A GNSS tropospheric and multipath joint modeling correction method and system

Abstract

The present invention belongs to the field of satellite positioning and navigation technology, and discloses a GNSS troposphere and multipath joint modeling correction method and system. The present invention is based on a semi-celestial grid point model, and performs GNSS troposphere and multipath joint modeling correction, including constructing a tropospheric delay semi-celestial map and generating a tropospheric delay correction table, constructing a GNSS multipath error semi-celestial map and generating a multipath error correction table, and by retrieving the tropospheric delay and multipath error correction values ​​corresponding to the satellite altitude angle and azimuth angle, the GNSS PPP observation equation is corrected to obtain the GNSS PPP positioning result. The present invention can achieve high-precision positioning of GNSS PPP under the influence of complex terrain and extreme weather conditions.

Description

Technical Field

[0001] The present invention belongs to the field of satellite positioning and navigation technology, and more specifically, relates to a GNSS tropospheric and multipath joint modeling correction method and system. Background Art

[0002] In the GNSS (Global Navigation Satellite System) Precise Point Positioning (PPP) data processing, the impact of unmodeled errors on GNSS PPP positioning can reach up to the centimeter level, which is mainly composed of multipath errors and tropospheric delays. Especially in complex terrain and extreme weather conditions, the correction effect of traditional tropospheric models is not good, and the coupling relationship between multipath errors and tropospheric delays in GNSS unmodeled errors is difficult to separate, resulting in deviations in the accuracy of GNSS positioning performance.

[0003] Complex terrain, such as canyons, dams, bridges and other areas, have large height differences between sites due to the large terrain undulations. According to the vertical structural characteristics of the troposphere, the tropospheric delay effects at different heights are different. In addition, the terrain will also affect the airflow circulation in the troposphere, resulting in small-scale changes in the tropospheric refractive index. Under the combined effect of the above two aspects, there are significant differences in the tropospheric delays experienced by adjacent GNSS sites. The traditional tropospheric model is not effective in processing the tropospheric delay, which poses a great challenge to the accuracy of GNSS positioning performance. Under extreme weather conditions, such as heavy rains and typhoons, the water vapor, temperature and air pressure in the troposphere change dramatically, causing rapid time-varying of the tropospheric refractive index, which directly leads to rapid time-varying characteristics of the tropospheric delay of the GNSS site. GNSS measurement relies on high-precision estimation of signal propagation time, and the drastic time-varying of tropospheric delay will have an adverse effect on the positioning results. In addition, the terrain will also cause diffraction and shielding of GNSS signals, resulting in multipath effects, which will affect the propagation of GNSS signals, which is also an important factor affecting GNSS positioning accuracy.

[0004] Usually, empirical models, grid models and parameter estimation methods are used to process tropospheric delay. However, these methods are difficult to meet the needs of GNSS high-precision positioning under complex terrain and extreme weather conditions. Due to the small station area or the rapid spatiotemporal changes of the troposphere, it is difficult to establish an empirical model that can be widely used; using the surrounding CORS stations to establish a regional tropospheric delay grid model is difficult to describe the tropospheric change characteristics in complex environmental areas and cannot guarantee interpolation accuracy; for estimating tropospheric delay as a parameter, the existing tropospheric mapping function will lose accuracy at low altitude angles and is difficult to estimate accurately. In terms of multipath effect correction, after various errors are corrected and GNSS data is processed, the remaining observation value residuals will be used for multipath modeling. GNSS stations in complex environments often find it difficult to accurately eliminate the impact of tropospheric delay, which will be absorbed by the observation value residuals, affecting multipath modeling and thus affecting positioning accuracy. Summary of the invention

[0005] The present invention solves the problem of poor positioning accuracy of GNSS PPP in complex environments in the prior art by providing a GNSS troposphere and multipath joint modeling correction method and system.

