Troposphere delay correction method and system, electronic equipment and storage medium

Abstract

The invention provides a troposphere delay correction method and system, electronic equipment and a storage medium, and the method comprises the steps: extracting troposphere delay of a reference station through a non-difference combination observation value method according to the obtained real-time reference station observation data, broadcast ephemeris, ultra-fast orbit and clock correction, carrying out the adjustment of observation values of a plurality of satellites, and carrying out the adjustment of the observation values of a plurality of satellites; the zenith troposphere delay of the base station is obtained; the zenith troposphere level of the base station after normalization processing is interpolated to the position of the moving station through an inverse distance weighted interpolation method, zenith troposphere delay of the moving station is obtained according to a pre-constructed elevation normalization model, and the elevation normalization model is constructed based on ERA5 horizontal atmospheric layer meteorological data. According to the method, the adaptability of the model to complex terrains can be improved, so that the model precision is improved, the precision single-point positioning convergence time of the moving station is effectively shortened, and the precision single-point positioning precision is improved.

Description

Technical Field

[0001] The present application belongs to the field of satellite navigation technology, and in particular relates to a tropospheric delay correction method, system, electronic device and storage medium. Background Art

[0002] The Global Navigation Satellite System (GNSS) serves as the core foundation of modern positioning technology. Its positioning accuracy is directly related to key areas such as geographic information acquisition and disaster monitoring. Atmospheric delay is one of the main sources of error in Precise Point Positioning (PPP). Tropospheric delay, due to its non-dispersive nature and complex meteorological correlations, is a key challenge in error correction.

[0003] Traditional tropospheric delay correction methods rely primarily on empirical models, but these models suffer from insufficient accuracy in real-time applications. While GNSS base stations currently provide highly accurate tropospheric delay products, their limited coverage makes them difficult to apply directly to target areas far from the base stations. Inadequate spatial representation in both horizontal and vertical directions leads to a significant decrease in correction accuracy in areas with high elevation differences. Summary of the Invention

[0004] In view of this, the present application aims to propose a tropospheric delay correction method, system, electronic device and storage medium to solve the problem of low tropospheric delay accuracy.

[0005] To achieve the above objectives, the technical solution of this application is implemented as follows:

[0006] In a first aspect, the present application provides a tropospheric delay correction method, comprising:

[0007] Based on the acquired real-time reference station observation data, broadcast ephemeris, ultra-rapid orbit and clock error, the tropospheric delay of the reference station is extracted by the non-differenced combined observation method, and the observations of multiple satellites are adjusted to obtain the zenith tropospheric delay of the reference station.

[0008] The normalized zenith tropospheric delay of the reference station is horizontally interpolated to the mobile station position by the inverse distance weighted interpolation method, and the zenith tropospheric delay of the mobile station is obtained according to the pre-constructed elevation normalization model, wherein the elevation normalization model is constructed based on the ERA5 horizontal pressure layer meteorological data.

[0009] In a second aspect, based on the same inventive concept, the present application also provides a tropospheric delay correction system, comprising:

[0010] The first delay module is configured to extract the tropospheric delay of the reference station based on the acquired real-time reference station observation data, broadcast ephemeris, ultra-rapid orbit and clock error by using a non-differenced combined observation value method, and adjust the observation values ​​of multiple satellites to obtain the zenith tropospheric delay of the reference station;

[0011] The second delay module is configured to horizontally interpolate the normalized zenith tropospheric delay of the reference station to the mobile station position through the inverse distance weighted interpolation method, and obtain the zenith tropospheric delay of the mobile station according to a pre-constructed elevation normalization model, wherein the elevation normalization model is constructed based on the ERA5 horizontal pressure layer meteorological data.

[0012] In a third aspect, based on the same inventive concept, the present application also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in the first aspect when executing the program.

[0013] In a fourth aspect, based on the same inventive concept, the present application also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the method described in the first aspect.

