Method and device for determining water vapor density, computer equipment and storage medium

Abstract

The application relates to a water vapor density determination method and device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: obtaining water vapor field information of a global navigation satellite system, observation network data and remote sensing data, wherein the water vapor field information comprises zenith troposphere wet delay data; determining a tomographic equation according to the observation network data, the water vapor field information and the remote sensing data, wherein the tomographic equation comprises a design matrix of a tomographic observation equation and a vertical constraint equation; solving the tomographic equation to obtain a tomographic solution result, and determining water vapor density according to the tomographic solution result. The method can improve the accuracy of calculating water vapor density.

Description

Technical Field

[0001] This application relates to the field of meteorological technology, and in particular to a method, apparatus, computer equipment, and storage medium for determining water vapor density. Background Technology

[0002] Water vapor (WV) is an important meteorological parameter, its distribution and dynamics closely related to weather phenomena, but it is also one of the most difficult meteorological parameters to characterize. In existing technologies, zenith tropospheric wet delay data generated through GPS data processing can be mapped onto precipitable water vapor (PWV), representing a two-dimensional distribution of WV, thus enabling water vapor monitoring. However, the solutions to the tomographic equations in existing technologies are not accurate enough, resulting in inaccurate water vapor monitoring. Summary of the Invention

[0003] Therefore, it is necessary to provide a method, apparatus, computer equipment, computer-readable storage medium, and computer program product for determining water vapor density to address the aforementioned technical problems.

[0004] Firstly, this application provides a method for determining water vapor density. The method includes:

[0005] Acquire water vapor field information, observation network data, and remote sensing data from the Global Navigation Satellite System. The water vapor field information includes zenith tropospheric wet delay data.

[0006] Based on observation network data, water vapor field information, and remote sensing data, the tomographic equations are determined. The tomographic equations include the design matrices of the tomographic observation equations and the vertical constraint equations, respectively.

[0007] The chromatography equation is solved to obtain the chromatography solution, and the water vapor density is determined based on the chromatography solution.

[0008] In one embodiment, the process of determining the design matrix of the vertical constraint equation includes:

[0009] Based on remote sensing data, vertical constraint equations are constructed, and the design matrix of the vertical constraint equations is determined.

[0010] In one embodiment, the process of determining the design matrix of the tomographic observation equation includes:

[0011] Based on the observation network data, a tomographic observation equation is constructed, and the design matrix of the tomographic observation equation is determined.

[0012] In one embodiment, prior to determining the torsion equation, the method further includes:

[0013] Interpolation processing was performed on the zenith tropospheric wet delay data to obtain virtual zenith tropospheric wet delay data.

[0014] In one embodiment, the tomographic equations are determined based on observation network data, water vapor field information, and remote sensing data, including:

[0015] By projecting the zenith tropospheric wet delay data and the virtual zenith tropospheric wet delay data onto the observation station direction of the global navigation satellite system, oblique path wet delay data and virtual oblique path wet delay data are obtained, respectively.

[0016] Multiply the oblique path wet delay data and the virtual oblique path wet delay data by the conversion factor to obtain the oblique path water vapor content and the virtual oblique path water vapor content, respectively.

[0017] The tomographic equations were determined based on the oblique path water vapor content, the virtual oblique path water vapor content, observation network data, and remote sensing data.

[0018] In one embodiment, the tomographic equation is determined based on oblique path water vapor content, virtual oblique path water vapor content, observation network data, and remote sensing data, including:

[0019]

[0020] Where SWV is the water vapor content along the oblique path, SWV' is the virtual oblique path water vapor content, A and B are the design matrices of the tomographic observation equations, X is the water vapor density, and V is the design matrix of the vertical constraint equations.

[0021] Secondly, this application also provides an apparatus for determining water vapor density. The apparatus includes:

[0022] The acquisition module is used to acquire water vapor field information, observation network data and remote sensing data from the Global Navigation Satellite System. The water vapor field information includes zenith tropospheric wet delay data.

[0023] The first determining module is used to determine the tomographic equations based on observation network data, water vapor field information and remote sensing data. The tomographic equations include the design matrices of the tomographic observation equations and the vertical constraint equations, respectively.

[0024] The second determining module is used to solve the chromatography equation, obtain the chromatography solution, and determine the water vapor density based on the chromatography solution.

