Three-dimensional water vapor tomography method and device based on mobile beidou equipment and storage medium

Abstract

The application discloses a three-dimensional water vapor tomography method and device based on a mobile Beidou device and a storage medium. The method comprises the following steps: acquiring regional characteristic data of a target monitoring area; planning an observation path for a mobile carrier carrying a Beidou receiving device based on the regional characteristic data, and controlling the mobile carrier to travel along the observation path; acquiring Beidou observation data collected by the Beidou receiving device during the travel of the mobile carrier; determining zenith troposphere delay parameters of a Beidou satellite signal based on the Beidou observation data, and decomposing the zenith troposphere delay parameters into zenith wet delay parameters; determining atmospheric precipitable water of each observation position in the target monitoring area based on the zenith wet delay parameters, determining a water vapor tomography observation function, and analyzing a three-dimensional water vapor field in the target monitoring area based on the atmospheric precipitable water and the water vapor tomography observation function.

Description

Technical Field

[0001] This invention relates to the field of three-dimensional water vapor chromatography technology, and in particular to a three-dimensional water vapor chromatography method, apparatus and storage medium based on mobile Beidou equipment. Background Technology

[0002] Water vapor is one of the key drivers of weather change. Three-dimensional water vapor tomography can provide spatiotemporal information on water vapor distribution, clearly demonstrating the characteristics of water vapor variation in both vertical and horizontal directions. For example, through continuous three-dimensional water vapor tomography data, the convergence and diffusion of water vapor at different altitudes, as well as the transport paths of water vapor within a region, can be observed. This detailed information helps to more accurately understand the formation and development mechanisms of weather systems, thus providing data support for severe weather forecasting and early warning, and the optimization of numerical weather prediction systems.

[0003] Currently, atmospheric water vapor distribution is typically retrieved by receiving satellite signals from fixed ground-based satellite systems. However, the limited coverage of fixed stations results in low accuracy of water vapor stratification in mountainous and remote areas without station coverage, making it impossible to accurately capture small-scale spatiotemporal changes in water vapor. Furthermore, the deployment of fixed stations is costly and time-consuming, and it is difficult to flexibly adjust the monitoring area. Summary of the Invention

[0004] This invention provides a three-dimensional water vapor chromatography method, apparatus, and storage medium based on mobile BeiDou equipment, which mainly improves the accuracy and flexibility of water vapor chromatography and saves water vapor chromatography costs.

[0005] According to a first aspect of the present invention, a three-dimensional water vapor chromatography method based on a mobile BeiDou device is provided, comprising:

[0006] In response to the three-dimensional water vapor chromatography signal of the target monitoring area, regional feature data of the target monitoring area are acquired; Based on the regional feature data, an observation path is planned for the mobile carrier equipped with the BeiDou receiving device, and the mobile carrier is controlled to travel along the observation path. During the travel of the mobile carrier, the BeiDou observation data collected by the BeiDou receiving device is acquired. Based on the BeiDou observation data, the zenith tropospheric delay parameter of the BeiDou satellite signal is determined, and the zenith tropospheric delay parameter is decomposed into the zenith wet delay parameter. Based on the zenith wet delay parameter, the atmospheric precipitable water content at each observation location in the target monitoring area is determined, the water vapor tomography observation function is determined, and the three-dimensional water vapor field in the target monitoring area is analyzed based on the atmospheric precipitable water content and the water vapor tomography observation function.

[0007] Optionally, before determining the zenith tropospheric delay parameter of the BeiDou satellite signal based on the BeiDou observation data, the method further includes: Each type of BeiDou observation data is taken as a target BeiDou observation data. Path BeiDou observation data with different paths within a preset time period are determined from the target BeiDou observation data. Based on the mean and standard deviation of the path BeiDou observation data, abnormal BeiDou observation data is detected and removed from the target BeiDou observation data. The carrier motion data and BeiDou satellite signal data are obtained, wherein the carrier motion data includes the travel speed, acceleration, and attitude angle of the mobile carrier, and the satellite signal data includes the satellite elevation angle and satellite azimuth angle of the BeiDou satellite; Obtain the collaborative correction function, and based on the carrier motion data and the satellite signal data, use the collaborative correction function to determine the multipath error correction parameters of the BeiDou observation data; Based on the multipath error correction parameters, the target BeiDou observation data after removing abnormal BeiDou observation data is corrected for multipath error, resulting in the path-corrected target BeiDou observation data.

