Tropospheric delay correction method, system, electronic device and storage medium

Abstract

The application provides a tropospheric delay correction method and system, electronic equipment and storage medium, comprising: according to the obtained real-time reference station observation data, broadcast ephemeris, ultrafast orbit and clock difference, and through the non-difference combined observation value method, the tropospheric delay of the reference station is extracted, and the observation values of a plurality of satellites are adjusted to obtain the zenith tropospheric delay of the reference station; the normalized zenith tropospheric delay of the reference station is interpolated to the flow station position by the inverse distance weighted interpolation method, and the zenith tropospheric delay of the flow station is obtained according to the pre-constructed elevation normalization model, wherein the elevation normalization model is constructed based on ERA5 horizontal pressure layer meteorological data. The application can improve the adaptability of the model to complex terrain, thereby improving the model precision, effectively shortening the precise point positioning convergence time of the flow station, and improving the precise point positioning precision.

Description

Technical Field

[0001] This 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 Technology

[0002] Global Navigation Satellite Systems (GNSS) are the core support of modern positioning technology, and their positioning accuracy is directly related to key areas such as geographic information acquisition and disaster monitoring. Atmospheric delay error is one of the main error sources of Precise Point Positioning (PPP), and tropospheric delay, due to its non-dispersive characteristics and complex meteorological correlations, has become a key and difficult point in error correction.

[0003] Traditional tropospheric delay correction methods mainly rely on empirical models, but these models suffer from insufficient accuracy in real-time applications. Currently, although GNSS base stations can provide high-precision tropospheric delay products, their coverage is limited, making them difficult to apply directly to target areas far from the base station. Furthermore, their insufficient spatial representation capabilities in both horizontal and vertical directions lead to a significant decrease in correction accuracy in areas with high elevation differences. Summary of the Invention

[0004] In view of this, this application aims to provide 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, this application provides a tropospheric delay correction method, comprising:

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

[0008] The zenith troposphere of the reference station is horizontally interpolated to the position of the rover using the inverse distance weighted interpolation method after normalization. The zenith troposphere delay of the rover is obtained based on a pre-constructed elevation normalization model, which is constructed based on ERA5 horizontal pressure layer meteorological data.

[0009] Secondly, based on the same inventive concept, this application also provides a tropospheric delay correction system, comprising:

[0010] The first delay module is configured to extract the tropospheric delay of the base station based on the acquired real-time base station observation data, broadcast ephemeris, ultra-fast orbit and clock error, and to perform adjustment processing on the observations of multiple satellites to obtain the zenith tropospheric delay of the base station.

[0011] The second delay module is configured to interpolate the normalized zenith troposphere of the base station to the rover location using an inverse distance weighted interpolation method, and to obtain the zenith troposphere delay of the rover station based on a pre-constructed elevation normalization model, wherein the elevation normalization model is constructed based on ERA5 horizontal pressure layer meteorological data.

[0012] Thirdly, based on the same inventive concept, this application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method described in the first aspect.

[0013] Fourthly, based on the same inventive concept, this application also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions for causing the computer to perform the method as 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 advantages:

[0015] The tropospheric delay correction method described in this application can improve the model's adaptability to complex terrain, thereby improving the model's accuracy, effectively shortening the convergence time of precise single-point positioning of the rover, and improving the accuracy of precise single-point positioning. Attached Figure Description

[0016] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0017] Figure 1 This is a flowchart of a tropospheric delay correction method according to an embodiment of this application;

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

[0019] Figure 3 This is a schematic diagram of the hardware structure of the electronic device described in an embodiment of this application. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with specific embodiments and the accompanying drawings.

[0021] It should be noted that, unless otherwise defined, the technical or scientific terms used in the embodiments of this application should have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms "first," "second," and similar terms used in the embodiments of this application do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" 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 this application are described in detail below with reference to the accompanying drawings.

[0023] Please see 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 base station observation data, broadcast ephemeris, ultra-fast orbit and clock error, and by using the non-difference combined observation method to extract the tropospheric delay of the base station, the observations of multiple satellites are adjusted to obtain the zenith tropospheric delay of the base station.