[0006] The present invention provides a GNSS troposphere and multipath joint modeling correction method, comprising the following steps:

[0007] Step 1: Use ray tracing to construct a tropospheric delay semi-spherical map and generate a tropospheric delay correction table;

[0008] Step 2: obtaining tropospheric delay information based on the tropospheric delay semi-spherical map, performing multi-system GNSS PPP data processing on the GNSS original observations, precision products and error correction products, extracting GNSS a posteriori residual information and the altitude and azimuth angles corresponding to the satellites, constructing a GNSS multipath error semi-spherical map, and generating a multipath error correction table;

[0009] Step 3: During the GNSS PPP data processing, the multipath error correction table is retrieved by using the time, altitude angle and azimuth angle corresponding to the current satellite to obtain the current multipath model correction value, and the correction is applied to the original GNSS observation value;

[0010] The tropospheric delay correction table is retrieved through the time, altitude angle and azimuth angle corresponding to the current satellite to obtain the current tropospheric delay information, the current tropospheric delay information, the current precision product and the output information of the error correction product are added to the GNSS PPP observation equation, the GNSS PPP observation equation is solved by Kalman filtering, and the GNSS PPP positioning result is obtained.

[0011] Preferably, the construction of a semi-celestial map of tropospheric delay using ray tracing includes: obtaining tropospheric tilt delay and corresponding mapping factors using ray tracing; generating a grid file based on the tropospheric delay information and its corresponding time, altitude angle and azimuth angle to form the tropospheric delay correction table.

[0012] Preferably, the ray tracing is performed based on ERA5 data, or, the ray tracing is performed based on ERA5 data and ground meteorological data.

[0013] Preferably, the tropospheric oblique delay includes: the total tropospheric delay, the static delay and the wet delay of the oblique path; the mapping factors include: the mapping factor of the total tropospheric delay, the mapping factor of the static delay and the mapping factor of the wet delay.

[0014] Preferably, ray tracing is used to obtain tropospheric tilt delays covering an azimuth range of 0 to 360 degrees with an interval of 1 degree and an altitude range of 3 to 90 degrees and corresponding mapping factors.

[0015] Preferably, the tropospheric delay is expressed as:

[0016] STD(e,α,t)=MFH(e,α,t)·ZHD+MFW(e,α,t)·ZWD

[0017] Wherein, STD(e,α,t) is the tropospheric delay, MFH(e,α,t) is the mapping factor of static delay, MFW(e,α,t) is the mapping factor of wet delay, ZHD and ZWD are the static delay and wet delay in the zenith direction, e is the azimuth, α is the altitude, and t is the time.

[0018] Preferably, the total tropospheric delay, static delay and wet delay of the inclined path are expressed as follows:

[0019]

[0020] Among them, STD, SHD, SWD are the total tropospheric delay, static delay, and wet delay of the slant path, respectively; k is the number of the refractive index field altitude layer divided by ray tracing; i is the altitude layer number; are the total refractive index, static refractive index, and wet refractive index of the troposphere at the middle position of the ray node; s i is the ray length between each altitude layer, s bend is the geometric bending effect, e i is the altitude angle of each ray node.

[0021] Preferably, the mapping factor of the total tropospheric delay, the mapping factor of the static delay and the mapping factor of the wet delay are expressed as follows:

[0022]

[0023] Among them, MFT, MFH, and MFW are the mapping factors of the total tropospheric delay, the mapping factors of the static delay, and the mapping factors of the wet delay, respectively; STD, SHD, and SWD are the total tropospheric delay, static delay, and wet delay of the slant path, respectively; ZTD, ZHD, and ZWD are the total tropospheric delay, static delay, and wet delay in the zenith direction, respectively.

[0024] Preferably, the GNSS a posteriori residual information includes pseudorange and carrier phase.

