corrected residual atmospheric error as zero, and the constraint variance of the pseudo-observation equation is determined based on the accuracy information of the observation domain integrated enhancement correction number. Based on the unified positioning model, the corrected observation equation, and the pseudo-observation equation, filtering estimation is performed to obtain the positioning result and output it.

[0084] Specifically, the user end is a mobile platform equipped with a GNSS receiver, including the receiver, processor, and memory. The receiver receives satellite navigation signals and generates pseudorange and carrier phase observations, while simultaneously receiving satellite-based precision correction information, observation domain integrated enhancement corrections, and accuracy information broadcast by the server. The processor performs the following operations: corrects satellite orbit and clock errors using satellite-based precision correction information, corrects pseudorange and carrier phase observations using observation domain integrated enhancement corrections, and obtains the corrected observation equations; establishes a unified positioning model to construct a state vector; constructs pseudo-observation equations with residual atmospheric error as zero and determines the constraint variance based on the accuracy information; performs joint filtering estimation based on the unified positioning model, the corrected observation equations, and the pseudo-observation equations to obtain floating-point solutions and their covariance, and outputs continuous positioning results after fixing integer ambiguities.

[0085] It should be noted that the core innovation of the user-side is that it does not use the enhanced corrections themselves as parameters to be estimated. Instead, after correcting the observations with the enhanced corrections, it explicitly estimates the residual ionospheric and tropospheric errors that were not completely eliminated. Based on the accuracy information, it adaptively determines the constraint variance of the zero prior constraint on the residual atmospheric error, so that the positioning model approaches the network RTK model when the accuracy of the corrections is high, and smoothly degenerates into the satellite-based PPP model when the accuracy decreases.

[0086] In one possible implementation, the user terminal corrects the pseudorange observations and carrier phase observations to obtain corrected pseudorange observation equations and corrected carrier phase observation equations.

[0087] In one possible implementation, the user terminal divides the enhanced and corrected residual atmospheric error into enhanced and corrected residual ionospheric error and enhanced and corrected residual tropospheric error, constructs pseudo-observation equations for each, and determines the constraint variances separately through mapping functions. When the constraint variance is small, the unified positioning model approximates the network RTK model; when the constraint variance is large, it approximates the satellite-based PPP model.

[0088] In one possible implementation, the user terminal performs joint filtering estimation based on the unified positioning model, the modified observation equation, and the pseudo-observation equation to obtain a floating-point solution and its covariance. The floating-point solution and its covariance are then fixed with integer ambiguity to obtain a fixed solution as the positioning result and output it.

[0089] In scenarios where users are far from the reference station network, located at the network boundary, or in areas extending beyond the network, the comprehensive augmentation correction of the observation domain is accompanied by significant spatial interpolation and temporal age errors, resulting in a substantial increase in the overall uncertainty of the correction. If a fixed, strong constraint is used to directly limit the residual atmospheric error, the bias inherent in the correction itself will be directly transmitted to the positioning solution. Therefore, a long-term continuous observation experiment was conducted to record the changes in the three-dimensional positioning errors (East, North, and Sky) over time, obtaining the corresponding error variation curves, such as... Figure 3 As shown, the differences in positioning results between the fixed tight constraint and the adaptive loose constraint modes of this application are presented intuitively. In this experimental scenario, this application relies on accuracy information to increase the variance of the virtual constraint of residual atmospheric error, releasing atmospheric residuals to participate in parameter estimation. This can offset the system offset introduced by the low confidence correction. The curve trends corresponding to the two constraint modes can clearly reflect the working logic of the adaptive adjustment mechanism in this scenario.

[0090] The uncertainty of the correction value continuously changes with the spatial distance between the user and the reference station network, and the corresponding adaptive constraint strength also varies significantly. A single fixed constraint cannot simultaneously adapt to two drastically different enhanced correction environments: one inside the network and one outside. To fully verify the core function of this solution—continuously switching the constraint strength based on the correction value accuracy—a comparative observation experiment was conducted where the user is located within the complete coverage area of ​​the reference station network. In this scenario, the correction value errors caused by interpolation and age are both at low levels, and the accuracy information can support the solution framework switching to an equivalent tight constraint state. By comparing the error curves of the two sets of differentiated scenarios, the technical advantages of the adaptive constraint mechanism in adapting to the positioning needs of the entire area are fully explained.