[0014] Compared with the prior art, the tropospheric delay correction method, system, electronic device, and storage medium described in this application have the following beneficial effects:

[0015] The tropospheric delay correction method described in this application can improve the adaptability of the model to complex terrain, thereby improving the model accuracy, effectively shortening the convergence time of the precise single-point positioning of the mobile station, and improving the precise single-point positioning accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of this application. The exemplary embodiments and descriptions of this application are intended to explain this application and do not constitute an improper limitation on this application. In the accompanying drawings:

[0017] Figure 1 This is a flow chart of a tropospheric delay correction method described in an embodiment of the present application;

[0018] Figure 2 This is a schematic structural diagram of a tropospheric delay correction device according to an embodiment of the present application;

[0019] Figure 3 This is a schematic diagram of the hardware structure of the electronic device described in an embodiment of the present application. DETAILED DESCRIPTION

[0020] In order to make the objectives, technical solutions and advantages of this application more clear, this application is further described in detail below in combination with specific embodiments and with reference to the accompanying drawings.

[0021] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present application should have the usual meanings understood by people with ordinary skills in the field to which this application belongs. The "first", "second" and similar words used in the embodiments of the present application do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0022] The embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0023] See also Figure 1 As shown, this embodiment provides a tropospheric delay correction method, including the following steps:

[0024] Step S101: Based on the acquired real-time reference station observation data, broadcast ephemeris, ultra-rapid orbit and clock error, the tropospheric delay of the reference station is extracted by a non-differenced combined observation method, and the observation values ​​of multiple satellites are adjusted to obtain the zenith tropospheric delay of the reference station;

[0025] Step S102: The normalized zenith tropospheric delay of the reference station is horizontally interpolated to the rover position using the inverse distance weighted interpolation method, and the zenith tropospheric delay of the rover is obtained based on a pre-built elevation normalization model, wherein the elevation normalization model is constructed based on the ERA5 horizontal pressure layer meteorological data.

[0026] Specifically, in this embodiment, ERA5 horizontal pressure layer meteorological data (including air pressure, temperature, potential and relative humidity) are read, and the integration method is used to obtain the ZTD (Zenith Total Delay) of each grid point. The Zenith Total Delay (ZTD) consists of the Zenith Still Delay (ZHD) and the Zenith Wet Delay (ZWD), which is an important factor leading to the precise positioning error of the Global Navigation Satellite System (GNSS) Precise Point Positioning (PPP) and real-time positioning.

[0027] For the ZTD obtained from ERA5, a piecewise negative exponential function is used for fitting. The ZTD and elevation normalization parameters of each grid point at each time are calculated. Trigonometric functions and spherical harmonic functions are then used for fitting. The model parameters are stored in the form of a grid to obtain an elevation normalization model. Using real-time reference station observation data, broadcast ephemeris, ultra-rapid orbits and clock errors, the undifferenced combined observation method is used to estimate the tropospheric delay of the reference station. The observations of multiple satellites are adjusted to obtain the zenith tropospheric delay of the reference station. The zenith tropospheric delay of the mobile station is obtained using the elevation normalization model and horizontal interpolation. The specific steps are as follows:

[0028] Step 201: Establishing an elevation normalization model using ERA5 data, specifically including:

[0029] Download the ERA5 hourly data of the reanalysis data for the past five years from the ECMWF official website. The data contains four-dimensional grid data of pressure, temperature, potential and relative humidity. Calculate the refractive index of each pressure layer per hour according to formula (1): , grid resolution 0.25°×0.25°, total 37 layers, where =77.604K / hPa, =64.79K / hPa, =377600K 2 / hPa; and Represents air pressure and water vapor pressure respectively, unit is hPa; Indicates temperature, unit ; The ZTD value above each pressure layer is obtained by integrating formula (2), Indicates altitude.

[0030] (1)

[0031] (2)

[0032] According to the piecewise negative exponential function formula (3), the ZTD variation characteristics of the grid points in the vertical direction are fitted, and the least squares method is used to obtain the piecewise negative exponential function parameters, where , and They represent the ZTD values ​​of the reference height in different elevation intervals respectively; , and are the elevation normalization parameters of ZTD respectively; Indicates the reference altitude.

