Tropospheric delay modeling method applied to mountainous environments

Abstract

The embodiment of the present application discloses a tropospheric delay modeling method for mountainous environments, which relates to the field of surveying and mapping technology. The method includes: obtaining a three-dimensional grid of zenithal tropospheric delay in a target area; calculating the interpolation weights of the first grid point in the three-dimensional zenithal tropospheric delay grid relative to all second grid points in a high-resolution two-dimensional elevation grid, resampling all first grid points to the second grid points based on the interpolation weights, and generating a tropospheric delay background field; fusing the real-time zenithal tropospheric delay information measured by GNSS stations within a preset range with the corresponding grid points, and outputting the fused tropospheric delay information. Using the method provided by the present application, a high-precision, high-resolution tropospheric delay model constructed based on GNSS and ERA5 data can improve the tropospheric delay accuracy in areas with large elevation differences, which is of great significance for enhancing the real-time precision positioning performance in complex terrain.

Description

Technical Field

[0001] The present application relates to the field of surveying and mapping technology, and in particular to a tropospheric delay modeling method applied to mountainous environments. Background Art

[0002] As electromagnetic wave signals from the Global Navigation Satellite System (GNSS) pass through Earth's neutral atmosphere, they are affected by atmospheric refraction, resulting in tropospheric delay. When using GNSS for precise positioning in various application scenarios, tropospheric delay can cause ranging errors ranging from several meters to tens of meters, severely impacting positioning accuracy and reliability. Therefore, accurately measuring atmospheric delay errors is crucial to improving GNSS's high-precision positioning services.

[0003] Related technologies can establish tropospheric delay models through classical tropospheric delay models, by interpolating / fitting the tropospheric delay of GNSS continuously operating reference stations, and by establishing tropospheric delay models based on numerical forecast model analysis and reanalysis data. However, these methods have the following defects: (1) The accuracy of traditional empirical tropospheric delay models is low and it is difficult to meet the needs of high-precision positioning; (2) The tropospheric delay models based on numerical model reanalysis data have low temporal and spatial resolutions and are difficult to apply to complex mountainous environments. In complex mountainous environments with large altitude differences and uneven altitude distribution, they cannot provide local detailed information, and therefore cannot meet the needs of fine modeling in complex mountainous areas; (3) The modeling accuracy of the tropospheric delay models based on GNSS stations is limited by the number and distribution of stations. The existing GNSS ground-based reference station network is small in number and unevenly distributed. Especially in mountainous areas with complex terrain, it is difficult to select GNSS ground-based reference stations that meet the needs. Therefore, it is difficult to provide a unified, seamless, and uniformly accurate tropospheric delay correction model on a global / regional scale.

[0004] Therefore, in order to solve the above problems, a tropospheric delay modeling method that is applicable to complex mountainous areas is needed. Summary of the Invention

[0005] The present application provides a tropospheric delay modeling method for mountainous environments to address the deficiencies in the above-mentioned related technologies. The technical solution is as follows:

[0006] In a first aspect, an embodiment of the present application provides a tropospheric delay modeling method applied to a mountainous environment, characterized by comprising:

[0007] Obtain the 3D grid of zenith tropospheric delay in the target area;

[0008] Obtaining an interpolation weight for each first grid point according to a horizontal distance and an elevation difference between each first grid point in the zenith tropospheric delay three-dimensional grid and a second grid point in the elevation grid of the target area obtained based on a digital elevation model;

[0009] resampling all first grid points to corresponding second grid points based on the interpolation weights to generate a tropospheric delay background field;

[0010] The real-time zenith tropospheric delay information measured by the GNSS stations within a preset range around each background field grid point in the tropospheric delay background field is fused with the corresponding grid point, and the fused tropospheric delay information is output.

[0011] In an optional solution of the first aspect, the real-time zenith tropospheric delay information measured by the GNSS station is measured based on the following steps, including:

[0012] Acquire a floating ambiguity of a first frequency and a floating ambiguity of a second frequency, and calculate a widelane floating ambiguity based on the floating ambiguity of the first frequency and the floating ambiguity of the second frequency;

[0013] Correcting the widelane float ambiguity based on an initial phase fractional deviation to obtain a fixed widelane float ambiguity;

[0014] calibrating a fractional phase deviation of a first frequency and a fractional phase deviation of a second frequency based on the fixed widelane floating ambiguity;

[0015] The GNSS station can obtain the real-time zenith tropospheric delay information based on the calibrated phase fractional deviation measurement.

