Inter-station time varying receiver differential code bias estimation method and system for a network of reference stations

Abstract

This invention discloses a method for estimating the inter-station time-varying receiver differential code bias in a reference station network. It constructs an inter-station differential observation equation using observations from reference stations distributed within a region, calculates the time-varying inter-station relative DCB results, and then restores them to the absolute DCB to obtain an accurate time-varying receiver DCB. This method improves the accuracy of ionospheric modeling results and reduces the impact of the pseudorange hardware delay (DCB) of the GNSS receiver on the accuracy of ionospheric modeling.

Description

Technical Field

[0001] This invention belongs to the field of GNSS satellite navigation and near-Earth space environment monitoring, specifically relating to a method and system for estimating differential code bias of time-varying receivers between reference stations in a reference station network. Background Technology

[0002] Ionospheric delay error is a significant factor reducing the positioning accuracy of Global Navigation Satellite System (GNSS). Therefore, it is necessary to model the ionosphere and correct this error during the positioning process using the model. However, since the ionosphere's influence on GNSS signals is frequency-dependent, the ionospheric observations acquired through GNSS include related errors introduced by the hardware circuitry at both the satellite and receiver ends in processing the frequency signals; this is called differential code bias (DCB). To establish a high-precision ionospheric model, high-precision satellite DCB and receiver DCB products are required. Extensive research has been conducted on DCB estimation, including simultaneously estimating receiver and satellite DCB when estimating the global ionospheric model, directly extracting receiver and satellite DCB from observations using existing ionospheric products, and establishing statistical models based on the temporal, spatial, and satellite elevation angle relationships of ionospheric observations for estimation. These methods have yielded high-precision receiver and satellite DCB estimation results, and related products and services have been continuously provided to users over the past 20 years. However, the above estimation method is limited by the continuity of satellite tracking and the discreteness of the distribution of station data. Its application effect is not good in regional distributed stations, especially in city-level reference station networks. This is mainly reflected in the low accuracy of receiver DCB estimation results, which further reduces the accuracy of regional ionospheric modeling results and affects GNSS positioning. Summary of the Invention

[0003] To improve the accuracy of ionospheric modeling results and reduce the impact of pseudorange hardware delay (DCB) of GNSS receivers on ionospheric modeling accuracy, this invention provides an inter-station time-varying receiver differential code bias estimation method for a reference station network. By using the observations of reference stations distributed in the region to construct inter-station differential observation equations, the inter-station relative DCB results that change over time are calculated, and then restored to the absolute DCB to obtain accurate time-varying receiver DCB.

[0004] According to one aspect of the present invention, a method for estimating the differential code offset of an inter-station time-varying receiver in a reference station network is provided, comprising:

[0005] Step 1: Use the receivers within the reference station network to perform non-differential, non-combined precise single-point positioning calculations, collect ionospheric observations of all satellites from all reference stations, and classify them according to the satellites;

[0006] Step 2: Calculate the inter-station differential ionospheric observations of all base stations for the same satellite at the same epoch, and detect and remove outliers and discrepancies in the time series of differential ionospheric observations;

[0007] Step 3: Initialize the model by collecting data within a preset time period to obtain the initial value of the inter-station DCB at the receiver end. At the same time, calculate the absolute receiver-end DCB of each station.

[0008] Step 4: After obtaining the initial value of the inter-station DCB at the receiver, estimate the inter-station DCB using a real-time filtering method;

[0009] Step 5: After obtaining the real-time solution results of the inter-station DCB, restore the inter-station DCB to the absolute DCB of each station based on the absolute receiver-end DCB calculated during initialization, for use in ionospheric modeling.

[0010] As a further technical solution, it is assumed that the receiver-side DCB is time-invariant during the time period described in step three, and the inter-station DCB during the time period is represented by a single parameter.

[0011] As a further technical solution, in step three, the absolute receiver-end DCB of each station is calculated using conventional estimation methods.