[0033] (3)

[0034] The ZTD parameter time series in different altitude intervals are fitted using trigonometric functions, as shown in formula (4), where doy represents the accumulated days per year and hour represents UTC time.

[0035] (4)

[0036] In the formula, the annual and daily periodic phases are parameterized, and the parameters are converted to ( =0, 1, 2…8) to perform spherical harmonic expansion, as shown in Equation (5), and the least squares method is used to solve the model coefficients.

[0037] (5)

[0038] in, represents Legendre polynomials; and are the latitude and longitude of the measuring station respectively; and are the spherical harmonics determined using least squares Step sub-coefficient; order Control the resolution and order of spherical harmonics in the latitude direction Controls the resolution of spherical harmonics in the longitude direction; The highest order of the spherical harmonic function expansion determines the complexity and spatial resolution of the model, and is generally selected to be 10-20.

[0039] Taking advantage of the fact that the elevation normalization parameters have an annual cycle variation trend, the wavelet transform method of time-frequency analysis is used to capture the short-term high frequency and long-term low frequency characteristics of the elevation normalization parameters and construct a parameter model.

[0040] First, the hourly data are detrended and standardized as shown in formula (6).

[0041] (6)

[0042] in, is the elevation normalization parameter; represents the normalized time in a year in hours, i.e. ; and are the slope and intercept of the linear trend obtained by least squares fitting; is the normalized parameter of elevation after detrending; is the mean after detrending; is the standard deviation after detrending; is the normalized elevation parameter after standardization.

[0043] Next, Morlet wavelet was selected for multi-scale analysis, and CWT was used to calculate Parameters are obtained, and the annual, semi-annual, and daily periods are extracted. The specific frequency band signals are extracted and reconstructed by wavelet, as shown in formula (7).

[0044] (7)

[0045] in, is the input elevation normalization parameter; is the Morlet wavelet basis function; and and translation parameters respectively; W( , ) is the wavelet coefficient, indicating the signal at scale and time Energy intensity under is the center frequency, usually 6; is the wavelet admissible constant, is the normalized parameter of the reconstructed elevation.

[0046] Finally, the final normalized parameter model is expressed using the multi-scale model expression, as shown in formula (8).

[0047] (8)

[0048] in, is the annual cycle component; is the half-year cycle component; is the daily cycle component; is the residual noise.

[0049] Step S202, estimating real-time tropospheric delay based on the GNSS station, specifically includes:

[0050] The non-differential combination method directly extracts the tropospheric delay information of the observation station by processing the GNSS observation data. The core idea is to use the combination of carrier phase and pseudorange observations to eliminate or weaken other error sources (such as ionospheric delay and satellite clock error), thereby extracting the tropospheric delay. Equation (9) shows the observation equation of the ionospheric-free combined GNSS through the linear combination of pseudorange (P) and carrier phase (L).

[0051] (9)

[0052] in, is the ionospheric-free combined observation value ( or ); is the geometric distance; is the speed of light; and are the receiver and satellite clock errors respectively; is the tropospheric delay; is the equivalent wavelength of the ionosphere-free combination; is the integer ambiguity of the ionospheric-free combination; is the observation noise of the ionosphere-free combination.

[0053] The zenith tropospheric delay of the reference station is extracted by the non-differential combination method. To further improve the accuracy, the observation values ​​of multiple satellites are adjusted to obtain the zenith tropospheric delay ZTD of the station, as shown in formula (10).

[0054] (10)

[0055] Where n is the number of visible satellites; is the zenith distance of satellite s.

[0056] Step S203: rover tropospheric delay correction, specifically including:

[0057] After obtaining the real-time tropospheric delays of different reference stations using the pseudorange carrier data and broadcast ephemeris, ultra-rapid orbit, and clock error of the base station in step S202, they are converted into the elevation-normalized zenith tropospheric delays according to formulas (3) and (4) so ​​as to interpolate between stations at different elevations.