[0016] In an optional solution of the first aspect, obtaining a three-dimensional grid of zenith tropospheric delay in a target area includes:

[0017] Based on the EAR5 analysis data, the meteorological elements of the ground layer and each isobaric surface layer are obtained, and the zenith tropospheric delay three-dimensional grid is calculated based on the meteorological elements. The formula is:

[0018]

[0019] ;

[0020] in, is the top isobaric surface, is the ground layer, ZTD is the zenith tropospheric delay from the ground layer to the top isobaric surface; is the gas constant of dry air, is the gas constant of moist air; 、 and is a constant; is the atmospheric pressure at the top isobaric surface, is the gravitational acceleration at the top isobaric surface, is the atmospheric temperature, is the air pressure, For specific humidity.

[0021] In an optional solution of the first aspect, obtaining the interpolation weight of each first grid point based on the horizontal distance and elevation difference between each first grid point in the zenith tropospheric delay three-dimensional grid and a second grid point in the elevation grid of the target area obtained based on the digital elevation model includes:

[0022] Calculating a horizontal weight based on a horizontal distance between each first grid point in the zenith tropospheric delay three-dimensional grid and a second grid point in the elevation grid of the target area obtained based on a digital elevation model;

[0023] Calculating an elevation difference weight according to an elevation difference between each first grid point in the zenith tropospheric delay three-dimensional grid and a second grid point in the elevation grid of the target area obtained based on a digital elevation model;

[0024] The interpolation weight is calculated based on the horizontal weight and the height difference weight.

[0025] In an optional solution of the first aspect, before fusing the real-time zenith tropospheric delay information measured by GNSS stations within a preset range around each background field grid point in the tropospheric delay background field with the corresponding grid point, the method further includes:

[0026] Acquire a tropospheric delay profile from the ground to a preset elevation based on the zenith tropospheric delay three-dimensional grid;

[0027] Calculating a zenith tropospheric delay vertical scaling factor based on the tropospheric delay profile;

[0028] Averaging within a grid of a preset resolution to obtain an average zenith tropospheric delay vertical scaling factor within the target area;

[0029] The fusing of the real-time zenith tropospheric delay information measured by the GNSS stations within a preset range around each background field grid point in the tropospheric delay background field with the corresponding grid point includes:

[0030] GNSS stations within a preset range around each background field grid point are selected, and the real-time zenith tropospheric delay information measured by the GNSS stations within the preset range is interpolated to the elevation of the background field grid point based on the average zenith tropospheric delay vertical scaling factor.

[0031] In an optional solution of the first aspect, the fusing of the real-time zenith tropospheric delay information measured by GNSS stations within a preset range around each background field grid point in the tropospheric delay background field with the corresponding grid point, and outputting the fused tropospheric delay information, includes:

[0032] Calculating the influence weight of the corresponding GNSS station according to the distance between the GNSS station within a preset range around the background field grid point and the background field grid point and the influence radius of the corresponding GNSS station;

[0033] The fused tropospheric delay of the background field grid point is calculated based on the real-time zenith tropospheric delay information measured by all GNSS stations within a preset range around the background field grid point and the corresponding weights and the tropospheric delay of the background field grid point;

[0034] A fused tropospheric delay is obtained based on the fused tropospheric delays of all the background field grid points, and the fused tropospheric delay information is output.

[0035] In a second aspect, an embodiment of the present application further provides a tropospheric delay modeling device for use in a mountainous environment, comprising an information module, a background field generation module, and a fusion module, specifically including:

[0036] An information module is used to obtain the three-dimensional grid of zenith tropospheric delay in the target area;

[0037] A background field generation module is configured to obtain an interpolation weight for each first grid point in the zenith tropospheric delay three-dimensional grid according to a horizontal distance and an elevation difference between each first grid point in the zenith tropospheric delay three-dimensional grid and a second grid point in the elevation grid of the target area obtained based on the digital elevation model; the background field generation module is further configured to resample all first grid points to corresponding second grid points using the interpolation weights to generate a tropospheric delay background field;

[0038] A fusion module is used to fuse the real-time zenith tropospheric delay information measured by GNSS stations within a preset range around each background field grid point in the tropospheric delay background field with the corresponding grid point, and output the fused tropospheric delay information.