[0008] Optionally, the BeiDou observation data includes BeiDou satellite orbit parameters and pseudorange; Before determining the zenith tropospheric delay parameter of the BeiDou satellite signal based on the aforementioned BeiDou observation data, the method further includes: Obtain a precise ephemeris file and a clock error file, wherein the precise ephemeris file contains reference satellite orbit parameters at multiple times, and the clock error file contains reference clock error parameters at multiple times; Based on reference satellite orbit parameters at multiple times, the parameter correction amount of the BeiDou satellite orbit parameters is determined, and based on reference clock error parameters at multiple times, the clock error correction amount of the pseudorange is determined. The BeiDou satellite orbit parameters are corrected based on the parameter correction amount, and the pseudorange is corrected based on the clock error correction amount. The method further includes: Determine the data acquisition reference time and the actual acquisition time of the BeiDou observation data; based on the acquisition reference time and the actual acquisition time, determine the missing acquisition time; and based on the difference between the missing acquisition time and the corresponding acquisition reference time, complete the BeiDou observation data under the missing acquisition time. The data acquisition reference location and the actual acquisition location of the BeiDou observation data are determined. Based on the acquisition reference location and the actual acquisition location, the missing acquisition location is determined. The corresponding neighboring actual acquisition location is determined. The positional relationship between the missing acquisition location and the neighboring actual acquisition location is determined. Based on the BeiDou observation data of the neighboring actual acquisition location at the same time and the positional relationship, the BeiDou observation data of the missing acquisition location is completed.

[0009] Optionally, the BeiDou observation data includes satellite elevation angle. carrier wavelength of band i Geometric distance between the BeiDou satellite and the mobile carrier ; The determination of the zenith tropospheric delay parameter of the BeiDou satellite signal based on the BeiDou observation data includes: Obtain the carrier phase function and pseudo-distance function ; To obtain reference data for solving the zenith tropospheric delay parameters, the reference data includes the speed of light c and the receiving clock bias of the mobile carrier. carrier wavelength Whole week blur Carrier phase observation noise pseudorange observation noise ; Based on the BeiDou observation data, the solution reference data, and the carrier phase function and the pseudo-distance function Determine the zenith tropospheric delay parameters of BeiDou satellite signals. ,in, , , This is a process mapping function.

[0010] Optionally, the analysis of the three-dimensional water vapor field in the target monitoring area based on the atmospheric precipitable water and the water vapor tomography observation function includes: A preset horizontal resolution and vertical height range for the target monitoring area are determined. Based on the preset horizontal resolution and the vertical height range, the target monitoring area is divided into a three-dimensional grid, and the propagation path length of the BeiDou satellite signal within the three-dimensional grid is determined. A regularization factor is determined, and a regularization term is introduced into the water vapor tomography observation function based on the regularization factor. The water vapor tomography observation function after introducing the regularization term is solved based on the atmospheric precipitable water and the propagation path length. The water vapor density value of each grid cell in the three-dimensional grid is determined based on the solution result, and the water vapor density value and spatiotemporal distribution characteristics of each grid cell are used as the three-dimensional water vapor field.

[0011] Optionally, the analysis of the three-dimensional water vapor field in the target monitoring area based on the atmospheric precipitable water and the water vapor tomography observation function includes: Based on the atmospheric precipitable water and the water vapor tomography observation function, the initial three-dimensional water vapor field in the three-dimensional tomography grid is determined. And obtain reference observation data of the target monitoring area, wherein the reference observation data includes atmospheric precipitable water and radiosonde data received by fixed satellite signal receiving stations in the target monitoring area, wherein the radiosonde data includes water vapor density at each altitude layer of the target monitoring area calculated based on temperature and humidity; Based on the reference observation data and the initial three-dimensional water vapor field The relationship between the observations is used to construct the observation matrix H, and to determine the observation vector corresponding to the reference observation data. And obtain the covariance matrix corresponding to the initial three-dimensional water vapor field. Based on the observation matrix H and the covariance matrix Determine the correction parameters for the initial three-dimensional water vapor field. ,in, R is the observation noise matrix of the initial three-dimensional water vapor field; Using the correction parameters For the initial three-dimensional water vapor field The initial three-dimensional water vapor field is corrected and used as the three-dimensional water vapor field. ,in, .