[0058] The normalized ZTD of the reference station is interpolated to the rover position using the inverse distance weighted interpolation method. The inverse distance weighting is shown in formula (11). Then, the zenith tropospheric delay of the rover is calculated based on the height normalization model.

[0059] (11)

[0060] Where, is the ZTD value of the point to be interpolated; is the distance weight; is the ZTD value of the i-th base station;

[0061] After obtaining the zenith tropospheric delay of the mobile station, it needs to be mapped to the slant path tropospheric delay (STD) on the satellite signal propagation path. The mapping function usually adopts the Niell model, global mapping function (GMF) or tropospheric mapping model (VMF).

[0062] The calculated slant path tropospheric delay (STD) is used as a correction term and applied to the GNSS observation equation of the mobile station to improve the positioning accuracy, as shown in formula (12).

[0063] (12)

[0064] in, and are the zenith static delay and the zenith wet delay; and are the static delay mapping function and the wet delay mapping function.

[0065] Step S204, accuracy verification, specifically includes:

[0066] Taking the IGS stations HKSL, HKWS, JFNG, URUM, and WUH2 as examples, the IGS station was used as a rover station, and stations within 50 km of it were selected as reference stations. The positioning accuracy of the commonly used tropospheric delay model GPT3 and the patented elevation normalization model was analyzed on July 1, 2021. Using the station center coordinate system as the reference, the accuracy of the coordinates solved by precise single-point positioning in the east, north, and elevation directions (i.e., the E, N, and U directions) was evaluated. The average model error is shown in Table 1.

[0067] Table 1 Average errors (cm) of the height normalization model and the GPT3 model in the E, N, and U directions

[0068]

[0069] Table 1 shows that the horizontal correction effects of the elevation normalization model and the GPT3 model are roughly equivalent in precise point positioning. Positioning accuracy is significantly improved in the elevation direction, with an average improvement of approximately 44.6%. This demonstrates that the real-time tropospheric correction method proposed in this application can improve the accuracy of station precise point positioning.

[0070] Therefore, the method described in this embodiment combines ERA5 hourly horizontal resolution barosphere meteorological data to construct an elevation normalization model; based on the reference station observation data, broadcast ephemeris, ultra-rapid orbit and clock error, a non-differential combination method is used to obtain high-precision tropospheric delay information, and the observation values ​​of multiple satellites are adjusted to obtain the zenith tropospheric delay of the reference station; based on the zenith tropospheric delay of the reference station, the elevation normalization model and horizontal interpolation are used to obtain the zenith tropospheric delay of the mobile station; this method effectively improves the precise single-point positioning accuracy of the mobile station and shortens the positioning convergence time.

[0071] The method described in this embodiment can improve the adaptability of the model to complex terrain, thereby improving the model accuracy, effectively shortening the convergence time of the precise single-point positioning of the mobile station, and improving the precise single-point positioning accuracy.

[0072] It should be noted that the above description is limited to some embodiments of the present application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in an order different from that described in the above embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0073] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, an embodiment of the present application further provides a tropospheric delay correction system.

[0074] like Figure 2 As shown, the tropospheric delay correction system includes:

[0075] The first delay module 11 is configured to extract the tropospheric delay of the reference station based on the acquired real-time reference station observation data, broadcast ephemeris, ultra-rapid orbit and clock error by using a non-differenced combined observation value method, and adjust the observation values ​​of multiple satellites to obtain the zenith tropospheric delay of the reference station;

[0076] The second delay module 12 is configured to horizontally interpolate the normalized zenith tropospheric delay of the reference station to the mobile station position through the inverse distance weighted interpolation method, and obtain the zenith tropospheric delay of the mobile station according to a pre-constructed elevation normalization model, wherein the elevation normalization model is constructed based on the ERA5 horizontal pressure layer meteorological data.

[0077] For the convenience of description, the above system is described as being divided into various modules according to their functions. Of course, when implementing the embodiments of the present application, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0078] The system of the above embodiment is used to implement the corresponding method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be described in detail here.