[0039] In a third aspect, an embodiment of the present application further provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method provided in the first aspect of the embodiment of the present application or any one of the implementations of the first aspect is implemented.

[0040] In a fourth aspect, the present application also provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, it implements the method provided by the first aspect of the embodiment of the present application or any one of the implementation methods of the first aspect.

[0041] The beneficial effects of the technical solutions provided by some embodiments of the present application include at least:

[0042] The embodiment of the present application provides a tropospheric delay modeling method for mountainous environments, which can not only take into account the changes in tropospheric delay with elevation and construct a tropospheric delay background field with high spatial resolution, but also further integrate multi-source data to enhance the ability to simulate tropospheric delay in a refined manner with atmospheric information at different scales. The high-precision, high-resolution tropospheric delay model constructed in this application based on GNSS and ERA5 data can improve the accuracy of tropospheric delay in areas with large elevation differences, and is of great significance for enhancing the real-time precision positioning performance under complex terrain. In addition, it can be applied to the data solution process of GNSS monitoring stations in landslide deformation areas, improve the reliability of GNSS deformation sequence results, and further enhance the GNSS landslide monitoring and early warning performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in this application or related technologies, the following briefly introduces the drawings required for use in the embodiments or related technical descriptions. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0044] Figure 1 This is a flow chart of a tropospheric delay modeling method applied to a mountainous environment according to an embodiment of the present application;

[0045] Figure 2 1 is a schematic structural diagram of a tropospheric delay modeling device for use in a mountainous environment, provided in an embodiment of the present application;

[0046] Figure 3 It is a structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0047] To make the objectives, technical solutions, and advantages of this application more clear, the technical solutions of this application will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments of this application, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of this application.

[0048] The terms "including" and "having," and any variations thereof, in the specification and claims of this application and the accompanying drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or modules is not limited to the listed steps or modules, but may optionally include steps or modules not listed, or may optionally include other steps or modules inherent to the process, method, product, or apparatus.

[0049] It should be noted that the terms "first" and "second" used in this application are merely used to distinguish similar objects and do not represent a specific ordering of the objects. It is understood that the terms "first" and "second" may interchangeably represent a specific order or precedence, where permitted. It should be understood that the objects distinguished by "first" and "second" may interchangeably represent a specific order or precedence, where appropriate, such that the embodiments of the present application described herein can be implemented in an order other than that described or illustrated herein.

[0050] Understandably, tropospheric delay is one of the sources of GNSS positioning error. Tropospheric delay in satellite navigation positioning generally refers to the signal delay caused by electromagnetic wave signals when passing through the non-ionized neutral atmosphere below an altitude of 50km. This delay varies with the refractive index of the troposphere, which is also affected by the temperature, pressure and relative humidity of the corresponding area. Therefore, in non-plain areas with large altitude differences, temperature, air pressure and humidity vary with altitude, making GNSS-based positioning in complex mountainous areas easily affected by tropospheric delay errors.

[0051] Among them, the troposphere is the lowest layer of the atmosphere, which is characterized by a decrease in temperature with increasing altitude. This temperature gradient causes convection movement of air in the atmosphere.

[0052] It should be noted that the embodiments of the present application are mainly used in application scenarios for measuring tropospheric delay in complex mountainous environments, that is, non-plain areas with large altitude differences. The background field is obtained by combining elevation information and the three-dimensional grid of tropospheric delay, and then the real-time tropospheric delay of the GNSS measurement stations around the grid points in the background field is integrated to obtain a tropospheric delay model suitable for mountainous environments. It can more accurately reflect the distribution of tropospheric delay in mountainous environments and improve positioning accuracy in complex mountainous environments.

[0053] The tropospheric delay modeling method for mountainous environments provided in the embodiments of the present application can improve positioning accuracy, thereby improving the deformation monitoring accuracy of structures such as mountains and buildings, improving the reliability of GNSS deformation sequence results, and further enhancing the GNSS landslide monitoring and early warning performance.