[0012] Optionally, based on the regional feature data, an observation path is planned for a mobile carrier equipped with a BeiDou receiver, including: Obtain information on water vapor chromatography requirements; Based on the regional characteristic data and the water vapor chromatography demand information, a path planning strategy is determined. Based on the path planning strategy, a grid cross-observation path is planned for a mobile carrier equipped with a BeiDou receiver.

[0013] According to a second aspect of the present invention, a three-dimensional water vapor chromatography apparatus based on a mobile BeiDou device is provided, comprising: The acquisition unit is used to acquire regional feature data of the target monitoring area in response to the three-dimensional water vapor chromatography signal of the target monitoring area; The data acquisition unit is used to plan an observation path for a mobile carrier equipped with a BeiDou receiving device based on the regional feature data, and control the mobile carrier to travel along the observation path. During the travel of the mobile carrier, the unit acquires the BeiDou observation data collected by the BeiDou receiving device. The decomposition unit is used to determine the zenith tropospheric delay parameter of the BeiDou satellite signal based on the BeiDou observation data, and decompose the zenith tropospheric delay parameter into an out-zenith wet delay parameter. The water vapor tomography unit is used to determine the atmospheric precipitable water at each observation location in the target monitoring area based on the zenith wet delay parameter, determine the water vapor tomography observation function, and analyze the three-dimensional water vapor field in the target monitoring area based on the atmospheric precipitable water and the water vapor tomography observation function.

[0014] According to a third aspect of the present invention, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the above-described three-dimensional water vapor chromatography method based on a mobile BeiDou device.

[0015] According to a fourth aspect of the present invention, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-described three-dimensional water vapor chromatography method based on a mobile Beidou device.

[0016] According to the present invention, a method, apparatus, and storage medium for three-dimensional water vapor tomography based on mobile BeiDou equipment is provided. Compared with the current method of receiving satellite signals and retrieving atmospheric water vapor distribution through fixed-ground satellite systems, the present invention plans an observation path for a mobile carrier equipped with BeiDou receiving equipment and controls the mobile carrier to travel along the observation path. Water vapor is tomographically analyzed using BeiDou observation data collected during the mobile carrier's travel. This allows for flexible planning of the observation path, overcomes the spatial limitations of fixed stations, and provides a wide monitoring range, enabling comprehensive water vapor monitoring. This improves the accuracy and flexibility of water vapor tomography. Furthermore, a single mobile carrier can monitor water vapor in multiple regions, saving on water vapor tomography costs. By decomposing the zenith wet delay parameter from the zenith tropospheric delay parameter, the influence of water vapor on satellite signals can be extracted separately, thus obtaining atmospheric water vapor information more accurately and achieving precise water vapor tomography. Attached Figure Description

[0017] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings: Figure 1 This invention provides a flowchart of a three-dimensional water vapor chromatography method based on a mobile BeiDou device. Figure 2 This invention provides a flowchart of another three-dimensional water vapor chromatography method based on a mobile BeiDou device. Figure 3 This diagram illustrates the structure of a three-dimensional water vapor chromatography device based on a mobile BeiDou system, according to an embodiment of the present invention. Figure 4 This invention provides a schematic diagram of another three-dimensional water vapor chromatography device based on a mobile BeiDou system, according to an embodiment of the present invention. Figure 5 A schematic diagram of the physical structure of a computer device provided in an embodiment of the present invention is shown. Detailed Implementation

[0018] The present invention will be described in detail below with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in the present application can be combined with each other.

[0019] Currently, atmospheric water vapor distribution is retrieved by receiving satellite signals through fixed-ground satellite systems. However, the coverage of fixed stations is limited, resulting in low accuracy of water vapor stratification in mountainous and remote areas without station coverage. Furthermore, the deployment of fixed stations is costly and time-consuming, making it difficult to flexibly adjust the monitoring area.

[0020] To address the aforementioned problems, embodiments of the present invention provide a three-dimensional water vapor chromatography method based on mobile BeiDou equipment, such as... Figure 1 As shown, the method includes: 101. Responding to the three-dimensional water vapor chromatography signal of the target monitoring area, acquire regional characteristic data of the target monitoring area.

[0021] The target monitoring area can be any region, such as plains, mountains, hills, valleys, and towns. Regional characteristic data includes, but is not limited to, altitude, land cover type, geographic coordinates, and meteorological data. This regional characteristic data can be obtained from a database or measured in real time using sensors and other measuring devices.