[0079] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, an embodiment of the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and runnable on the processor, wherein when the processor executes the program, the method described in any of the above embodiments is implemented.

[0080] Figure 310 is a schematic diagram showing a more specific hardware structure of an electronic device provided in this embodiment. The device may include: a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040 are communicatively connected to each other within the device via the bus 1050.

[0081] The processor 1010 can be implemented using a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0082] The memory 1020 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage devices, dynamic storage devices, etc. The memory 1020 can store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 1020 and is called and executed by the processor 1010.

[0083] The input / output interface 1030 is used to connect to an input / output module to enable information input and output. The input / output module can be configured as a component within the device (not shown) or can be externally connected to the device to provide corresponding functions. Input devices may include a keyboard, mouse, touch screen, microphone, various sensors, etc. Output devices may include a display, speaker, vibrator, indicator light, etc.

[0084] The communication interface 1040 is used to connect to a communication module (not shown) to enable communication between the device and other devices. The communication module can communicate via wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, Wi-Fi, Bluetooth, etc.).

[0085] The bus 1050 comprises a pathway for transmitting information between various components of the device, such as the processor 1010 , the memory 1020 , the input / output interface 1030 , and the communication interface 1040 .

[0086] It should be noted that although the above device only shows the processor 1010, the memory 1020, the input / output interface 1030, the communication interface 1040, and the bus 1050, in a specific implementation, the device may also include other components necessary for normal operation. In addition, it will be understood by those skilled in the art that the above device may only include the components necessary to implement the embodiments of this specification, and does not necessarily include all the components shown in the figure.

[0087] The electronic device of the above embodiment is used to implement the corresponding method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be described in detail here.

[0088] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, the present application also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the method described in any of the above embodiments.

[0089] The computer-readable media of this embodiment includes permanent and non-permanent, removable and non-removable media that can be used to store information by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, tape disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0090] The computer instructions stored in the storage medium of the above embodiment are used to enable the computer to execute the method described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0091] Those skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present application (including the claims) is limited to these examples. Within the scope of the present application, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the embodiments of the present application as described above, which are not provided in detail for the sake of simplicity.

[0092] In addition, to simplify the description and discussion, and to avoid obscuring the understanding of the embodiments of the present application, well-known power / ground connections to integrated circuit (IC) chips and other components may or may not be shown in the provided figures. Furthermore, devices may be shown in block diagram form to avoid obscuring the understanding of the embodiments of the present application, and this also takes into account the fact that the implementation details of these block diagram devices are highly dependent on the platform on which the embodiments of the present application will be implemented (i.e., these details should be fully understood by those skilled in the art). Where specific details (e.g., circuits) are set forth to describe the exemplary embodiments of the present application, it will be apparent to those skilled in the art that the embodiments of the present application can be implemented without these specific details or with variations therefrom. Therefore, these descriptions should be considered illustrative rather than restrictive.

[0093] Although the present invention has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of these embodiments will be apparent to those skilled in the art based on the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may utilize the discussed embodiments.

[0094] The embodiments of the present application are intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present application should be included in the scope of protection of this application.

Claims

1. A tropospheric delay correction method, characterized in that: include: Based on the acquired real-time reference station observation data, broadcast ephemeris, ultra-rapid orbit and clock error, the tropospheric delay of the reference station is extracted by the non-differenced combined observation method, and the observations of multiple satellites are adjusted to obtain the zenith tropospheric delay of the reference station. The normalized zenith tropospheric delay of the reference station is horizontally interpolated to the rover position by the inverse distance weighted interpolation method, and the zenith tropospheric delay of the rover is obtained according to a pre-constructed elevation normalization model, wherein the elevation normalization model is constructed based on ERA5 horizontal pressure layer meteorological data, and the construction method of the elevation normalization model includes: Calculate the refractive index of each pressure layer every hour based on ERA5 horizontal pressure layer meteorological data, and calculate the ZTD value of each pressure layer according to the refractive index; The ZTD variation characteristics of the out-of-grid points in the vertical direction are obtained by fitting the piecewise negative exponential function, and the piecewise negative exponential function parameters are obtained by the least squares method. According to the ZTD parameter time series in different altitude intervals, data fitting is performed through trigonometric functions and spherical harmonic functions to obtain the model parameters. The annual cycle variation trend characteristics of the elevation normalization parameters are utilized, and the wavelet transform method of time-frequency analysis is used to capture the short-term high-frequency characteristics and long-term low-frequency characteristics of the elevation normalization parameters to construct the elevation normalization model.