[0025] On the other hand, the present invention provides a GNSS tropospheric and multipath joint modeling correction system, comprising:

[0026] Tropospheric delay module, used to construct a tropospheric delay semi-celestial map using ray tracing and generate tropospheric delay correction tables;

[0027] A multipath error module is used to obtain tropospheric delay information based on the tropospheric delay semi-celestial map, perform multi-system GNSS PPP data processing in combination with GNSS original observations, precision products and error correction products, extract GNSS a posteriori residual information and the altitude angle and azimuth angle corresponding to the satellite, construct a GNSS multipath error semi-celestial map, and generate a multipath error correction table;

[0028] A joint correction module is used to retrieve the multipath error correction table through the time, altitude and azimuth corresponding to the current satellite during the GNSS PPP data processing, obtain the current multipath model correction value, and correct it on the GNSS original observation value; retrieve the tropospheric delay correction table through the time, altitude and azimuth corresponding to the current satellite, obtain the current tropospheric delay information, add the current tropospheric delay information, the current precision product and the output information of the error correction product to the GNSS PPP observation equation, perform Kalman filtering on the GNSS PPP observation equation, and obtain the GNSS PPP positioning result;

[0029] The GNSS troposphere and multipath joint modeling correction system is used to execute the steps in the above-mentioned GNSS troposphere and multipath joint modeling correction method.

[0030] One or more technical solutions provided in the present invention have at least the following technical effects or advantages:

[0031] The present invention proposes a GNSS troposphere and multipath joint modeling correction method based on a semi-celestial grid point model, including constructing a tropospheric delay semi-celestial map and generating a tropospheric delay correction table, constructing a GNSS multipath error semi-celestial map and generating a multipath error correction table, and correcting the GNSS PPP observation equation by retrieving the tropospheric delay and multipath error correction values ​​corresponding to the satellite altitude angle and azimuth angle to obtain the GNSS PPP positioning result. Compared with traditional functions or empirical models, the joint model constructed by the present invention has the advantages of high temporal and spatial resolution, simple model, high accuracy, etc. Specifically, on the one hand, the present invention only needs to construct two semi-celestial maps during modeling, and there is no need to determine the PRN (Pseudo-Random Noise) number of a specific satellite during correction, which has the advantages of being simple and easy to implement; on the other hand, under complex terrain and extreme weather conditions, the traditional method of using a mapping function and estimating horizontal gradients cannot fully consider the complexity of the terrain and the rapid changes in atmospheric water vapor, resulting in inaccurate tropospheric delay estimation at low altitude angles, and the residual part is often mistaken for a multipath effect. The tropospheric semi-celestial map modeling and correction scheme proposed in the present invention can significantly alleviate the coupling relationship between the tropospheric residual and the multipath error in the GNSS unmodeled error, thereby obtaining a more "clean" multipath error, improving the modeling and correction effect of the multipath error, and thus being able to achieve high-precision positioning of GNSS PPP under the influence of complex terrain and extreme weather conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 A flowchart of a GNSS tropospheric and multipath joint modeling correction method provided in Example 1 of the present invention;

[0033] Figure 2 A schematic diagram of model construction corresponding to a GNSS tropospheric and multipath joint modeling correction method provided in Example 1 of the present invention;

[0034] Figure 3 A GNSS PPP carrier phase residual sequence before and after correction using a GNSS tropospheric and multipath joint modeling correction method provided by Example 1 of the present invention and a traditional method;

[0035] Figure 4 The present invention provides a GNSS tropospheric and multipath joint modeling correction method and a GNSS PPP positioning error time series before and after correction using a traditional method. DETAILED DESCRIPTION

[0036] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0037] Embodiment 1:

[0038] Example 1 provides a GNSS tropospheric and multipath joint modeling correction method, see Figure 1 , including the following steps:

[0039] Step 1: Use ray tracing to construct a semi-spherical map of tropospheric delay and generate a tropospheric delay correction table.