[0054] The present application is described in detail below with reference to specific embodiments.

[0055] Next, combine Figure 1 Taking any terminal executing the tropospheric delay modeling method applied to a mountainous environment as an example, the tropospheric delay modeling method applied to a mountainous environment includes the following steps:

[0056] S101, obtaining a three-dimensional grid of zenith tropospheric delay in a target area.

[0057] Specifically, the target area may be a selected geographical area, such as a mountainous area, a scenic area, a valley, etc. The boundary of the target area may be determined by longitude and latitude coordinates, which is not limited in the embodiments of the present application.

[0058] Specifically, the meteorological elements of the ground layer and each isobaric surface layer can be obtained based on the EAR5 analysis data, and the zenith tropospheric delay three-dimensional grid can be calculated based on the meteorological elements. The specific application is the following formula:

[0059]

[0060] ;

[0061] in, is the top isobaric surface, is the surface layer, ZTD is the zenith tropospheric delay from the surface layer to the top isobaric surface; is the gas constant of dry air, is the gas constant of moist air; 、 and is a constant; is the atmospheric pressure at the top isobaric surface, is the gravitational acceleration at the top isobaric surface, is the atmospheric temperature, is the air pressure, For specific humidity.

[0062] It should be noted that the ERA5 analysis data is the fifth-generation atmospheric reanalysis dataset of the global climate from January 1950 to the present, compiled by the European Centre for Medium-Range Weather Forecasts (ECMWF). ERA5 provides hourly estimates of a large number of atmospheric, land, and oceanic climate variables. This data covers the Earth on a 30-kilometer grid and uses 137 altitudes from the surface to 80 kilometers to resolve the atmosphere. It includes uncertainty information for all variables at reduced spatial and temporal resolution. ERA5 combines model data with observations from around the world to form a globally complete and consistent dataset.

[0063] Specifically, the resolution of the three-dimensional grid of zenith tropospheric delay obtained based on ERA5 is 0.25°×0.25°.

[0064] S102: Obtain an interpolation weight for each first grid point based on a horizontal distance and an elevation difference between each first grid point in the zenith tropospheric delay three-dimensional grid and a second grid point in the elevation grid of the target area obtained based on the digital elevation model.

[0065] Specifically, the two-dimensional elevation grid of the target area can be obtained through the digital elevation model. Each elevation grid point on the two-dimensional elevation grid is the above-mentioned second grid point. Each grid point corresponds to the corresponding longitude and latitude coordinates and records the elevation information at the corresponding longitude and latitude coordinates.

[0066] Specifically, when generating a tropospheric delay background field based on a three-dimensional zenithal tropospheric delay grid and a two-dimensional elevation grid, the numerical value of each first grid point in the three-dimensional zenithal tropospheric delay grid can be interpolated into the two-dimensional elevation grid to generate the tropospheric delay background field. Specifically, the horizontal distance and elevation difference between each first grid point in the three-dimensional zenithal tropospheric delay grid and a second grid point in the two-dimensional elevation grid can be calculated, and the interpolation weight of each first grid point relative to the second grid point can be calculated.

[0067] Exemplarily, there are first grid points A1, A2, A3, and A4 in the three-dimensional grid of the zenith tropospheric delay, and there are second grid points B1, B2, B3, and B4 in the two-dimensional elevation grid. The interpolation weights C{c1, c2, c3, c4} of the first grid points A1, A2, A3, and A4 relative to the second grid point B1 are calculated respectively, where c1 is the interpolation weight of the first grid point A1 relative to the second grid point B1, c2 is the interpolation weight of the first grid point A2 relative to the second grid point B1, c3 is the interpolation weight of the first grid point A3 relative to the second grid point B1, and c4 is the interpolation weight of the first grid point A4 relative to the second grid point B1; based on this, the interpolation weights of the first grid points A1, A2, A3, and A4 relative to other second grid points are calculated in sequence.

[0068] Specifically, the process of calculating the interpolation weights includes the following steps:

[0069] The horizontal weight is calculated based on the horizontal distance between each first grid point in the 3D zenith tropospheric delay grid and the second grid point in the elevation grid of the target area obtained based on the digital elevation model, using the formula:

[0070] ;

[0071] in, is the horizontal distance weight, d is the horizontal distance between the first grid point and the second grid point.