[0091] like Figure 4 As shown, when the user is in a densely covered area within the reference station network, the spatial distribution of reference stations is sufficient, and the reliability of the interpolated comprehensive augmentation correction for the observation domain is high, with a smaller uncertainty value represented by the corresponding accuracy information. This application can automatically reduce the constraint variance of the residual atmospheric error pseudo-observation equation based on this accuracy information, suppress atmospheric residual fluctuations by relying on high-intensity virtual constraints, and fully leverage the advantages of high precision and high stability of the ground-based augmentation correction. In the error curves corresponding to this scenario, the curve representing tight constraints converges quickly and remains close to the zero-error benchmark for a long time, with fluctuation amplitude remaining at an extremely low level; the loose constraint mode weakens the atmospheric error constraint, fails to fully utilize the high-precision correction conditions, has a slower convergence speed, and exhibits greater error fluctuations throughout the process. The curve comparison intuitively demonstrates the effect of adaptive tightening constraints on improving positioning stability within the network.

[0092] This invention also provides a computer storage medium (Memory), which is a memory device in an electronic device used to store programs and data. It is understood that the computer storage medium here can include both the built-in storage medium in the electronic device and extended storage media supported by the electronic device. The computer storage medium provides storage space that stores the operating system of the electronic device. Furthermore, the storage space also stores one or more instructions suitable for loading and execution by the processor 301. These instructions can be one or more computer programs (including program code). It should be noted that the computer storage medium here can be a high-speed RAM memory or a non-stable memory, such as at least one disk storage device; optionally, it can also be at least one computer storage medium located remotely from the aforementioned processor.

[0093] like Figure 5 The diagram shown is a schematic diagram of the structure of the electronic device provided in this application, including: at least one processor 301, such as a central processing unit, at least one memory 302, and at least one bus 303.

[0094] The aforementioned memory 302 can store program instructions, and the aforementioned processor 301 can be used to call the program instructions to execute a satellite-ground fusion continuous positioning method based on enhanced correction number accuracy adaptive constraints.

[0095] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, including read-only memory, random access memory, programmable read-only memory, erasable programmable read-only memory, programmable read-only memory, electronically erasable rewritable read-only memory, read-only optical disk, solid-state drive or other optical disk storage, disk storage, magnetic tape storage, or any other computer-readable medium capable of carrying or storing data.

[0096] This embodiment involves collaborative operation between the server and the user. The server uniformly generates and distributes complete correction data and corresponding accuracy information, providing standardized input support for the terminal's adaptive solution. After receiving multiple types of data, the user terminal fully executes the entire process of adaptive constraint adjustment and joint filtering solution. The hardware and software modules have clear division of labor and the data transmission link is complete. There is no need for manual switching of positioning modes. The user terminal can dynamically adjust the solution logic based on the reliability of the correction data, which is compatible with the operational requirements of continuous positioning services across the entire domain. This reduces the difficulty of terminal algorithm development and maintenance, and maintains a stable positioning output state during long-term observation of the mobile carrier.

[0097] The above are merely preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. For those skilled in the art, the present invention can have various modifications and variations. Any changes, modifications, substitutions, integrations, and parameter changes made to these embodiments within the spirit and principles of the present invention, without departing from the principles and spirit of the present invention, through conventional substitutions or to achieve the same function, fall within the scope of protection of the present invention.