[0040] Step 2: Based on the tropospheric delay semi-spherical map, the tropospheric delay information is obtained, and multi-system GNSS PPP data processing is performed on the GNSS original observations, precision products, and error correction products to extract the GNSS a posteriori residual information and the altitude and azimuth angles corresponding to the satellites, construct a GNSS multipath error semi-spherical map, and generate a multipath error correction table.

[0041] Step 3: During the GNSS PPP data processing, the multipath error correction table is retrieved by using the time, altitude angle and azimuth angle corresponding to the current satellite to obtain the current multipath model correction value, and the correction is applied to the original GNSS observation value;

[0042] The tropospheric delay correction table is retrieved through the time, altitude angle and azimuth angle corresponding to the current satellite to obtain the current tropospheric delay information, the current tropospheric delay information, the current precision product and the output information of the error correction product are added to the GNSS PPP observation equation, the GNSS PPP observation equation is solved by Kalman filtering, and the GNSS PPP positioning result is obtained.

[0043] Among them, ray tracing is a method that uses meteorological data to trace the ray path from the edge of the atmosphere to the receiver to obtain the tropospheric delay. This method divides the neutral atmosphere into specific high-resolution horizontal grids and altitude layers through optical approximation. In these grids, the ray tracing beam propagates and experiences delays and bends according to complex refraction rules, which is very similar to the actual propagation path. By integrating the refractive index of the ray path, the tropospheric delay along the ray path can be obtained. Therefore, the ray tracing method can be used to accurately calculate the tropospheric delay.

[0044] Based on the above considerations, in order to improve the positioning accuracy of GNSS PPP in complex environments, the present invention targets GNSS stations in complex environments, and based on the tropospheric delay ray tracing technology, can obtain the tropospheric delay in the tilt and zenith directions for modeling, and combine the spatial repeatability of the multipath effect to construct a combined model. By correcting the more accurate tropospheric delay model, the coupling between the tropospheric delay and the multipath effect is reduced, thereby further improving the positioning accuracy and ambiguity convergence speed of GNSS under complex terrain and extreme weather conditions.

[0045] In addition, the tomography technology requires a large number of GNSS observations for calculation and inversion, and is only suitable for post-processing; compared with the tomography technology, the ray tracing used in the present invention only needs to use ERA5 meteorological data, has low calculation cost, and has a time resolution of 1 hour, which has significant advantages.

[0046] Specifically, the method of constructing a semi-celestial tropospheric delay map using ray tracing in the present invention includes: obtaining the tropospheric tilt delay and the corresponding mapping factor using ray tracing; generating a grid file based on the tropospheric delay information (i.e., the tropospheric delay ray tracing result) and its corresponding time, altitude angle and azimuth angle to form the tropospheric delay correction table.

[0047] The present invention performs the ray tracing based on ERA5 data, or performs the ray tracing based on ERA5 data and ground meteorological data.

[0048] The tropospheric oblique delay includes: the tropospheric total delay, the static delay and the wet delay of the oblique path; the mapping factors include: the mapping factor of the tropospheric total delay, the mapping factor of the static delay and the mapping factor of the wet delay.

[0049] Specifically, ray tracing is used to obtain the tropospheric tilt delay covering an azimuth range of 0 to 360 degrees with an interval of 1 degree and an altitude range of 3 to 90 degrees and the corresponding mapping factors.

[0050] The present invention is further described below in conjunction with parameters.

[0051] See also Figure 1 The present invention provides a GNSS troposphere and multipath joint modeling correction method based on a semi-celestial grid point model, which specifically includes the following steps:

[0052] Step 1: Construct a tropospheric delay hemispheric map (THM).

[0053] It mainly includes using ray tracing to construct a semi-celestial map of tropospheric delay and generate a tropospheric delay correction table.