[0012] As a further technical solution, in step four, during the process of estimating the inter-station DCB using the real-time filtering method, it is assumed that the inter-station DCB of each epoch is changing, and the inter-station DCB of the previous epoch is used as a constraint.

[0013] As a further technical solution, in step four, the Kalman filtering method is used to estimate the inter-station differential ionospheric delay as a random walk process, and the only parameter to be estimated is the inter-station DCB.

[0014] As a further technical solution, in step five, the absolute DCB of receiver b at epoch k is:

[0015] ,

[0016] in For the absolute receiver terminal DCB of receiver a at epoch t, The time-varying inter-station DCB for receivers a and b at epoch k is estimated in real time.

[0017] According to one aspect of the present invention, an inter-station time-varying receiver differential code offset estimation system for a reference station network is provided, comprising:

[0018] The first main module is used to perform non-differential, non-combined precise single-point positioning calculations using receivers within the reference station network, collect ionospheric observations of all satellites from all reference stations, and classify them according to the satellites.

[0019] The second main module is used to calculate the inter-station differential ionospheric observations of all base stations for the same satellite at the same epoch, and to detect and remove outliers and abnormal values ​​in the time series of differential ionospheric observations.

[0020] The third main module is used to initialize the model by collecting data within a preset time period, obtain the initial value of the inter-station DCB at the receiver end, and at the same time, calculate the absolute receiver end DCB of each station.

[0021] The fourth main module is used to estimate the inter-station DCB using a real-time filtering method after obtaining the initial value of the inter-station DCB at the receiver end.

[0022] The fifth main module is used to restore the inter-station DCB to the absolute DCB of each station based on the absolute receiver-end DCB calculated during initialization after obtaining the real-time solution results of the inter-station DCB, and is used for modeling the ionospheric model.

[0023] According to one aspect of the present invention, a GNSS receiver is provided, including a memory and a processor, wherein the memory stores program instructions that are executed by the processor, and the processor invokes the program instructions to execute the inter-station time-varying receiver differential code offset estimation method of the reference station network.

[0024] According to one aspect of the present invention, a non-transitory computer-readable storage medium is provided, the non-transitory computer-readable storage medium storing computer instructions that cause the computer to execute the inter-station time-varying receiver differential code offset estimation method of the reference station network.

[0025] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0026] 1. This invention constructs an inter-station differential observation equation using observations from reference stations distributed within a region, calculates the time-varying inter-station relative DCB results, and then restores them to the absolute DCB to obtain an accurate time-varying receiver DCB. This improves the accuracy of ionospheric modeling results and reduces the impact of the pseudorange hardware delay (DCB) of the GNSS receiver on the accuracy of ionospheric modeling.

[0027] 2. By utilizing the high-precision inter-station DCB estimates obtained by this invention, after removing the DCB from the ionospheric observations, a more accurate ionospheric TEC observation value that does not contain the influence of DCB can be obtained, thereby improving the accuracy of the ionospheric model. Attached Figure Description

[0028] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0029] Figure 1 This is a flowchart illustrating the method for estimating the differential code deviation of an inter-station time-varying receiver in a reference station network, as provided in an embodiment of the present invention. Detailed Implementation

[0030] Because satellites operate in the stable, low-temperature environment of space for extended periods, and their equipment is sophisticated with advanced manufacturing processes, satellite-side DCB (Distributed DCB) is more stable, generally considered to be stable within a month. However, receiver DCB stability is poor due to various factors such as temperature variations, equipment aging, and firmware upgrades. Current research has revealed that receiver-side DCB varies with ambient temperature, with fluctuations reaching several nanoseconds (ns). Furthermore, satellite-side DCB can be estimated using receivers worldwide and the results can be published, while receiver-side errors can only be estimated by the base station network operators. Therefore, receiver-side DCB has a greater impact on model accuracy during ionospheric modeling, especially since the inter-station DCB of the receivers used for modeling is unstable. This instability can lead to a reduction in the accuracy of a unified regional ionospheric model due to DCB variations between different receivers, severely impacting its application in GNSS positioning.