2. The method according to claim 1, wherein: The combination of carrier phase and pseudorange observations is used to extract the tropospheric delay of the reference station, where the undifferenced pseudorange and carrier observation equations are as follows: ； Where, represents the ionospheric-free combined observation value, including or , represents the pseudorange, Indicates the carrier phase; Represents geometric distance; represents the speed of light; and Represent the clock differences of the receiver and satellite respectively; represents the tropospheric delay; represents the equivalent wavelength of the ionosphere-free combination; represents the integer ambiguity of the ionospheric-free combination; represents the observation noise of the ionosphere-free combination.

3. The method according to claim 2, characterized in that The formula for the zenith tropospheric delay of the reference station is as follows: ； Where, Indicates the number of visible satellites; Indicates satellite The zenith distance, represents the zenith tropospheric delay.

4. The method according to claim 1, wherein The inverse distance weighted formula is as follows: ； Where, Indicates the ZTD value of the point to be interpolated; represents the distance weight; Indicates the The ZTD value of each base station.

5. The method according to claim 1, wherein The elevation normalization model is expressed by a multi-scale model expression. The specific formula is as follows: ； Where, represents the annual cycle component; represents the semiannual component; represents the diurnal component; represents the residual noise, represents the normalized time within a year; and represent the slope and intercept respectively.

6. The method according to claim 1, characterized in that Also includes: The zenith tropospheric delay of the mobile station is converted into the slant path tropospheric delay on the satellite signal propagation path through a mapping function. The obtained slant path tropospheric delay is applied as a correction term to the GNSS observation equation of the mobile station to correct the positioning delay of the mobile station. The slant path tropospheric delay formula is: ； Where, represents the slant path tropospheric delay, and denote the zenith static delay and wet delay respectively, and represent the static delay function and wet delay mapping function respectively.

7. A tropospheric delay correction system, characterized in that: include: The first delay module is configured to extract the tropospheric delay of the reference station based on the acquired real-time reference station observation data, broadcast ephemeris, ultra-rapid orbit and clock error by using a non-differenced combined observation value method, and adjust the observation values ​​of multiple satellites to obtain the zenith tropospheric delay of the reference station; The second delay module is configured to horizontally interpolate the normalized zenith tropospheric delay of the reference station to the mobile station position through an inverse distance weighted interpolation method, and obtain the zenith tropospheric delay of the mobile station according to a pre-constructed elevation normalization model, wherein the elevation normalization model is constructed based on ERA5 horizontal pressure layer meteorological data, and the construction method of the elevation normalization model includes: Calculate the refractive index of each pressure layer every hour based on ERA5 horizontal pressure layer meteorological data, and calculate the ZTD value of each pressure layer according to the refractive index; The ZTD variation characteristics of the out-of-grid points in the vertical direction are obtained by fitting the piecewise negative exponential function, and the piecewise negative exponential function parameters are obtained by the least squares method. According to the ZTD parameter time series in different altitude intervals, data fitting is performed through trigonometric functions and spherical harmonic functions to obtain the model parameters. The annual cycle variation trend characteristics of the elevation normalization parameters are utilized, and the wavelet transform method of time-frequency analysis is used to capture the short-term high-frequency characteristics and long-term low-frequency characteristics of the elevation normalization parameters to construct the elevation normalization model.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 6 when executing the program.

9. A non-transitory computer-readable storage medium, characterized in that in, The non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to cause a computer to execute the method according to any one of claims 1 to 6.

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