[0054] Specifically, since the most commonly used GMF, GPT3 and VMF3 mapping functions and the GRAD horizontal gradient model are currently used, ray tracing technology is used to fit the results of 7 altitude angles (3°, 5°, 7°, 10°, 15°, 30° and 70°) and 16 azimuth angles (0°: 22.5°: 337.5°) using ERA-Interim meteorological products (horizontal resolution 1° × 1°, time resolution 6 hours).

[0055] The present invention uses ERA5 (horizontal resolution 0.25°×0.25°, time resolution 1 hour) and ground meteorological data of ERA-Interim (only ERA5 data is used if there is no ground meteorological data) to calculate the total delay, static delay and wet delay of the inclined troposphere in the range of 0 to 360 degrees with an interval of 1 degree and an altitude angle of 3 to 90 degrees, as well as the corresponding mapping factors, which are specifically expressed as follows:

[0056]

[0057] Among them, STD, SHD, SWD are the total tropospheric delay, static delay, and wet delay of the slant path, respectively; k is the number of the refractive index field altitude layer divided by ray tracing; i is the altitude layer number; are the total refractive index, static refractive index, and wet refractive index of the troposphere at the middle position of the ray node; s i is the ray length between each altitude layer, s bend is the geometric bending effect, e i is the altitude angle of each ray node.

[0058]

[0059] Among them, ZTD, ZHD, and ZWD are the total tropospheric delay, static delay, and wet delay in the zenith direction, respectively, and Δh i =h i+1 -h i , i=1,…,k-1;h i is the height of the i-th altitude layer in the zenith direction; and They are the average total refractive index, average static refractive index and average wet refractive index between the i-th and i+1-th altitude layers in the zenith direction, respectively.

[0060]

[0061] Among them, MFT, MFH and MFW are the mapping factors of total tropospheric delay, static delay and wet delay, respectively, which can be used for the estimation of tropospheric delay of space geodetic techniques such as GNSS and VLBI, as well as the development of mapping functions and horizontal gradients.

[0062] The tropospheric delay and mapping factors calculated by the above formula, together with their corresponding time, altitude angle, and azimuth, generate a grid file with a resolution of 1°×1°, which constitutes the tropospheric delay correction table. This model is a single-station model with high temporal and spatial resolution, and can be used for fine correction of tropospheric delay.

[0063] For tropospheric delay, the traditional method is to use the Saastamoinen model, combined with the tropospheric empirical model or ground meteorological measurement data, to calculate the zenith tropospheric static delay, and then use the static mapping function to map the observed value according to the altitude angle and subtract it from the original GNSS observation value. Then, the zenith tropospheric wet delay is estimated using the tropospheric wet mapping function as a partial derivative. Finally, the tropospheric horizontal gradient, that is, the influence of the azimuth asymmetry of the tropospheric delay, is estimated.

[0064] The tropospheric hemispheric map of the present invention retrieves the statics and wet mapping factors on the tropospheric delay correction table based on the corresponding time, altitude and azimuth information. The formula for estimating GNSS tropospheric delay is as follows:

[0065] STD(e,α,t)=MFH(e,α,t)·ZHD+MFW(e,α,t)·ZWD

[0066] Wherein, STD(e,α,t) is the tropospheric delay, MFH(e,α,t) is the mapping factor of static delay, MFW(e,α,t) is the mapping factor of wet delay, ZHD and ZWD are the static delay and wet delay in the zenith direction, e is the azimuth, α is the altitude, and t is the time.

[0067] Specifically, MFH(e,α,t) and MFW(e,α,t) are tropospheric mapping factors obtained by linear time interpolation and bilinear space interpolation methods.

[0068] The method provided by the present invention is different from the traditional method. The static mapping function is replaced by the static mapping factor, and the wet mapping function is replaced by the wet mapping factor. There is no need to estimate the horizontal gradient. This is because the mapping factor is not only related to the altitude angle, but also to the azimuth angle. The mapping function and the horizontal gradient are constructed based on the mapping factor. The semi-celestial map is a high-resolution grid model of the mapping factor, which avoids the modeling errors of the mapping function and the horizontal gradient. Therefore, the tropospheric delay can be calculated more accurately and the unmodeled error can be effectively separated.