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

[0026] Specifically, in this embodiment, meteorological data of the ERA5 horizontal pressure layer (including air pressure, temperature, geopotential and relative humidity) are read, and the ZTD (Zenith Total Delay) of each grid point is obtained by integration method. The zenith tropospheric delay ZTD consists of zenith hydrostatic delay (ZHD) and zenith wet delay (ZWD), and is an important factor causing the precise positioning error when using 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 was used for fitting, calculating the ZTD and elevation normalization parameters for each grid point at each time point. Trigonometric functions and spherical harmonic functions were then used for fitting, and the model parameters were stored in grid form to obtain the elevation normalization model. Using real-time base station observation data, broadcast ephemeris, ultra-fast orbits, and clock errors, the tropospheric delay of the base station was estimated using an undifferentiated combined observation method. The observations from multiple satellites were adjusted to obtain the zenith tropospheric delay of the base station. The zenith tropospheric delay of the rover station was obtained using the elevation normalization model and horizontal interpolation. The specific steps are as follows:

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

[0029] Download the ERA5 hourly reanalysis data from the ECMWF website for the past 5 years. This data includes four-dimensional grid data of air pressure, temperature, geopotential and relative humidity. Calculate the refractive index per hour per air pressure layer according to formula (1). The grid resolution is 0.25° × 0.25°, with a total of 37 layers. In the formula... =77.604 K / hPa, =64.79K / hPa, =377600K 2 / hPa; and These represent air pressure and water vapor pressure, respectively, in hPa. Temperature is indicated, in units of The ZTD value above each pressure layer is obtained by integrating formula (2). Indicates altitude.

[0030] (1)

[0031] (2)

[0032] The ZTD variation characteristics of the grid points in the vertical direction are fitted according to the piecewise negative exponential function formula (3), and the parameters of the piecewise negative exponential function are obtained by least squares. , and These represent the ZTD values ​​of the reference height in different elevation ranges; , and These are the elevation normalization parameters for ZTD; Indicates the reference altitude.

[0033] (3)

[0034] The ZTD parameter time series in different altitude ranges are fitted with trigonometric functions, as shown in formula (4), where doy represents the year-to-date and hour represents UTC time.

[0035] (4)

[0036] In the formula, the phases of the annual and daily cycles are parameterized, and spherical harmonic functions are used to convert the parameters. ( =0, 1, 2…8) are spherically harmonic expanded as shown in equation (5), and the model coefficients are solved by the least squares method.

[0037] (5)

[0038] in, Represents Legendre polynomials; and These are the latitude and longitude of the station, respectively. and To determine the spherical harmonic function using least squares Step Order coefficient; degree Controlling the resolution and order of the spherical harmonic function in the latitudinal direction. Controlling the resolution of the spherical harmonic function in the longitude direction; This represents the highest order of the spherical harmonic function expansion, which determines the complexity and spatial resolution of the model; it is generally chosen to be between 10 and 20.

[0039] By utilizing the annual cycle variation trend of the elevation normalization parameter, 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 parameter and construct a parameter model.

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

[0041] (6)

[0042] in, For elevation normalization parameters; This represents the normalized time within a year, expressed in hours. ; and The slope and intercept of the linear trend obtained by least squares fitting; These are the normalized elevation parameters after detrending. This is the detrended mean; The standard deviation after detrending; These are the standardized elevation normalization parameters.

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

[0044] (7)

[0045] in, The input elevation normalization parameter; These are Morlet wavelet basis functions; and These are the scale parameter and translation parameter, respectively; W( , ) represents the wavelet coefficients, indicating the signal at different scales. and time The energy intensity below; The center frequency is usually set to 6; Let be the wavelet allowable constant. These are the normalized elevation parameters after reconstruction.

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

[0047] (8)

[0048] in, This is a component with an annual cycle. This is a six-month cycle component; This is a daily cycle component; This is residual noise.

[0049] Step S202: Estimate the real-time tropospheric delay based on GNSS stations, specifically including:

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

[0051] (9)

[0052] in, For observations of the non-ionospheric combination ( or ); Geometric distance; The speed of light; and These are the receiver and the satellite clock bias, respectively. For tropospheric delay; The equivalent wavelength for the ionosphere-free combination; For integer ambiguity of ionosphere-free combinations; This is the observation noise for ionospheric combinations.

[0053] The zenith tropospheric delay of the base station is extracted by non-difference combination method. To further improve the accuracy, the observations 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; Let be the zenith distance of satellite s.

[0056] Step S203, Tropospheric Delay Correction for the Rover, specifically includes:

[0057] According to step S202, after obtaining the real-time tropospheric delay of different reference stations using the pseudorange carrier data and broadcast ephemeris, ultra-fast orbit and clock difference of the base station, it is converted into the elevation-normalized zenith tropospheric delay according to formulas (3) and (4) so ​​as to interpolate between stations at different elevations.