Claims

1. A seamless satellite-to-ground positioning method based on adaptive constraints for enhanced correction accuracy, characterized in that, include: Acquire reference station network observation data and satellite-based precision correction information. Under the unified benchmark of the satellite-based precision correction information, generate an observation domain comprehensive enhancement correction number based on the reference station network observation data, and generate the accuracy information of the observation domain comprehensive enhancement correction number. Based on the satellite-based precision correction information and the observation domain comprehensive enhancement correction number, the user terminal observation values ​​are corrected to obtain the corrected observation equation; A unified positioning model is established, with receiver position, residual atmospheric error after enhancement correction, and carrier phase ambiguity as the parameters to be estimated in the unified positioning model. A pseudo-observation equation is constructed with the residual atmospheric error after the enhancement correction set to zero, and the constraint variance of the pseudo-observation equation is determined based on the accuracy information of the comprehensive enhancement correction number of the observation domain. Based on the unified positioning model, the modified observation equation, and the pseudo-observation equation, filtering estimation is performed to obtain the positioning result and output it.

2. The seamless satellite-to-ground fusion positioning method based on adaptive constraints of enhanced correction number accuracy as described in claim 1, characterized in that, The generation of the observation domain comprehensive enhancement correction based on reference station network observation data includes: Based on the difference between the pseudorange observation value and the pseudorange calculation value at the reference station, a pseudorange comprehensive enhancement correction number is generated; Based on the difference between the carrier phase observation value and the calculated carrier phase value at the reference station, a carrier phase comprehensive enhancement correction number is generated; Both the pseudorange calculation value and the carrier phase calculation value are calculated based on the reference station prior information, the satellite-based precision correction information, and the modelable error correction. Within the same satellite system, a reference satellite is selected, and the pseudorange integrated enhancement correction and carrier phase integrated enhancement correction of the target satellite and the reference satellite are calculated separately for inter-satellite single difference to obtain the inter-satellite single difference observation domain integrated enhancement correction. A spatial interpolation model is constructed using the inter-satellite single-difference observation domain comprehensive enhancement corrections corresponding to multiple reference stations, and the interpolation solution is used to obtain the observation domain comprehensive enhancement corrections corresponding to the user terminal location.

3. The seamless satellite-to-ground fusion positioning method based on adaptive constraints of enhanced correction number accuracy as described in claim 1, characterized in that, The accuracy information of the generated observation domain comprehensive enhancement correction includes: Generate the covariance matrix of the comprehensive enhancement corrections in the observation domain The covariance matrix consists of a spatial interpolation propagation error term, a correction age error term, and a fundamental noise term, and is expressed by the following formula: in This is the spatial interpolation propagation error term; To correct for the age-related error term; This is the basic noise term.

4. The satellite-to-ground fusion seamless positioning method based on adaptive constraints of enhanced correction number accuracy as described in claim 3, characterized in that, The spatial interpolation propagation error term and the corrected age error term of the covariance matrix are specifically determined as follows: The correction number age error term is determined based on the time interval between the correction number generation time and the user terminal observation epoch, as well as the power spectral density or empirical growth coefficient of the correction number as it degrades over time. The spatial interpolation propagation error term is determined by the regional interpolation model prediction variance of the residual atmospheric correction; the residual atmospheric correction includes the residual ionospheric correction and the residual tropospheric correction; By establishing a regional interpolation model for any residual atmospheric correction, spatial interpolation model coefficients are calculated based on the spatial coordinate difference vectors corresponding to the baselines of multiple reference stations and the difference in residual atmospheric corrections. Based on the spatial interpolation model coefficients, the spatial coordinate difference vectors corresponding to the user end or interpolation point location, and the spatial interpolation unit weight error, the spatial interpolation standard deviation of the residual atmospheric correction at the user end or interpolation point location is calculated as the spatial interpolation propagation error term.