[0069] Step 2: Construct a GNSS multipath error semi-celestial map (C-TMHM).

[0070] In GNSS PPP processing, the time, altitude and azimuth corresponding to the current satellite are used to retrieve the tropospheric delay correction table to obtain the tropospheric delay model value (i.e., tropospheric delay information). Multi-system GNSS PPP data processing is performed in combination with the GNSS original observation data, satellite orbit, satellite clock error and other error correction products to extract GNSS a posteriori residuals (including pseudorange and carrier phase) and satellite position information (including altitude and azimuth), and to construct a multipath semi-celestial model.

[0071] The specific steps include:

[0072] First, correlation analysis is performed on the residual sequences of different GNSS systems in the same grid point. If they are strongly correlated or highly correlated, all GNSS satellites in the grid point can be jointly modeled, otherwise the single system is modeled separately (C-TMHM). Considering that the number of satellite coverage in some grids is insufficient, the residual data of a certain satellite in the same grid is highly correlated. Therefore, it is necessary to judge the multicollinearity of the residual data in the same grid. If multicollinearity exists, constrained trend surface analysis is performed on the multipath residual data in the same grid, otherwise no constraint processing is implemented. The trend surface fitting equation of multipath error in the same grid point can be expressed as:

[0073]

[0074] in, is the estimated multipath error value; az i ,el i are the altitude angle and azimuth angle of satellite i respectively; a0-a5 are the trend surface fitting coefficients, which are obtained by Kalman filter fitting.

[0075] Secondly, in order to avoid overfitting and underfitting, it is necessary to perform statistical tests on the results of the above trend surface analysis, including moderation test and significance test. If the statistical test is passed, the fitting coefficient is stored; otherwise, the residual in the grid is averaged.

[0076] Finally, the calculated multipath error model values ​​within the grid points together with the satellite elevation angle and azimuth angle are used to generate a grid file with a resolution of 1°×1°, forming a multipath error correction table.

[0077] Step 3: Joint modeling correction of tropospheric delay and multipath error (TMM).

[0078] Based on the two semi-celestial maps constructed above, the present invention proposes a refined tropospheric delay and multipath error joint modeling correction method (TMM) based on the semi-celestial grid point model. In the GNSS PPP data processing process, the multipath model correction value is obtained by retrieving the improved multipath semi-celestial map (C-TMHM) correction table through the time, altitude and azimuth information corresponding to the current satellite. The correction is applied to the original GNSS observation value and can be expressed as:

[0079]

[0080] Among them, mp i is the multipath model correction value, az i is the azimuth of the i-th satellite, el iis the altitude angle of the i-th satellite. Then, in the GNSS data processing process, the THM model is used again to process the tropospheric delay, and the multi-system GNSS PPP data processing is performed in combination with the GNSS original observation data, satellite orbit, satellite clock error and other error correction products to obtain high-precision positioning results.

[0081] By comparing the present invention with the existing traditional method of using a mapping function and estimating the horizontal gradient (VMF3), it is found that the method of the present invention is superior to the traditional model in improving the PPP positioning performance. Figure 2 Schematic diagram of the established tropospheric and multipath model based on semi-celestial grid point division. Figure 3 The carrier residual time series of three satellites G12, G26 and C30 obtained by PPP solution using three different strategies, respectively: (1) traditional tropospheric model (VMF3) + uncorrected multipath, (2) traditional tropospheric model (VMF3) + corrected multipath, (3) the method proposed by the present invention. The results show that since the present invention uses ground meteorological data with high temporal and spatial resolution when constructing the tropospheric semi-celestial map and considers the influence of low altitude angles and azimuth angles, compared with the traditional method, the present invention can more accurately correct the GNSS tropospheric delay and multipath error. Furthermore, the residual sequence of the present invention fluctuates less over time than the traditional method. It can be seen that the refined tropospheric and multipath quantitative modeling method can effectively reduce the satellite carrier phase residual, which is beneficial to improve the multi-system GNSS PPP positioning accuracy and shorten the convergence time. Figure 4 The positioning error time series in the north, east and vertical directions are respectively obtained by using three different strategies. The results show that the unmodeled error correction magnitude in the GNSS PPP observation equation is improved due to the improvements made in the present invention in tropospheric delay correction and multipath error extraction. Therefore, compared with the traditional method, the present invention can effectively shorten the convergence of the PPP positioning error series.