[0058] The normalized ZTD of the base station is interpolated to the position of the rover 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 elevation normalization model.

[0059] (11)

[0060] In the formula, The ZTD value of the point to be interpolated; Distance weights; Let be the ZTD value of the i-th base station;

[0061] After obtaining the zenith tropospheric delay of the rover, it needs to be mapped to the skew path tropospheric delay (STD) on the satellite signal propagation path. The mapping function is usually the Niell model, the global mapping function (GMF), or the 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 rover station to improve positioning accuracy, as shown in formula (12).

[0063] (12)

[0064] in, and For zenith static delay and zenith wet delay; and These 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, with the IGS station as the rover and stations within a 50km radius as reference stations, the positioning accuracy of the commonly used tropospheric delay model GPT3 and the elevation normalization model of this patent was analyzed on July 1, 2021. Using the station center coordinate system as the reference, the accuracy of the coordinates calculated by the precise single-point positioning in the east, north, and elevation directions (E, N, and U directions) was evaluated. The average error of the model is shown in Table 1.

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

[0068]

[0069] Table 1 shows that the elevation normalization model and the GPT3 model have roughly the same horizontal correction effect in precise single-point positioning, while the positioning accuracy is greatly improved in the elevation direction, with an average improvement of about 44.6%. This demonstrates that the real-time tropospheric correction method proposed in this application can improve the accuracy of the station in precise single-point positioning.

[0070] Therefore, the method described in this embodiment combines hourly horizontal resolution barosphere meteorological data from ERA5 to construct an elevation normalization model; based on reference station observation data, broadcast ephemeris, ultra-fast orbits, and clock errors, a non-difference combination method is used to obtain high-precision tropospheric delay information; the observation values ​​from 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 rover station; this method effectively improves the precision single-point positioning accuracy of the rover station and shortens the positioning convergence time.

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

[0072] It should be noted that the above description describes some embodiments of this application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in a different order than that shown in the above embodiments and still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0073] Based on the same inventive concept, and corresponding to the methods of any of the above embodiments, the embodiments of this application also provide 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 base station based on the acquired real-time base station observation data, broadcast ephemeris, ultra-fast orbit and clock error, and to perform adjustment processing on the observations of multiple satellites to obtain the zenith tropospheric delay of the base station.

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

[0077] For ease of description, the above system is described by dividing it into various modules based on their functions. Of course, in implementing the embodiments of this application, the functions of each module can be implemented in one or more software and / or hardware.

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

[0079] Based on the same inventive concept, corresponding to the methods of any of the above embodiments, embodiments of this application also provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the methods described in any of the above embodiments.

[0080] Figure 3This embodiment illustrates a more specific hardware structure of an electronic device, which may include a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, memory 1020, input / output interface 1030, and communication interface 1040 are interconnected internally via the bus 1050.

[0081] The processor 1010 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, 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 device, dynamic storage device, etc. The memory 1020 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented by 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 input / output modules to realize information input and output. The input / output modules can be configured as components in the device (not shown in the figure) or externally connected to the device to provide corresponding functions. Input devices may include keyboards, mice, touch screens, microphones, various sensors, etc., and output devices may include displays, speakers, vibrators, indicator lights, etc.

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

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

[0086] It should be noted that although the above-described device only shows the processor 1010, memory 1020, input / output interface 1030, communication interface 1040, and bus 1050, in specific implementations, the device may also include other components necessary for normal operation. Furthermore, those skilled in the art will understand that the above-described device may only include the components necessary for implementing the embodiments of this specification, and not necessarily all the components shown in the figures.

[0087] The electronic devices described above are used to implement the corresponding methods in any of the foregoing embodiments and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0088] Based on the same inventive concept, corresponding to the methods of any of the above embodiments, this application also provides a non-transitory computer-readable storage medium that stores computer instructions for causing the computer to perform the methods described in any of the above embodiments.

[0089] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. 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 technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0090] The computer instructions stored in the storage medium of the above embodiments are used to cause the computer to perform the methods 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 exemplary and is not intended to imply that the scope of this application (including the claims) is limited to these examples; within the framework of this application, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of different aspects of the embodiments of this application as described above, which are not provided in the details for the sake of brevity.

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

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

[0094] The embodiments of this 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 this application should be included within the protection scope of this application.