[0072] The height difference weight is calculated based on the elevation difference between each first grid point in the 3D zenith tropospheric delay grid and the second grid point in the elevation grid of the target area obtained based on the digital elevation model, using the formula:

[0073] ;

[0074] in, is the elevation difference between the first grid point and the second grid point, is the minimum elevation difference threshold between the two, for example, the minimum elevation difference threshold is 50m. The maximum elevation difference threshold between the two, for example, the maximum elevation difference threshold is 500m.

[0075] Furthermore, the interpolation weight is calculated based on the horizontal weight and the height difference weight, and the formula is applied:

[0076] ;

[0077] in, is the coefficient of the level weight, is the height difference weight.

[0078] Further, S103 is executed to resample all first grid points to corresponding second grid points based on the interpolation weights to generate a tropospheric delay background field.

[0079] Preferably, after the elevation grid is generated based on the digital elevation model, the resolution of the elevation grid may be resampled to 0.1°×0.1° to obtain a high-resolution elevation grid.

[0080] Preferably, each first grid point in the zenith tropospheric delay three-dimensional grid is resampled to a high-resolution elevation grid based on the interpolation weights calculated in S102 to obtain a tropospheric delay background field with a resolution of 0.1°×0.1°.

[0081] In some embodiments, when the geographical environment of the target area is relatively simple, such as but not limited to plain areas, gentle wetlands, areas with small height differences, areas with gentle slopes, etc., calculations can be performed only based on the ground grid points in the zenith tropospheric delay three-dimensional grid, thereby reducing the complexity of the calculation and improving the calculation efficiency, including: calculating the horizontal distance and elevation difference between each ground grid point and the second grid point in the elevation grid to obtain the interpolation weight of each ground grid point, and then executing step S103, generating the interpolation weight based on each ground grid point based on the ground grid point, and resampling all the ground grid points to the corresponding second grid points to generate the tropospheric delay background field.

[0082] S104: fusing the real-time zenith tropospheric delay information measured by the GNSS stations within a preset range around each background field grid point in the tropospheric delay background field with the corresponding grid point, and outputting the fused tropospheric delay information.

[0083] Specifically, with each background field grid point as the center, GNSS stations within a preset range are selected. For example, all GNSS stations within a circular range with a radius of 50 km and a background field grid point as the center are searched to obtain the zenith tropospheric delay information obtained by real-time measurement of the GNSS stations within the preset range.

[0084] In some embodiments, the ambiguity fixation of Precise Point Positioning (PPP) can be achieved based on the initial observation values ​​of the GNSS site, the precise orbit and clock products, and the integer decimal deviation products, so as to obtain high-precision real-time zenith tropospheric delay information.

[0085] Specifically, the following steps can be used to correct or eliminate the fractional cycle deviations between the satellite and receiver ends, thereby restoring the integer characteristics of the ambiguity parameters and fixing the ambiguity. Specifically, they include:

[0086] Get the floating point ambiguity of the first frequency L1 and the floating ambiguity of the second frequency L2 , based on the floating point ambiguity of the first frequency and the floating point ambiguity of the second frequency Calculate the wide lane floating point ambiguity , apply the formula:

[0087] ;

[0088] Furthermore, the wide-lane floating ambiguity is corrected based on the initial phase decimal deviation to obtain a fixed wide-lane floating ambiguity. The initial phase decimal deviation is the uncalibrated phase decimal deviation (UPD) based on the satellite wide-lane. Due to the long wavelength of the wide-lane, the wide-lane floating ambiguity can be fixed by directly rounding.

[0089] Furthermore, the fractional phase deviation of the first frequency and the fractional phase deviation of the second frequency are calibrated based on the fixed widelane floating ambiguity, and the formula is applied:

[0090] ;

[0091] in, is the fractional phase deviation corresponding to the first frequency, is the fractional phase deviation corresponding to the second frequency, is the fractional phase deviation corresponding to the wide-lane floating-point ambiguity, is the fractional phase deviation corresponding to the narrow lane floating point ambiguity, is the calculation parameter.