[0082] Embodiment 2:

[0083] Embodiment 2 provides a GNSS tropospheric and multipath joint modeling correction system, including:

[0084] Tropospheric delay module, used to construct a tropospheric delay semi-celestial map using ray tracing and generate tropospheric delay correction tables;

[0085] A multipath error module is used to obtain tropospheric delay information based on the tropospheric delay semi-celestial map, perform multi-system GNSS PPP data processing in combination with GNSS original observations, precision products and error correction products, extract GNSS a posteriori residual information and the altitude angle and azimuth angle corresponding to the satellite, construct a GNSS multipath error semi-celestial map, and generate a multipath error correction table;

[0086] A joint correction module is used to retrieve the multipath error correction table through the time, altitude and azimuth corresponding to the current satellite during the GNSS PPP data processing, obtain the current multipath model correction value, and correct it on the GNSS original observation value; retrieve the tropospheric delay correction table through the time, altitude and azimuth corresponding to the current satellite, obtain the current tropospheric delay information, add the current tropospheric delay information, the current precision product and the output information of the error correction product to the GNSS PPP observation equation, perform Kalman filtering on the GNSS PPP observation equation, and obtain the GNSS PPP positioning result;

[0087] The GNSS troposphere and multipath joint modeling correction system provided in Example 2 is used to execute the steps in the GNSS troposphere and multipath joint modeling correction method described in Example 1.

[0088] Since the functions of each module in the system provided in Example 2 correspond to the steps in the method provided in Example 1, they can be understood by referring to Example 1 and will not be repeated here.

[0089] Finally, it should be noted that the above specific implementation methods are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to examples, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

Claims

1. A GNSS tropospheric and multipath joint modeling correction method, characterized in that: The following steps are involved: Step 1: Use ray tracing to construct a tropospheric delay semi-spherical map and generate a tropospheric delay correction table; The ray tracing is performed based on ERA5 data and ground meteorological data; the tropospheric tilt delay covering the azimuth range of 0 to 360 degrees with an interval of 1 degree and the altitude range of 3 to 90 degrees and the corresponding mapping factors are obtained by ray tracing; a grid file is generated according to the tropospheric delay ray tracing results and their corresponding time, altitude and azimuth to form the tropospheric delay correction table; Step 2: obtaining tropospheric delay information based on the tropospheric delay semi-spherical map, performing multi-system GNSS PPP data processing on the GNSS original observations, precision products and error correction products, extracting GNSS a posteriori residual information and the altitude and azimuth angles corresponding to the satellites, constructing a GNSS multipath error semi-spherical map, and generating a multipath error correction table; Step 3: During the GNSS PPP data processing, the multipath error correction table is retrieved by using the time, altitude angle and azimuth angle corresponding to the current satellite to obtain the current multipath model correction value, and the correction is applied to the original GNSS observation value; The tropospheric delay correction table is retrieved through the time, altitude angle and azimuth angle corresponding to the current satellite to obtain the current tropospheric delay information, the current tropospheric delay information, the current precision product and the output information of the error correction product are added to the GNSS PPP observation equation, the GNSS PPP observation equation is solved by Kalman filtering, and the GNSS PPP positioning result is obtained.