[0025] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to perform the following steps:

[0026] Acquire water vapor field information, observation network data, and remote sensing data from the Global Navigation Satellite System. The water vapor field information includes zenith tropospheric wet delay data.

[0027] Based on observation network data, water vapor field information, and remote sensing data, the tomographic equations are determined. The tomographic equations include the design matrices of the tomographic observation equations and the vertical constraint equations, respectively.

[0028] The chromatography equation is solved to obtain the chromatography solution, and the water vapor density is determined based on the chromatography solution.

[0029] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, performs the following steps:

[0030] Acquire water vapor field information, observation network data, and remote sensing data from the Global Navigation Satellite System. The water vapor field information includes zenith tropospheric wet delay data.

[0031] Based on observation network data, water vapor field information, and remote sensing data, the tomographic equations are determined. The tomographic equations include the design matrices of the tomographic observation equations and the vertical constraint equations, respectively.

[0032] The chromatography equation is solved to obtain the chromatography solution, and the water vapor density is determined based on the chromatography solution.

[0033] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, performs the following steps:

[0034] Acquire water vapor field information from the Global Navigation Satellite System, as well as observation network data and remote sensing data. The water vapor field information includes zenith tropospheric wet delay data.

[0035] Based on observation network data, water vapor field information, and remote sensing data, the tomographic equations are determined. The tomographic equations include the design matrices of the tomographic observation equations and the vertical constraint equations, respectively.

[0036] The chromatography equation is solved to obtain the chromatography solution, and the water vapor density is determined based on the chromatography solution.

[0037] The aforementioned method, apparatus, computer equipment, storage medium, and computer program product for determining water vapor density acquire water vapor field information from the Global Navigation Satellite System, observation network data, and remote sensing data. The water vapor field information includes zenith tropospheric wet delay data. Based on the observation network data, water vapor field information, and remote sensing data, tomographic equations are determined, including the design matrices for both the tomographic observation equations and the vertical constraint equations. The tomographic equations are solved to obtain the tomographic solution results, and the water vapor density is determined based on these results. This method improves the accuracy of water vapor monitoring. Attached Figure Description

[0038] Figure 1This is a diagram illustrating the application environment of a method for determining water vapor density in one embodiment.

[0039] Figure 2 This is a flowchart illustrating a method for determining water vapor density in one embodiment;

[0040] Figure 3 This is a flowchart illustrating the method for determining water vapor density in another embodiment;

[0041] Figure 4 This is a structural block diagram of a device for determining water vapor density in one embodiment;

[0042] Figure 5 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0044] It is understood that the terms "first," "second," etc., used in this application may be used to describe various technical terms, but unless otherwise specified, these technical terms are not limited to these terms. These terms are only used to distinguish one technical term from another. For example, without departing from the scope of this application, the third preset threshold and the fourth preset threshold may be the same or different.

[0045] The method for determining water vapor density provided in this application embodiment can be applied to, for example, Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104, or it can be located in the cloud or on another network server.

[0046] The terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, and smart in-vehicle systems. Portable wearable devices can include smartwatches, smart bracelets, and head-mounted devices. The server 104 can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0047] In one embodiment, such as Figure 2 As shown, a method for determining water vapor density is provided, which can be applied to... Figure 1 Taking the terminal in the example, the explanation includes the following steps:

[0048] 201. Obtain water vapor field information from the Global Navigation Satellite System, as well as observation network data and remote sensing data. The water vapor field information includes zenith tropospheric wet delay data.

[0049] 202. Based on the observation network data, water vapor field information and remote sensing data, determine the tomographic equations, which include the design matrices of the tomographic observation equations and the vertical constraint equations respectively.

[0050] 203. Solve the chromatography equation to obtain the chromatography solution, and determine the water vapor density based on the chromatography solution.

[0051] The Global Navigation Satellite System (GNSS) is used to observe three-dimensional water vapor data in nature, obtaining corresponding water vapor field information, observation network data, and remote sensing data. Water vapor field information refers to water vapor information over a specific area, such as the water vapor field information over a city during severe convective weather. Observation network data refers to data from the network of observation platforms built based on the GNSS. Remote sensing data (RS data) refers to satellite data, such as satellite imagery, taken by the GNSS of a corresponding area.