[0092] Furthermore, the GNSS station may obtain the real-time zenith tropospheric delay information based on the calibrated phase fractional deviation measurement.

[0093] Specifically, the tropospheric delay background field and the real-time zenith tropospheric delay information are fused through the step-by-step correction method. The specific calculation method is as follows:

[0094] ;

[0095] ;

[0096] in, is the tropospheric delay of the corresponding grid i after fusion, is the tropospheric delay of the background field corresponding to grid i in the tropospheric delay background field, is the zenith tropospheric delay information measured in real time by GNSS observation station k, K represents the total number of observation stations, k represents one of the K observation stations, represents the weight of station k relative to grid i, R is the influence radius of the observation station, is the distance between observation station k and grid point i, is the ratio of the observation error variance to the background field error variance.

[0097] Based on the above embodiments, a fused tropospheric delay grid value can be obtained, and the obtained tropospheric delay has an accuracy of more than 1 cm, which can meet the requirements of GNSS real-time precise positioning in complex mountainous environments.

[0098] In some embodiments, before fusing the real-time zenith tropospheric delay information measured by GNSS stations within a preset range around each background field grid point in the tropospheric delay background field with the corresponding grid point, calculating the vertical lapse rate of the tropospheric delay to correct the elevation information in the tropospheric delay background field includes:

[0099] The tropospheric delay profile from the ground to a preset elevation is obtained based on the zenith tropospheric delay three-dimensional grid. That is, a grid located on the ground in the zenith tropospheric delay three-dimensional grid is selected to generate a tropospheric delay profile from the ground grid to a preset elevation, for example, a tropospheric delay profile from the ground grid to a vertical height of 4 kilometers from the ground.

[0100] Furthermore, the zenith tropospheric delay vertical scaling factor is calculated based on the tropospheric delay profile, and the zenith tropospheric delay vertical lapse rate, i.e., the zenith tropospheric delay vertical scaling factor, can be obtained by fitting the tropospheric delay profile with an exponential function.

[0101] Furthermore, averaging is performed within a grid of a preset resolution, and the average value of the zenith tropospheric delay vertical scaling factor generated based on each grid within a given grid of a preset resolution is averaged to obtain the average zenith tropospheric delay vertical scaling factor in the target area.

[0102] Specifically, S104 also includes:

[0103] Select GNSS stations within a preset range around each background grid point, and interpolate the real-time zenith tropospheric delay information measured by the GNSS stations within the preset range to the elevation of the background grid point based on the mean zenith tropospheric delay vertical scaling factor, applying the formula:

[0104] ;

[0105] in, Elevation h The tropospheric delay at is the tropospheric delay at the ground, and is the air pressure value at the corresponding altitude, is the elevation scaling factor.

[0106] The following are device embodiments of the present application, which can be used to implement the method embodiments of the present application. For details not disclosed in the device embodiments of the present application, please refer to the method embodiments of the present application.

[0107] See next Figure 2 , which is a schematic diagram of the structure of a tropospheric delay modeling device for mountainous environments provided by an exemplary embodiment of the present application. The device can be implemented as all or part of a terminal through software, hardware, or a combination of both, or can be integrated into a server as an independent module. The tropospheric delay modeling device for mountainous environments in the embodiment of the present application can be applied to a terminal or the cloud. The device 20 includes an information module 210, a background field generation module 220, and a fusion module 230, wherein:

[0108] Information module 210, for obtaining a three-dimensional grid of zenith tropospheric delay in a target area;

[0109] A background field generation module 220 is configured to obtain an interpolation weight for each first grid point in the zenith tropospheric delay three-dimensional grid based on a horizontal distance and an elevation difference between each first grid point and a second grid point in the elevation grid of the target area obtained based on a digital elevation model; the background field generation module 220 is further configured to resample all first grid points to corresponding second grid points using the interpolation weights to generate a tropospheric delay background field;

[0110] The fusion module 230 is used to fuse the real-time zenith tropospheric delay information measured by the GNSS stations within a preset range around each background field grid point in the tropospheric delay background field with the corresponding grid point, and output the fused tropospheric delay information.