[0031] Based on the aforementioned situation, this invention discloses a method for estimating the inter-station time-varying receiver differential code bias in a reference station network. This method constructs inter-station differential observation equations using observations from reference stations distributed within the region, calculates the time-varying inter-station relative DCB results, and then restores them to the absolute DCB to obtain an accurate time-varying receiver DCB. This method improves the accuracy of ionospheric modeling results and reduces the impact of the pseudorange hardware delay (DCB) of the GNSS receiver on the accuracy of ionospheric modeling.

[0032] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. In addition, the technical features of the various embodiments or individual embodiments provided by the present invention can be arbitrarily combined to form new technical solutions. Such combinations are not bound by the order of steps and / or structural composition patterns, but must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.

[0033] See appendix Figure 1 The present invention provides a method for estimating the differential code deviation of an inter-station time-varying receiver in a reference station network, comprising the following steps:

[0034] Step 1: Use the receivers within the reference station network to perform un-differenced and un-combined precise point positioning (UDUC PPP) calculations, collect ionospheric observations from all receivers for all satellites, and classify them according to the satellites.

[0035] Step 2: Calculate the inter-station differential ionospheric observations of all base stations at the same epoch for the same satellite observations, and detect and remove outliers and abnormal values ​​in the time series of differential ionospheric observations.

[0036] Step 3: Initialize the model by collecting data over a period of time. During this period, it is assumed that the receiver-side DCB is time-invariant; therefore, the inter-station DCB within this timeframe is represented by a single parameter. Simultaneously, using conventional estimation methods, calculate the absolute receiver-side DCB for each station, facilitating the conversion of inter-station DCB to absolute DCB during use.

[0037] Step 4: After obtaining the initial value of the inter-station DCB at the receiver, the inter-station DCB is estimated using a real-time filtering method. In this process, it is assumed that the inter-station DCB changes in each epoch. At the same time, in order to ensure the continuity of the inter-station DCB, the inter-station DCB of the previous epoch is used as a constraint.

[0038] Step 5: After obtaining the real-time solution results, the inter-station DCB is restored to the absolute DCB of each station based on the absolute receiver DCB calculated during initialization, and used for ionospheric modeling.

[0039] In the above technical solution, the specific operation method for step one, which involves using receivers within the reference station network to perform UDUC PPP calculation, collecting ionospheric observations from all receivers for all satellites, and classifying them according to satellites, is as follows:

[0040] During the UDUC PPP solution process, the reconstructed observation equation of receiver r for satellite s at time t is as follows:

[0041]

[0042] In the observation equation and These represent pseudorange and carrier observations, respectively, where i represents the frequency point. This represents the frequency of frequency point i. and These are the reconstructed receiver and satellite clock bias, respectively. This represents the ratio of frequency point i to the reference frequency point. Indicates the oblique ionospheric delay error. The deionization combination factor is... and These represent the receiver and the satellite DCB, respectively. This represents the tropospheric delay projection factor, where T is the tropospheric delay. This represents the floating-point ambiguity of frequency point i. Using the Extended Kalman Filter (EKF), high-precision ionospheric observations including the DCB can be calculated from all satellite observations of a single station. .

[0043] The ionospheric observations were obtained through calculation. Then, they were classified according to different satellites, resulting in... , , These are used for subsequent calculations.

[0044] Step two involves calculating the inter-station differential ionospheric observations of all base stations for the same satellite at the same epoch, and detecting and removing outliers and discrepancies in the time series of these differential ionospheric observations. The specific operation method is as follows:

[0045] Calculate the signal from receiver r to a satellite s at the same epoch. The difference, according to the formula in equation (1), can be obtained as the difference between the ionospheric observations of receivers a and b.