[0052] Zenith wet delay (ZWD) data can be used to retrieve atmospheric zenith precipitable water. Within any given region, different horizontal altitudes correspond to one ZWD data point. In this embodiment of the invention, one horizontal altitude corresponds to one ZWD data point. Correspondingly, the number of horizontal altitudes available determines the number of water vapor densities corresponding to those altitudes. For example, with ZWD data at 10 horizontal altitudes, the water vapor density at all 10 horizontal altitudes can be calculated.

[0053] Specifically, the observation network data, water vapor field information, and remote sensing data are cleaned and processed to obtain the processed observation network data, water vapor field information, and remote sensing data. Based on the processed observation network data, water vapor field information, and remote sensing data, tomographic grid data is obtained, and a tomographic equation for the water vapor density of the corresponding region is constructed. The tomographic equation is then solved to obtain the tomographic solution, which is a matrix of water vapor density for the corresponding region. This matrix is ​​an n*1 matrix, where each row contains elements representing the water vapor density at a given horizontal height. Here, n is an integer not less than 2.

[0054] The method provided in this invention uses water vapor field information, observation network data, and remote sensing data of a certain region to build a tomographic equation, which can calculate the water vapor density of the corresponding region at different altitudes, thereby realizing the detection of water vapor in the corresponding region.

[0055] In conjunction with the above embodiments, in one embodiment, the process of determining the design matrix of the vertical constraint equation includes:

[0056] Based on remote sensing data, vertical constraint equations are constructed, and the design matrix of the vertical constraint equations is determined.

[0057] Specifically, vertical constraint equations are constructed using remote sensing data within a certain time period, and the design matrix of these vertical constraint equations is determined. For example, vertical constraints can be constructed using remote sensing data from the first three days of tomography.

[0058] The method provided in this invention constructs vertical constraint equations using remote sensing data before tomography, which can improve the accuracy of vertical constraint equations.

[0059] In conjunction with the above embodiments, in one embodiment, the process of determining the design matrix of the tomographic observation equation includes:

[0060] Based on the observation network data, a tomographic observation equation is constructed, and the design matrix of the tomographic observation equation is determined.

[0061] The design matrix of the tomographic observation equation consists of the intercepts in each cell of the tomographic grid data. The corresponding tomographic grid data can be constructed using the observation grid data.

[0062] The method provided in this embodiment of the invention can determine the tomographic observation equation and the corresponding design matrix of the tomographic observation equation by using observation network data.

[0063] In conjunction with the above embodiments, in one embodiment, before determining the torsion equation, the following steps are also included:

[0064] Interpolation processing was performed on the zenith tropospheric wet delay data to obtain virtual zenith tropospheric wet delay data.

[0065] The wet delay data of the zenith troposphere is interpolated as shown in Equation (1).

[0066]

[0067] In formula (1), ZWD i For the i-th zenith tropospheric wet delay data, ZWD i For each horizontal height, VZWD represents the virtual zenith tropospheric wet delay data. 'n' indicates that there are n horizontal heights of zenith tropospheric wet delay data. i d represents the coefficient corresponding to the i-th zenith tropospheric wet delay data. i It is a constant.

[0068] It is worth mentioning that the wet delay data of the zenith troposphere in this embodiment of the invention needs to be corrected for elevation. The wet delay data of the zenith troposphere needs to be corrected for elevation as shown in formula (2).

[0069]

[0070] In formula (2), ZWD(h0) is the zenith tropospheric wet delay data corresponding to the horizontal height h0, and ZWD(h) is the zenith tropospheric wet delay data corresponding to the horizontal height h after correcting the horizontal height h0.

[0071] In addition, when solving the tomographic equations, it is also necessary to reduce the weight of the virtual top tropospheric wet delay data.

[0072] The method provided in this invention can obtain virtual top tropospheric wet delay data by interpolating the zenith tropospheric wet delay data. Simultaneously, by performing elevation correction processing on the zenith tropospheric wet delay data, the accuracy of the zenith tropospheric wet delay data can be improved.

[0073] In conjunction with the above embodiments, in one embodiment, the tomographic equation is determined based on observation network data, water vapor field information, and remote sensing data, including:

[0074] By projecting the zenith tropospheric wet delay data and the virtual zenith tropospheric wet delay data onto the observation station direction of the global navigation satellite system, oblique path wet delay data and virtual oblique path wet delay data are obtained, respectively.