[0111] It should be noted that the apparatus 20 provided in the above embodiment, when executing the method for modeling tropospheric delay in mountainous environments, is merely illustrated by the division of the aforementioned functional modules. In actual applications, the aforementioned functions can be assigned to different functional modules as needed, i.e., the internal structure of the apparatus can be divided into different functional modules to complete all or part of the functions described above. Furthermore, the apparatus provided in the above embodiment and the embodiment of the method for modeling tropospheric delay in mountainous environments are based on the same concept. The implementation process is detailed in the method embodiment and will not be further described here.

[0112] 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 executable on the processor. When the processor executes the program, the steps of the method provided in any of the above embodiments are implemented.

[0113] See Figure 3 , is a structural block diagram of an electronic device provided in an embodiment of the present application.

[0114] like Figure 3 As shown, the electronic device 300 includes a processor 301 and a memory 302 .

[0115] In the embodiment of the present application, the processor 301 is the control center of the computer system and can be the processor of a physical machine or the processor of a virtual machine. The processor 301 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 301 can be implemented in the form of at least one hardware of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), or PLA (Programmable Logic Array).

[0116] The processor 301 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state.

[0117] The memory 302 may include one or more computer-readable storage media, which may be non-transitory. The memory 302 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices and flash memory storage devices. In some embodiments of the present application, the non-transitory computer-readable storage medium in the memory 302 is used to store at least one instruction, which is used to be executed by the processor 301 to implement the method in the embodiment of the present application.

[0118] In some embodiments, the electronic device 300 further includes a peripheral device interface 303 and at least one peripheral device. The processor 301, memory 302, and peripheral device interface 303 may be connected via a bus or signal lines. Each peripheral device 304 may be connected to the peripheral device interface 303 via a bus, signal lines, or circuit boards. Specifically, the peripheral devices 304 may include a display screen, a camera, and an audio circuit. The peripheral device interface 303 may be used to connect at least one I / O (Input / Output)-related peripheral device 304 to the processor 301 and memory 302.

[0119] In some embodiments of the present application, the processor 301, the memory 302, and the peripheral device interface 303 are integrated on the same chip or circuit board; in some other embodiments of the present application, any one or two of the processor 301, the memory 302, and the peripheral device interface 303 may be implemented on separate chips or circuit boards. This embodiment of the present application is not specifically limited to this.

[0120] The electronic device structure block diagram shown in the embodiment of the present application does not constitute a limitation on the electronic device 300. The electronic device 300 may include more or fewer components than shown in the figure, or combine certain components, or adopt a different component arrangement.

[0121] The present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method of any of the aforementioned embodiments. The computer-readable storage medium may include, but is not limited to, any type of disk, including a floppy disk, an optical disk, a DVD, a CD-ROM, a microdrive and a magneto-optical disk, a ROM, a RAM, an EPROM, an EEPROM, a DRAM, a VRAM, a flash memory device, a magnetic or optical card, a nanosystem (including a molecular memory IC), or any other type of medium or device suitable for storing instructions and / or data.

[0122] Through the description of the above embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the relevant technology, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods described in each embodiment or certain portions of the embodiments.

[0123] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A tropospheric delay modeling method for mountainous environments, characterized in that: include: Obtain the 3D grid of zenith tropospheric delay in the target area; Obtaining an interpolation weight for each first grid point according to a horizontal distance and an elevation difference between each first grid point in the zenith tropospheric delay three-dimensional grid and a second grid point in the elevation grid of the target area obtained based on a digital elevation model; resampling all first grid points to corresponding second grid points based on the interpolation weights to generate a tropospheric delay background field; The real-time zenith tropospheric delay information measured by the GNSS stations within a preset range around each background field grid point in the tropospheric delay background field is fused with the corresponding grid point, and the fused tropospheric delay information is output.

2. The tropospheric delay modeling method for mountainous environments according to claim 1, characterized in that: The real-time zenith tropospheric delay information measured by the GNSS station is measured based on the following steps, including: Acquire a floating ambiguity of a first frequency and a floating ambiguity of a second frequency, and calculate a widelane floating ambiguity based on the floating ambiguity of the first frequency and the floating ambiguity of the second frequency; Correcting the widelane float ambiguity based on an initial phase fractional deviation to obtain a fixed widelane float ambiguity; calibrating a fractional phase deviation of a first frequency and a fractional phase deviation of a second frequency based on the fixed widelane floating ambiguity; The GNSS station can obtain the real-time zenith tropospheric delay information based on the calibrated phase fractional deviation measurement.