[0046]

[0047] Equation (2) shows that after calculating the difference, the satellite DCB is eliminated, leaving only the receiver-side inter-station DCB and the inter-station oblique ionospheric delay difference. Considering that the change in the receiver's inter-station DCB should be relatively gradual and the change in the ionosphere is continuous, the difference error in the inter-station ionospheric observations can be obtained through time series analysis. The median absolute deviation (MAD) in the sliding window can effectively detect gross errors in the sequence. Here, the sliding window size is 1 hour. The data after removing the gross errors can be used for subsequent calculation of the inter-station DCB.

[0048] Step three involves initializing the model by collecting data over a period of time. During this time period, it is assumed that the receiver-side DCB is time-invariant; therefore, the inter-station DCB within this period is represented by a single parameter. Simultaneously, using conventional estimation methods, the absolute receiver-side DCB for each station is calculated, facilitating the conversion of inter-station DCB to absolute DCB during use. The specific operation method is as follows:

[0049] First, since the distance between the satellite and the ground is approximately 20,000 kilometers, and the distance between stations is no more than 100 kilometers, it is assumed that the satellite signals observed by receivers a and b are parallel. Therefore, the elevation angle has the same effect on the ionosphere of receivers a and b. Here, only the effect of the distance between the two stations on the inter-station differential ionospheric delay is considered. Statistically, it is assumed that the TEC differs by 0.5 TECU for every 100 km increase in distance. Therefore, it is assumed that the inter-station differential ionospheric delay follows a zero-mean normal distribution.

[0050]

[0051] in, This represents the distance between the puncture points of the observations of receivers a and b to satellite s, in km. Inter-station DCB estimation will use a station located at the center of the baseline network as the reference, assumed to be [reference station name missing]. The parameters to be estimated are respectively , The inter-station DCB. Using the above observations and the stochastic model, equations were constructed to obtain...

[0052]

[0053] The residuals of the equation follow the distribution shown in equation (3) above. Using the weighted least squares method, the parameters to be estimated are obtained. for

[0054]

[0055] The initial DCB values ​​for the receiver can be obtained by solving the above equation using baseline station network observation data from a continuous 8-hour nighttime period (e.g., 8 PM to 4 AM the next day). Then, the receiver absolute DCB is estimated using conventional methods, selecting ionospheric model products and satellite DCB products from the aforementioned nighttime period, based on ionospheric observations. The ionospheric slant path delay and satellite DCB are directly removed, and the average value is calculated to obtain the receiver absolute DCB, as follows:

[0056]

[0057] in, This represents the oblique ionospheric delay between the receiver r and the satellite s at epoch t, ​​estimated using the ionospheric model product. This represents the DCB of satellite s obtained from the product, where n is the number of observations.

[0058] After obtaining the initial value of the inter-station DCB at the receiver end as described in step four, the inter-station DCB is estimated using a real-time filtering method. In this process, it is assumed that the inter-station DCB changes at each epoch. At the same time, in order to ensure the continuity of the inter-station DCB, the inter-station DCB of the previous epoch is used as a constraint. The specific implementation method is as follows:

[0059] After obtaining the initial values ​​of the inter-station DCB for each receiver, the time-varying inter-station DCB can be estimated using real-time data. The Kalman filter method is used, treating the inter-station differential ionospheric delay as a random walk process for estimation. Since only the inter-station DCB is among the parameters to be estimated, the filtering equation is:

[0060]

[0061] in, The definition is the same as in equation (4), where DCB is the inter-station DCB of the receiver to be estimated for epoch k. Compared with equation (4), constraints have been added to the existing ones. and The format is as follows

[0062]

[0063] The current time-varying DCB between stations can be calculated in real time using Kalman filtering.

[0064] After obtaining the real-time solution results as described in step five, the inter-station DCB is restored to the absolute DCB of each station based on the absolute receiver DCB calculated during initialization. The specific implementation method for modeling the ionospheric model is as follows:

[0065] The time-varying inter-station DCB obtained in step four can be converted into a time-varying absolute DCB by combining it with the receiver absolute DCB obtained in step three. The method is as follows:

[0066]

[0067] in The absolute DCB of receiver b at epoch k. Same as equation (6), The time-varying inter-station DCB at epoch k is estimated by equation (7). After obtaining the absolute DCB, accurate ionospheric delay observations without the influence of satellite and receiver DCB can be extracted, and a high-precision ionospheric model can be established.