[0075] Multiply the oblique path wet delay data and the virtual oblique path wet delay data by the conversion factor to obtain the oblique path water vapor content and the virtual oblique path water vapor content, respectively.

[0076] The tomographic equations were determined based on the oblique path water vapor content, the virtual oblique path water vapor content, observation network data, and remote sensing data.

[0077] The zenith tropospheric wet delay data refers to the zenith tropospheric wet delay data after elevation correction. The virtual tropospheric wet delay data refers to the virtual tropospheric wet delay data after weight reduction. The conversion factor is a constant.

[0078] Specifically, the zenith tropospheric wet delay data and the virtual zenith tropospheric wet delay data are projected onto the direction of the satellite observation station of the Global Navigation Satellite System using the Global Mapping Function (GMF) model, so that each grid in the tomographic grid data has a ray passing through it, thus obtaining the projected zenith tropospheric wet delay data and the virtual zenith tropospheric wet delay data. Then, the projected zenith tropospheric wet delay data and the virtual zenith tropospheric wet delay data are multiplied by the transformation factor to obtain the oblique path water vapor content and the virtual oblique path water vapor content, respectively.

[0079] The method provided in this invention uses the GMF model to project zenith tropospheric wet delay data and virtual zenith tropospheric wet delay data onto the observation direction of the Global Navigation Satellite System. The projected data domain transformation factor is then multiplied to obtain oblique path water vapor content and virtual oblique path water vapor content, thereby improving the accuracy of oblique path water vapor content data and virtual oblique path water vapor content data.

[0080] In conjunction with the above embodiments, in one embodiment, the tomographic equation is determined based on oblique path water vapor content, virtual oblique path water vapor content, observation network data, and remote sensing data, including:

[0081]

[0082] In formula (3), SWV is the water vapor content of the oblique path, SWV' is the water vapor content of the virtual oblique path, A and B are both design matrices of the tomographic observation equation. Specifically, A is the design matrix of the tomographic observation equation, B is the design matrix of the virtual tomographic observation equation, X is the water vapor density to be solved, and V is the design matrix of the vertical constraint equation.

[0083] Solving equation (3), we get:

[0084] X = (A T P A A+B T P B B+V T P V V) -1 *(ATP A SWV+B T P B SWV')(4);

[0085] In formula (4), SWV is the water vapor content along the oblique path, SWV' is the virtual water vapor content along the oblique path, A is the design matrix of the tomographic observation equation, B is the design matrix of the virtual tomographic observation equation, X is the water vapor density to be solved, V is the design matrix of the vertical constraint equation, and P A P BP V These are the weight matrices for the tomographic observation equation, the virtual tomographic observation equation, and the vertical constraint equation, respectively.

[0086] Specifically, the water vapor density X is determined by the Gaussian function, and the Gaussian function equation is shown in formula (5):

[0087]

[0088] In formula (5), X j and X i These are the elements corresponding to the j-th and i-th rows of matrix X, respectively. In other words, X... j For a horizontal height h j The corresponding water vapor density, X i For another horizontal height h i The corresponding water vapor density, b and c are both coefficients in the Gaussian function equation, and b and c are constants.

[0089] By transforming formula (5), we can obtain:

[0090]

[0091] In formula (6), X(h) represents the water vapor density at horizontal height h, and a, b and c are constant coefficients.

[0092] The tomographic equation can be solved using formulas (4), (5) and (6), and the tomographic solution can be obtained. The tomographic solution is an n*1 matrix, in which the element of each row is the water vapor density at the corresponding horizontal height.

[0093] Table 1

[0094]

[0095] In one example, as shown in Table 1, the water vapor density calculated using the method for determining water vapor density provided by this invention within a certain time period is compared with the water vapor density in remote sensing data and data provided by a certain institution. It can be determined that the water vapor density calculated by this invention not only matches well with the water vapor density in the remote sensing data, but also matches the water vapor density in the data provided by a certain institution.

[0096] Relative to the water vapor density in remote sensing data, the water vapor density calculated using the method of this invention has a bias between -0.78 and 0.13 g / m³ in the entire troposphere, with an average bias of -0.36 g / m³; and a standard deviation (SD) between 0.55 and 1.11 g / m³, with an average standard deviation of 0.90 g / m³. In the lower troposphere, the bias is between -0.78 and 0.51 g / m³, with an average bias of -0.43 g / m³; and the standard deviation is between 0.68 and 1.51 g / m³, with an average standard deviation of 1.08 g / m³.