2. The GNSS tropospheric and multipath joint modeling correction method according to claim 1, characterized in that: The tropospheric oblique delay includes: the tropospheric total delay, the static delay and the wet delay of the oblique path; the mapping factors include: the mapping factor of the tropospheric total delay, the mapping factor of the static delay and the mapping factor of the wet delay.

3. The GNSS tropospheric and multipath joint modeling correction method according to claim 1, characterized in that: The tropospheric delay is expressed as: STD(e,α,t)=MFH(e,α,t)·ZHD+MFW(e,α,t)·ZWD Wherein, STD(e, a, t) is the tropospheric delay, MFW(e, a, t) is the mapping factor of the static delay, MFW(e, a, t) is the mapping factor of the wet delay, ZHD and ZWD are the static delay and wet delay in the zenith direction, e is the azimuth, α is the altitude, and t is the time.

4. The GNSS tropospheric and multipath joint modeling correction method according to claim 2, characterized in that: The total tropospheric delay, static delay and wet delay of the slant path are expressed as follows: Among them, STD, SHD, SWD are the total tropospheric delay, static delay, and wet delay of the slant path, respectively; k is the number of the refractive index field altitude layer divided by ray tracing; i is the altitude layer number; are the total refractive index, static refractive index, and wet refractive index of the troposphere at the middle position of the ray node; s i is the ray length between each altitude layer, s bend is the geometric bending effect, e i is the altitude angle of each ray node.

5. The GNSS tropospheric and multipath joint modeling correction method according to claim 2, characterized in that: The mapping factors of the total tropospheric delay, the static delay and the wet delay are expressed as follows: Among them, MFT, NFH, and NFW are the mapping factors of the total tropospheric delay, the mapping factors of the static delay, and the mapping factors of the wet delay, respectively; STD, SHD, and SWD are the total tropospheric delay, the static delay, and the wet delay of the slant path, respectively; ZTD, ZHD, and ZWD are the total tropospheric delay, the static delay, and the wet delay in the zenith direction, respectively.

6. The GNSS tropospheric and multipath joint modeling correction method according to claim 1, characterized in that: The GNSS a posteriori residual information includes pseudorange and carrier phase.

7. A GNSS tropospheric and multipath joint modeling correction system, characterized in that: include: A tropospheric delay module is used to construct a tropospheric delay semi-celestial map by ray tracing and generate a tropospheric delay correction table; wherein the ray tracing is performed based on ERA5 data and ground meteorological data; tropospheric tilt delays covering an azimuth range of 0 to 360 degrees with an interval of 1 degree and an altitude range of 3 to 90 degrees and corresponding mapping factors are obtained by ray tracing; a grid file is generated according to the tropospheric delay ray tracing results and their corresponding time, altitude and azimuth angles to form the tropospheric delay correction table; A multipath error module is used to obtain tropospheric delay information based on the tropospheric delay semi-celestial map, perform multi-system GNSS PPP data processing in combination with GNSS original observations, precision products and error correction products, extract GNSS a posteriori residual information and the altitude angle and azimuth angle corresponding to the satellite, construct a GNSS multipath error semi-celestial map, and generate a multipath error correction table; The joint correction module is used to retrieve the multipath error correction table through the time, altitude and azimuth corresponding to the current satellite during the GNSS PPP data processing, obtain the current multipath model correction value, and correct it on the GNSS original observation value; retrieve the tropospheric delay correction table through the time, altitude and azimuth corresponding to the current satellite, obtain the current tropospheric delay information, add the current tropospheric delay information, the current precision product and the output information of the error correction product to the GNSS PPP observation equation, perform Kalman filtering on the GNSS PPP observation equation, and obtain the GNSS PPP positioning result; The GNSS troposphere and multipath joint modeling correction system is used to execute the steps in the GNSS troposphere and multipath joint modeling correction method as described in any one of claims 1-6.

Images