[0068] The implementation of the various embodiments of the present invention is based on programmed processing by a device with processor functionality. Therefore, in practical engineering, the technical solutions and functions of the various embodiments of the present invention are encapsulated into various modules. Based on this reality, and building upon the above embodiments, the embodiments of the present invention provide an inter-station time-varying receiver differential code offset estimation system for a reference station network. This system is used to execute the inter-station time-varying receiver differential code offset estimation method for a reference station network in the above method embodiments.

[0069] The system comprises: a first main module, used to perform non-differential, non-combined precise single-point positioning calculations using receivers within the reference station network, collecting ionospheric observations from all reference stations for all satellites, and classifying them according to satellites; a second main module, used to calculate inter-station differential ionospheric observations from all base stations for the same satellite at the same epoch, and to detect and remove outliers and gross errors in the time series of differential ionospheric observations; a third main module, used to initialize the model by collecting data within a preset time period, obtaining the initial value of the inter-station DCB at the receiver end, and simultaneously calculating the absolute receiver-end DCB for each station; a fourth main module, used to estimate the inter-station DCB using a real-time filtering method after obtaining the initial value of the inter-station DCB at the receiver end; and a fifth main module, used to restore the inter-station DCB to the absolute DCB of each station based on the absolute receiver-end DCB calculated during initialization after obtaining the real-time calculation result of the inter-station DCB, for modeling the ionospheric model.

[0070] The time-varying receiver differential code bias estimation system for a reference station network provided in this invention addresses the problem that existing estimation methods are limited by the continuity of satellite tracking and the discreteness of data distribution between stations, resulting in poor application performance in regionally distributed stations, especially in city-level reference station networks. By employing the aforementioned modules, the system constructs inter-station differential observation equations using observations from reference stations distributed within the region, calculates the time-varying inter-station relative DCB results, and then restores them to the absolute DCB to obtain accurate time-varying receiver DCB.

[0071] It should be noted that the system embodiments provided by this invention, in addition to implementing the methods in the above method embodiments, are also used to implement the methods in other method embodiments provided by this invention. The difference lies only in setting corresponding functional modules, and their principles are basically the same as those of the above system embodiments provided by this invention. As long as those skilled in the art, based on the above system embodiments and referring to the specific technical solutions in other method embodiments, obtain corresponding technical means and technical solutions composed of these technical means by combining technical features, and improve the modules in the above system embodiments while ensuring the practicality of the technical solutions, they can obtain corresponding system-like embodiments for implementing the methods in other method-like embodiments. For example:

[0072] Based on the above system embodiments, as a preferred embodiment, the inter-station time-varying receiver differential code deviation estimation system for the reference station network provided in this embodiment of the invention, wherein the third main module is further configured to execute the following instructions: assuming that the receiver-end DCB is time-invariant during the time period, the inter-station DCB during the time period is represented by a parameter.

[0073] Based on the above system embodiments, as a preferred embodiment, the inter-station time-varying receiver differential code deviation estimation system for the reference station network provided in this embodiment of the invention, wherein the third main module is further configured to execute the following instructions: calculate the absolute receiver end DCB of each station using conventional estimation methods.

[0074] Based on the above system embodiments, as a preferred embodiment, the inter-station time-varying receiver differential code deviation estimation system for the reference station network provided in this embodiment of the invention, wherein the fourth main module is further configured to execute the following instructions: in the process of estimating the inter-station DCB using a real-time filtering method, it is assumed that the inter-station DCB of each epoch is changing, and the inter-station DCB of the previous epoch is used as a constraint.