[0097] Compared to data provided by a certain institution, the deviation of the water vapor density calculated using the method of this invention ranges from -0.60 to 0.08 g / m³, with an average deviation of -0.30 g / m³; the standard deviation ranges from 0.51 to 1.20 g / m³, with an average standard deviation of 0.83 g / m³. In the lower troposphere, the deviation ranges from -0.86 to 0.18 g / m³, with an average deviation of -0.29 g / m³; the standard deviation ranges from 0.65 to 1.37 g / m³, with an average standard deviation of 0.97 g / m³. This demonstrates the effectiveness of the method provided by this invention and the feasibility of real-time acquisition of three-dimensional water vapor fields.

[0098] The method provided in this invention provides that, by solving the tomographic equation, the corresponding water vapor density can be obtained, thereby enabling the monitoring of water vapor in the atmosphere and improving the accuracy of water vapor density calculation.

[0099] In conjunction with the above embodiments, in one embodiment, such as Figure 3 As shown, a method for determining water vapor density includes:

[0100] 301. Obtain water vapor field information, observation network data, and remote sensing data from the Global Navigation Satellite System. The water vapor field information includes zenith tropospheric wet delay data.

[0101] 302. Project the zenith tropospheric wet delay data and the virtual zenith tropospheric wet delay data onto the observation station direction of the Global Navigation Satellite System to obtain the slant path wet delay data and the virtual slant path wet delay data, respectively;

[0102] 303. Multiply the oblique path wet delay data and the virtual oblique path wet delay data by the conversion factor respectively to obtain the oblique path water vapor content and the virtual oblique path water vapor content.

[0103] 304. Determine the tomographic equation based on the water vapor content of the oblique path, the water vapor content of the virtual oblique path, the observation network data, and the remote sensing data.

[0104] 305. Solve the chromatography equation to obtain the chromatography solution, and determine the water vapor density based on the chromatography solution.

[0105] The method provided in this invention constructs a tomographic equation using water vapor field information, observation network data, and remote sensing data, and solves the tomographic equation to obtain the water vapor density. This can improve the accuracy of water vapor density calculation and thus enable the monitoring of water vapor density.

[0106] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0107] Based on the same inventive concept, this application also provides a water vapor density determination apparatus for implementing the water vapor density determination method described above. The solution provided by this apparatus is similar to the solution described in the above method; therefore, the specific limitations in one or more embodiments of the water vapor density determination apparatus provided below can be found in the limitations of the water vapor density determination method described above, and will not be repeated here.

[0108] In one embodiment, such as Figure 4 As shown, a device for determining water vapor density is provided, comprising: an acquisition module 401, a first determination module 402, and a first determination module 403, wherein:

[0109] The acquisition module 401 is used to acquire water vapor field information, observation network data and remote sensing data of the global navigation satellite system. The water vapor field information includes zenith tropospheric wet delay data.

[0110] The first determining module 402 is used to determine the tomographic equations based on the observation network data, water vapor field information and remote sensing data. The tomographic equations include the design matrices of the observation equations and the vertical constraint equations, respectively.

[0111] The second determining module 403 is used to solve the tomographic equation, obtain the tomographic solution, and determine the water vapor density based on the tomographic solution.

[0112] In one embodiment, the first determining module 402 includes:

[0113] The first determination submodule is used to construct the vertical constraint equations based on remote sensing data and determine the design matrix of the vertical constraint equations.

[0114] In one embodiment, the first determining module 402 further includes:

[0115] The second determination submodule is used to construct the tomographic observation equations based on the observation network data and determine the design matrix of the tomographic observation equations.

[0116] In one embodiment, the first determining module 402 further includes:

[0117] The processing submodule is used to interpolate the zenith tropospheric wet delay data to obtain virtual zenith tropospheric wet delay data.

[0118] In one embodiment, the first determining module 402 further includes:

[0119] The projection submodule is used to project the zenith tropospheric wet delay data and the virtual zenith tropospheric wet delay data onto the observation station direction of the global navigation satellite system, so as to obtain the slant path wet delay data and the virtual slant path wet delay data, respectively.