3. The tropospheric delay modeling method for mountainous environments according to claim 1, characterized in that: The step of obtaining a three-dimensional grid of zenith tropospheric delay in a target area includes: Based on the EAR5 analysis data, the meteorological elements of the ground layer and each isobaric surface layer are obtained, and the zenith tropospheric delay three-dimensional grid is calculated based on the meteorological elements. The formula is: ； in, is the top isobaric surface, is the ground layer, ZTD is the zenith tropospheric delay from the ground layer to the top isobaric surface; is the gas constant of dry air, is the gas constant of moist air; 、 and is a constant; is the atmospheric pressure at the top isobaric surface, is the gravitational acceleration at the top isobaric surface, is the atmospheric temperature, is the air pressure, For specific humidity.

4. The tropospheric delay modeling method for mountainous environments according to claim 1, characterized in that: The interpolation weight of each first grid point is obtained according to the horizontal distance and elevation difference between each first grid point in the zenith tropospheric delay three-dimensional grid and a second grid point in the elevation grid of the target area obtained based on the digital elevation model, including: Calculating a horizontal weight based on a horizontal distance between each first grid point in the zenith tropospheric delay three-dimensional grid and a second grid point in the elevation grid of the target area obtained based on a digital elevation model; Calculating an elevation difference weight according to an elevation difference between each first grid point in the zenith tropospheric delay three-dimensional grid and a second grid point in the elevation grid of the target area obtained based on a digital elevation model; The interpolation weight is calculated based on the horizontal weight and the height difference weight.

5. The tropospheric delay modeling method for mountainous environments according to claim 1, characterized in that: Before fusing the real-time zenith tropospheric delay information measured by GNSS stations within a preset range around each background field grid point in the tropospheric delay background field with the corresponding grid point, the method further includes: Acquire a tropospheric delay profile from the ground to a preset elevation based on the zenith tropospheric delay three-dimensional grid; Calculating a zenith tropospheric delay vertical scaling factor based on the tropospheric delay profile; Averaging within a grid of a preset resolution to obtain an average zenith tropospheric delay vertical scaling factor within the target area; The fusing of the real-time zenith tropospheric delay information measured by the GNSS stations within a preset range around each background field grid point in the tropospheric delay background field with the corresponding grid point includes: GNSS stations within a preset range around each background field grid point are selected, and the real-time zenith tropospheric delay information measured by the GNSS stations within the preset range is interpolated to the elevation of the background field grid point based on the average zenith tropospheric delay vertical scaling factor.

6. The tropospheric delay modeling method for mountainous environments according to claim 5, characterized in that: The step of fusing the real-time zenith tropospheric delay information measured by GNSS stations within a preset range around each background field grid point in the tropospheric delay background field with the corresponding grid point and outputting the fused tropospheric delay information comprises: Calculating the influence weight of the corresponding GNSS station according to the distance between the GNSS station within a preset range around the background field grid point and the background field grid point and the influence radius of the corresponding GNSS station; The fused tropospheric delay of the background field grid point is calculated based on the real-time zenith tropospheric delay information measured by all GNSS stations within a preset range around the background field grid point and the corresponding weights and the tropospheric delay of the background field grid point; A fused tropospheric delay is obtained based on the fused tropospheric delays of all the background field grid points, and the fused tropospheric delay information is output.

7. A tropospheric delay modeling device for use in mountainous environments, characterized in that: include: An information module is used to obtain the three-dimensional grid of zenith tropospheric delay in the target area; A background field generation module is configured to obtain an interpolation weight of each first grid point according to a horizontal distance and an elevation difference between each first grid point in the zenith tropospheric delay three-dimensional grid and a second grid point in the elevation grid of the target area obtained based on a digital elevation model; The background field generation module is further configured to resample all first grid points to corresponding second grid points using the interpolation weights to generate a tropospheric delayed background field; A fusion module is used to fuse the real-time zenith tropospheric delay information measured by GNSS stations within a preset range around each background field grid point in the tropospheric delay background field with the corresponding grid point, and output the fused tropospheric delay information.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

Images