[0075] Based on the above system embodiments, as a preferred embodiment, the inter-station time-varying receiver differential code deviation estimation system for the reference station network provided in this embodiment of the invention, wherein the fourth main module is further configured to execute the following instructions: using the Kalman filtering method, the inter-station differential ionospheric delay is estimated as a random walk process, and the parameters to be estimated only include the inter-station DCB.

[0076] Based on the above system embodiments, as a preferred embodiment, the inter-station time-varying receiver differential code deviation estimation system for a reference station network provided in this embodiment of the invention, wherein the fifth main module is further configured to execute the following instructions: the absolute DCB of receiver b at epoch k is

[0077] ,

[0078] in For the absolute receiver terminal DCB of receiver a at epoch t, The time-varying inter-station DCB for receivers a and b at epoch k is estimated in real time.

[0079] Based on the same inventive concept as the foregoing embodiments, this embodiment of the invention also provides a GNSS receiver, including a memory and a processor. The memory stores program instructions that are executed by the processor. The processor calls the program instructions to execute the inter-station time-varying receiver differential code offset estimation method of the reference station network.

[0080] In embodiments of the present invention, the memory can be non-volatile memory, such as a hard disk drive (HDD) or a solid-state drive (SSD), or it can be volatile memory, such as random-access memory (RAM). Memory is any other medium capable of carrying or storing desired program code having an instruction or data structure form and accessible by a computer, but is not limited thereto. The memory in embodiments of the present invention can also be a circuit or any other device capable of implementing a storage function for storing program instructions and / or data.

[0081] In this embodiment of the invention, the processor may be a general-purpose processor, a digital signal processor, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in this embodiment of the invention. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in this embodiment of the invention can be directly manifested as being executed by a hardware processor, or executed by a combination of hardware and software modules within the processor.

[0082] Based on the same inventive concept as the foregoing embodiments, this embodiment of the invention also provides a non-transitory computer-readable storage medium storing computer instructions. These computer instructions cause the computer to execute the inter-station time-varying receiver differential code offset estimation method for the reference station network, including:

[0083] Step 1: Use the receivers within the reference station network to perform non-differential, non-combined precise single-point positioning calculations, collect ionospheric observations from all reference stations and all satellite pairs, and classify them according to the satellites.

[0084] Step 2: Calculate the inter-station differential ionospheric observations of all base stations for the same satellite at the same epoch, and detect and remove outliers and abnormal values ​​in the time series of differential ionospheric observations.

[0085] Step 3: Initialize the model by collecting data over a period of time. During this period, it is assumed that the receiver-side DCB is time-invariant; therefore, the inter-station DCB within this timeframe is represented by a single parameter. Simultaneously, using conventional estimation methods, calculate the absolute receiver-side DCB for each station, facilitating the conversion of inter-station DCB to absolute DCB during use.

[0086] Step 4: After obtaining the initial value of the inter-station DCB at the receiver, the inter-station DCB is estimated using a real-time filtering method. In this process, it is assumed that the inter-station DCB changes in each epoch. At the same time, in order to ensure the continuity of the inter-station DCB, the inter-station DCB of the previous epoch is used as a constraint.

[0087] Step 5: After obtaining the real-time solution results, the inter-station DCB is restored to the absolute DCB of each station based on the absolute receiver DCB calculated during initialization, and used for ionospheric modeling.

[0088] In summary, this invention discloses a method for obtaining accurate time-varying receiver DCB by constructing inter-station differential observation equations using observations from reference stations distributed within a region, calculating time-varying inter-station relative DCB results, and then restoring them to absolute DCB. This method improves the accuracy of ionospheric modeling results and reduces the impact of pseudorange hardware delay (DCB) of GNSS receivers on the accuracy of ionospheric modeling.

[0089] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the technical solutions of the embodiments of the present invention.