[0120] The multiplication submodule is used to multiply the slant path wet delay data and the virtual slant path wet delay data by the conversion factor respectively, to obtain the slant path water vapor content and the virtual slant path water vapor content respectively;

[0121] The third determination submodule is used to determine the tomographic equations based on the oblique path water vapor content, virtual oblique path water vapor content, observation network data, and remote sensing data.

[0122] In one embodiment, the first determining module 402 further includes:

[0123]

[0124] In formula (7), SWV is the water vapor content of the oblique path, SWV' is the virtual oblique path water vapor content, A and B are both design matrices of the chromatographic observation equation, X is the water vapor density, and V is the design matrix of the vertical constraint equation.

[0125] Each module in the aforementioned water vapor density determination device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0126] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 5As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When executed by the processor, the computer program implements a method for determining water vapor density. The display unit is used to form a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0127] Those skilled in the art will understand that Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0128] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0129] Acquire water vapor field information, observation network data, and remote sensing data from the Global Navigation Satellite System. The water vapor field information includes zenith tropospheric wet delay data.

[0130] Based on observation network data, water vapor field information, and remote sensing data, the tomographic equations are determined. The tomographic equations include the design matrices of the tomographic observation equations and the vertical constraint equations, respectively.

[0131] The chromatographic equation is solved to obtain the chromatographic solution, and the water vapor density is determined based on the chromatographic solution.

[0132] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0133] Based on remote sensing data, vertical constraint equations are constructed, and the design matrix of the vertical constraint equations is determined.

[0134] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0135] Based on the observation network data, tomographic observation equations are constructed, and the design matrix of the tomographic observation equations is determined.

[0136] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0137] Interpolation processing was performed on the zenith tropospheric wet delay data to obtain virtual zenith tropospheric wet delay data.

[0138] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0139] By projecting the zenith tropospheric wet delay data and the virtual zenith tropospheric wet delay data onto the observation station direction of the global navigation satellite system, oblique path wet delay data and virtual oblique path wet delay data are obtained, respectively.

[0140] Multiply the oblique path wet delay data and the virtual oblique path wet delay data by the conversion factor to obtain the oblique path water vapor content and the virtual oblique path water vapor content, respectively.

[0141] The tomographic equations were determined based on the water vapor content of the oblique path, the water vapor content of the virtual oblique path, observation network data, and remote sensing data.

[0142] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0143]

[0144] In formula (8), SWV is the water vapor content of the oblique path, SWV' is the virtual oblique path water vapor content, A and B are both design matrices of the chromatographic observation equation, X is the water vapor density, and V is the design matrix of the vertical constraint equation.

[0145] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0146] Acquire water vapor field information, observation network data, and remote sensing data from the Global Navigation Satellite System. The water vapor field information includes zenith tropospheric wet delay data.

[0147] Based on observation network data, water vapor field information, and remote sensing data, the tomographic equations are determined. The tomographic equations include the design matrices of the tomographic observation equations and the vertical constraint equations, respectively.

[0148] The chromatography equation is solved to obtain the chromatography solution, and the water vapor density is determined based on the chromatography solution.

[0149] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0150] Based on remote sensing data, vertical constraint equations are constructed, and the design matrix of the vertical constraint equations is determined.

[0151] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0152] Based on the observation network data, a tomographic observation equation is constructed, and the design matrix of the tomographic observation equation is determined.

[0153] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0154] Interpolation processing was performed on the zenith tropospheric wet delay data to obtain virtual zenith tropospheric wet delay data.

[0155] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0156] By projecting the zenith tropospheric wet delay data and the virtual zenith tropospheric wet delay data onto the observation station direction of the global navigation satellite system, oblique path wet delay data and virtual oblique path wet delay data are obtained, respectively.

[0157] Multiply the oblique path wet delay data and the virtual oblique path wet delay data by the conversion factor to obtain the oblique path water vapor content and the virtual oblique path water vapor content, respectively.

[0158] The tomographic equations were determined based on the oblique path water vapor content, the virtual oblique path water vapor content, observation network data, and remote sensing data.

[0159] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0160]

[0161] In formula (9), SWV is the water vapor content of the oblique path, SWV' is the virtual oblique path water vapor content, A and B are both design matrices of the chromatographic observation equation, X is the water vapor density, and V is the design matrix of the vertical constraint equation.

[0162] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:

[0163] Acquire water vapor field information, observation network data, and remote sensing data from the Global Navigation Satellite System. The water vapor field information includes zenith tropospheric wet delay data.