5. The satellite-to-ground fusion seamless positioning method based on adaptive constraints of enhanced correction number accuracy according to claim 1, characterized in that, The process of correcting the user-end observations to obtain the corrected observation equation includes: Obtain the raw pseudorange observations and raw carrier phase observations from the user terminal; Satellite-based precision correction information is used to correct satellite precision orbit errors and satellite clock errors. Then, the observation domain comprehensive enhancement correction is superimposed to compensate for path errors in pseudorange observations and carrier phase observations, respectively. Based on the compensated pseudorange observations, a corrected pseudorange observation equation is constructed, which includes receiver position terms, residual tropospheric error terms, and residual ionospheric error terms. Based on the compensated carrier phase observations, a corrected carrier phase observation equation is constructed, which includes a receiver position term, a residual tropospheric error term, a residual ionospheric error term, and a carrier phase integer ambiguity term.

6. The seamless satellite-to-ground fusion positioning method based on adaptive constraints of enhanced correction number accuracy according to claim 1, characterized in that, The process of constructing a pseudo-observation equation with the enhanced and corrected residual atmospheric error as zero, and determining the constraint variance of the pseudo-observation equation based on the accuracy information of the comprehensive enhanced correction number of the observation domain, includes: The enhanced and corrected residual atmospheric error includes the enhanced and corrected residual ionospheric error and the enhanced and corrected residual tropospheric error; a pseudo-observation equation for the residual ionospheric error is constructed with the enhanced and corrected residual ionospheric error as zero, and a pseudo-observation equation for the residual tropospheric error is constructed with the enhanced and corrected residual tropospheric error as zero. Based on the spatial interpolation propagation error term and the correction age error term, the residual ionospheric error constraint variance and the residual tropospheric error constraint variance are determined by the mapping function, respectively, and used as the constraint variance of the pseudo-observation equation; When the constraint variance is in a small range, the enhanced and corrected residual atmospheric error is strongly constrained, and the unified positioning model approaches the network RTK model; when the constraint variance is in a large range, the enhanced and corrected residual atmospheric error is released from estimation, and the unified positioning model approaches the satellite-based PPP model.

7. The seamless satellite-to-ground fusion positioning method based on adaptive constraints of enhanced correction number accuracy according to claim 1, characterized in that, The step of performing filtering estimation based on the unified positioning model, the modified observation equation, and the pseudo-observation equation to obtain and output the positioning result includes: Based on the unified positioning model, the corrected observation equation, and the pseudo-observation equation, a filtering estimation is performed to obtain the floating-point solution and its covariance. The floating-point solution and covariance are fixed with integer ambiguity, and the ambiguity-fixed solution is output as the final positioning result.

8. A seamless satellite-to-ground positioning system based on adaptive constraints for enhanced correction accuracy, used to implement the seamless satellite-to-ground positioning method based on adaptive constraints for enhanced correction accuracy as described in claims 1-7, characterized in that... The system includes a server and a user terminal; The server acquires reference station network observation data and satellite-based precision correction information. Under the unified benchmark of satellite-based precision correction information, it generates observation domain comprehensive enhancement correction numbers based on reference station network observation data, and generates accuracy information of observation domain comprehensive enhancement correction numbers. Send satellite-based precision correction information, observation domain integrated enhancement corrections, and accuracy information to the user terminal; The user terminal is used to receive the base precision correction information, the observation domain comprehensive enhancement correction number and accuracy information, and correct the user terminal observation value based on the satellite-based precision correction information and the observation domain comprehensive enhancement correction number to obtain the corrected observation equation; By establishing a unified positioning model, the receiver position, the residual atmospheric error after enhancement correction, and the carrier phase ambiguity are used as parameters to be estimated. A pseudo-observation equation is constructed with the residual atmospheric error after enhancement correction as zero, and the constraint variance of the pseudo-observation equation is determined based on the accuracy information of the comprehensive enhancement correction in the observation domain. The positioning results are obtained and output by filtering estimation based on the unified positioning model, the modified observation equation, and the pseudo-observation equation.

9. A computer device, characterized in that, include: Memory and processor; The memory and the processor are interconnected. The memory stores computer instructions. The processor executes the computer instructions to perform the satellite-ground fusion seamless positioning method based on enhanced correction number accuracy adaptive constraints as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the satellite-ground fusion seamless positioning method based on enhanced correction number accuracy adaptive constraints as described in any one of claims 1 to 7.

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