Claims

1. A method for correcting tropospheric delay, characterized in that, include: Based on the real-time base station observation data, broadcast ephemeris, ultra-fast orbit and clock error, the tropospheric delay of the base station is extracted by the non-difference combined observation method. The observations of multiple satellites are adjusted to obtain the zenith tropospheric delay of the base station. The zenith tropospheric level of the normalized base station is interpolated to the rover's location using an inverse distance-weighted interpolation method. The zenith tropospheric delay of the rover is then obtained based on a pre-constructed elevation normalization model. This elevation normalization model is constructed using ERA5 horizontal barosphere meteorological data, and the construction method for the elevation normalization model includes: The refractive index of each pressure layer per hour is calculated based on ERA5 horizontal pressure layer meteorological data, and the ZTD value of each pressure layer is calculated based on 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 parameters of the piecewise negative exponential function are obtained by the least squares method. Based on the time series of ZTD parameters in different altitude ranges, and by fitting the data using trigonometric functions and spherical harmonic functions, model parameters are obtained. Utilizing the annual cycle variation trend characteristics of the elevation normalization parameters, 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 in order to construct an elevation normalization model. The elevation normalization model is expressed using a multi-scale model expression, with the specific formula as follows: In the formula, Indicates the annual cycle component; Indicates a six-month cycle component; Represents the daily periodic component; ∈ i represents residual noise, t represents the normalization time within one year; a and b represent the slope and intercept, respectively.

2. The method according to claim 1, characterized in that: The tropospheric delay of the reference station is extracted by combining carrier phase and pseudorange observations. The equations for the unequal pseudorange and carrier observations are as follows: φ IF =ρ+c·(dt r -dt s )+T r +λ IF ·N IF +ε IF ; In the formula, φ IF This represents observations of the ionosphere-free combination, including or P represents pseudorange, L represents carrier phase; ρ represents geometric distance, c represents speed of light; dt r and dt s T represents the clock difference corresponding to the receiver and the satellite, respectively; r Indicates tropospheric delay; λ IF Indicates the equivalent wavelength of the ionosphere-free combination; N IF Indicates the integer ambiguity of the ionosphere-free combination; ε IF This represents the observation noise without an ionospheric assembly.

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

4. The method according to claim 1, characterized in that, The inverse distance weighted formula is as follows: In the formula, ZTD u This represents the ZTD value of the point to be interpolated; Represents distance weight; ZTD i This represents the ZTD value of the i-th base station.

5. The method according to claim 1, characterized in that, Also includes: The zenith tropospheric delay of the rover station is converted into a slant-path tropospheric delay along the satellite signal propagation path using a mapping function. This slant-path tropospheric delay is then applied as a correction term to the rover station's GNSS observation equations to correct its positioning delay. The formula for the slant-path tropospheric delay is as follows: STD=ZHD·Mf h +ZWD·Mf w ; In the formula, STD represents the oblique path tropospheric delay, ZHD and ZWD represent the zenith static delay and wet delay, respectively, and Mf h andMf w These represent the static delay function and the wet delay mapping function, respectively.

6. A tropospheric delay correction system, characterized in that, include: The first delay module is configured to extract the tropospheric delay of the base station based on the acquired real-time base station observation data, broadcast ephemeris, ultra-fast orbit and clock error, and to perform adjustment processing on the observations of multiple satellites to obtain the zenith tropospheric delay of the base station. The second delay module is configured to interpolate the normalized zenith troposphere of the base station to the rover's location using an inverse distance-weighted interpolation method, and to obtain the zenith troposphere delay of the rover based on a pre-constructed elevation normalization model. The elevation normalization model is constructed based on ERA5 horizontal barosphere meteorological data, and the construction method of the elevation normalization model includes: The refractive index of each pressure layer per hour is calculated based on ERA5 horizontal pressure layer meteorological data, and the ZTD value of each pressure layer is calculated based on 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 parameters of the piecewise negative exponential function are obtained by the least squares method. Based on the time series of ZTD parameters in different altitude ranges, and by fitting the data using trigonometric functions and spherical harmonic functions, model parameters are obtained. Utilizing the annual cycle variation trend characteristics of the elevation normalization parameters, 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 in order to construct an elevation normalization model. The elevation normalization model is expressed using a multi-scale model expression, with the specific formula as follows: In the formula, Indicates the annual cycle component; Indicates a six-month cycle component; Represents the daily periodic component; ∈ i represents residual noise, t represents the normalization time within one year; a and b represent the slope and intercept, respectively.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the method as claimed in any one of claims 1-5.

8. A non-transitory computer-readable storage medium, characterized in that, in, The non-transitory computer-readable storage medium stores computer instructions for causing a computer to perform the method described in any one of claims 1-5.

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