[0164] Based on observation network data, water vapor field information, and remote sensing data, the tomographic equations are determined. The tomographic equations include the design matrices of the tomographic observation equations and the vertical constraint equations, respectively.

[0165] The chromatography equation is solved to obtain the chromatography solution, and the water vapor density is determined based on the chromatography solution.

[0166] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0167] Based on remote sensing data, vertical constraint equations are constructed, and the design matrix of the vertical constraint equations is determined.

[0168] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0169] Based on the observation network data, a tomographic observation equation is constructed, and the design matrix of the tomographic observation equation is determined.

[0170] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0171] Interpolation processing was performed on the zenith tropospheric wet delay data to obtain virtual zenith tropospheric wet delay data.

[0172] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0173] By projecting the zenith tropospheric wet delay data and the virtual zenith tropospheric wet delay data onto the observation station direction of the global navigation satellite system, oblique path wet delay data and virtual oblique path wet delay data are obtained, respectively.

[0174] Multiply the oblique path wet delay data and the virtual oblique path wet delay data by the conversion factor to obtain the oblique path water vapor content and the virtual oblique path water vapor content, respectively.

[0175] The tomographic equations were determined based on the oblique path water vapor content, the virtual oblique path water vapor content, observation network data, and remote sensing data.

[0176] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0177]

[0178] In formula (10), SWV is the water vapor content of the oblique path, SWV' is the virtual oblique path water vapor content, A and B are both design matrices of the chromatographic observation equation, X is the water vapor density, and V is the design matrix of the vertical constraint equation.

[0179] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data shall comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0180] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0181] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0182] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for determining water vapor density, characterized in that, The method includes: Acquire water vapor field information, observation network data, and remote sensing data from the Global Navigation Satellite System, wherein the water vapor field information includes zenith tropospheric wet delay data; Based on the observation network data, the water vapor field information, and the remote sensing data, the tomographic equations are determined, and the tomographic equations include the design matrices of the tomographic observation equations and the vertical constraint equations, respectively. The chromatography equation is solved to obtain the chromatography solution, and the water vapor density is determined based on the chromatography solution. The process of determining the design matrix of the vertical constraint equation includes: Based on the remote sensing data, construct the vertical constraint equation and determine the design matrix of the vertical constraint equation; The process of determining the design matrix of the tomographic observation equation includes: Based on the observation network data, the tomographic observation equation is constructed, and the design matrix of the tomographic observation equation is determined; Before determining the torsion equation, the process also includes: The zenith tropospheric wet delay data is interpolated to obtain virtual zenith tropospheric wet delay data; The step of determining the tomographic equation based on the observation network data, the water vapor field information, and the remote sensing data includes: The zenith tropospheric wet delay data and the virtual zenith tropospheric wet delay data are projected onto the observation station direction of the global navigation satellite system to obtain oblique path wet delay data and virtual oblique path wet delay data, respectively. Multiply the oblique path wet delay data and the virtual oblique path wet delay data by the conversion factor respectively to obtain the oblique path water vapor content and the virtual oblique path water vapor content; The tomographic equation is determined based on the oblique path water vapor content, the virtual oblique path water vapor content, the observation network data, and the remote sensing data. The step of determining the tomographic equation based on the oblique path water vapor content, the virtual oblique path water vapor content, the observation network data, and the remote sensing data includes: ； Wherein, SWV represents the oblique path water vapor content. Let A be the virtual oblique path water vapor content, B be the design matrix of the tomographic observation equation, X be the water vapor density, and V be the design matrix of the vertical constraint equation.

2. A device for determining water vapor density, characterized in that, The apparatus is used to implement the steps of the method of claim 1, and the apparatus includes: The acquisition module is used to acquire water vapor field information, observation network data and remote sensing data from the global navigation satellite system, wherein the water vapor field information includes zenith tropospheric wet delay data; The first determining module is used to determine the tomographic equations based on the observation network data, the water vapor field information, and the remote sensing data. The tomographic equations include the design matrices of the observation equations and the vertical constraint equations, respectively. The second determining module is used to solve the chromatography equation, obtain the chromatography solution, and determine the water vapor density based on the chromatography solution.

3. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method of claim 1.

4. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the method of claim 1.

5. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method of claim 1.

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