Claims

1. A method for estimating the differential code bias of inter-station time-varying receivers in a reference station network, characterized in that, include: Step 1: Use the receivers within the reference station network to perform non-differential, non-combined precise single-point positioning calculations, collect ionospheric observations of all satellites from all reference stations, and classify them according to the satellites; Step 2: Calculate the inter-station differential ionospheric observations of all base stations for the same satellite at the same epoch, and detect and remove outliers and discrepancies in the time series of differential ionospheric observations; Step 3: Initialize the model by collecting data within a preset time period to obtain the initial value of the inter-station DCB at the receiver end. At the same time, calculate the absolute receiver end DCB of each station. It is assumed that the receiver end DCB is time-invariant within the time period, and the inter-station DCB within the time period is represented by a single parameter. Step 4: After obtaining the initial value of the inter-station DCB at the receiver end, the inter-station DCB is estimated using a real-time filtering method. In the process of estimating the inter-station DCB using the real-time filtering method, it is assumed that the inter-station DCB of each epoch is changing, and the inter-station DCB of the previous epoch is used as a constraint. Step 5: After obtaining the real-time solution results of the inter-station DCB, restore the inter-station DCB to the absolute DCB of each station based on the absolute receiver-end DCB calculated during initialization, for use in ionospheric modeling.

2. The method for estimating the differential code deviation of the inter-station time-varying receiver in the reference station network according to claim 1, characterized in that, In step three, the absolute receiver DCB of each station is calculated using the following method: Select the ionospheric model product and satellite DCB product within the preset time period used for initialization, directly remove the ionospheric slant path delay and satellite DCB from the ionospheric observations, and calculate the average value to obtain the absolute receiver DCB.

3. The method for estimating the differential code deviation of inter-station time-varying receivers in a reference station network according to claim 1, characterized in that, In step four, the Kalman filter method is used to estimate the inter-station differential ionospheric delay as a random walk process, and the only parameter to be estimated is the inter-station DCB.

4. The method for estimating the differential code deviation of the inter-station time-varying receiver in the reference station network according to claim 1, characterized in that, In step five, the absolute DCB of receiver b at epoch k is: ， in For the absolute receiver terminal DCB of receiver a at epoch t, The time-varying inter-station DCB for receivers a and b at epoch k is estimated in real time.

5. A differential code offset estimation system for inter-station time-varying receivers in a reference station network, characterized in that, include: The first main module is used to perform non-differential, non-combined precise single-point positioning calculations using receivers within the reference station network, collect ionospheric observations of all satellites from all reference stations, and classify them according to the satellites. The second main module is used to calculate the inter-station differential ionospheric observations of all base stations for the same satellite at the same epoch, and to detect and remove outliers and abnormal values ​​in the time series of differential ionospheric observations. The third main module is used to initialize the model by collecting data within a preset time period, obtain the initial value of the inter-station DCB at the receiver end, and calculate the absolute receiver end DCB of each station. It is assumed that the receiver end DCB is time-invariant within the time period, and the inter-station DCB within the time period is represented by a single parameter. The fourth main module is used to estimate the inter-station DCB using a real-time filtering method after obtaining the initial value of the inter-station DCB at the receiver end. In the process of estimating the inter-station DCB using the real-time filtering method, it is assumed that the inter-station DCB of each epoch is changing, and the inter-station DCB of the previous epoch is used as a constraint. The fifth main module is used to restore the inter-station DCB to the absolute DCB of each station based on the absolute receiver-end DCB calculated during initialization after obtaining the real-time solution results of the inter-station DCB, and is used for modeling the ionospheric model.

6. A GNSS receiver, characterized in that, It includes a memory and a processor, the memory storing program instructions that are executed by the processor, and the processor calling the program instructions to execute the inter-station time-varying receiver differential code offset estimation method for the reference station network according to any one of claims 1 to 4.

7. A non-transitory computer-readable storage medium, characterized in that, The non-transitory computer-readable storage medium stores computer instructions that cause the computer to execute the inter-station time-varying receiver differential code offset estimation method for the reference station network as described in any one of claims 1 to 4.

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