[0022] 102. Based on regional feature data, plan the observation path for the mobile carrier equipped with BeiDou receiving equipment, and control the mobile carrier to travel along the observation path. During the travel of the mobile carrier, acquire the BeiDou observation data collected by the BeiDou receiving equipment.

[0023] Among them, the mobile carrier can be a vehicle, drone, ship, portable carrier, etc., and there can be one or multiple mobile carriers; the Beidou receiving equipment is a terminal device used to receive signals transmitted by the Beidou satellite navigation system to obtain information such as location and time, as well as related navigation, positioning, and timing services.

[0024] For embodiments of the present invention, a grid-like cross-observation path is planned based on the regional characteristic data of the target monitoring area. For example, in plains / gentle areas (slope < 5°): an equally spaced positive grid is used, with a horizontal and vertical spacing of 1-3 km (preferably 2 km). The path is arranged straight along latitude and longitude lines or road directions to ensure uniform distribution of observation points and no blind spots; in mountainous / hilly areas (slope ≥ 5°): ① the spacing is increased to 1-2 km to avoid data loss due to terrain obstruction; ② the path is planned along contour lines or valleys and ridges to avoid steep slopes (slope > 30°) and cliff areas, reducing the difficulty of moving vehicles; ③ in valleys, passes, and other areas where water vapor easily accumulates, cross paths are added (1-2 additional horizontal auxiliary paths) to increase the observation density in the area; in river valleys / waterfront areas: ① the vertical path is parallel to the river channel, and the horizontal path is perpendicular to the river channel with a spacing of 1 km, focusing on covering a 1 km range on both sides of the riverbank; ② If there are key facilities such as bridges and dams, add a ring-shaped auxiliary path around the facilities to ensure the accuracy of water vapor monitoring around the facilities; in urban areas: combine the road network planning with grid paths, with a spacing of 1.5-3km, avoid the obstruction range of densely built-up areas (building height > 50m), and prioritize open road sections (such as urban main roads and the area around parks) to ensure the quality of satellite signal reception.

[0025] Furthermore, after determining the observation path, the travel speed of the mobile vehicle is set, such as 30 km / h, and the data sampling frequency of the BeiDou receiving equipment is set, such as 10 Hz. This ensures uniform observation time intervals between adjacent path nodes; standard time slices are divided, such as every 5-15 minutes, specifying the observation path segment and data acquisition volume to be completed within each time slice. The mobile vehicle is then controlled to travel along the observation path. During this process, the BeiDou receiving equipment on board collects BeiDou observation data transmitted from BeiDou satellites to the ground based on the sampling frequency. This BeiDou observation data includes, but is not limited to, carrier phase, pseudorange, satellite ephemeris, BeiDou precise timestamp, satellite elevation angle, carrier wavelength of band i, and the geometric distance between the BeiDou satellite and the mobile vehicle. Simultaneously, the real-time position and speed data of the mobile vehicle also need to be determined. This invention determines the observation path through regional feature data, helping to identify which areas require focused observation and which areas can be simplified for observation, thereby optimizing the observation path and improving observation efficiency. By using a mobile BeiDou receiving device to collect BeiDou observation data and achieving dynamic scanning through the moving trajectory, it can cover areas difficult for fixed stations to reach, improving spatiotemporal resolution. Furthermore, by adjusting the moving path to avoid obstructions or utilizing the multipath effect to enhance signal reception, it can improve the accuracy of water vapor chromatography. Simultaneously, a single mobile carrier can monitor water vapor in multiple regions, saving on water vapor chromatography costs.

[0026] 103. Based on BeiDou observation data, determine the zenith tropospheric delay parameter of BeiDou satellite signal, and decompose the zenith tropospheric delay parameter into the zenith wet delay parameter.

[0027] In this embodiment of the invention, to improve the data quality of BeiDou observation data, it is first necessary to preprocess the BeiDou observation data. Based on this, the method includes: taking any type of BeiDou observation data as a target BeiDou observation data; determining path BeiDou observation data for different paths within a preset time period from the target BeiDou observation data; and detecting and removing abnormal BeiDou observation data from the target BeiDou observation data based on the data mean and standard deviation of the path BeiDou observation data; acquiring carrier motion data of the mobile carrier and satellite signal data of the BeiDou satellites, wherein the carrier motion data includes the travel speed, acceleration, and attitude angle of the mobile carrier, and the satellite signal data includes the satellite elevation angle and azimuth angle of the BeiDou satellites; acquiring a collaborative correction function; determining multipath error correction parameters for the BeiDou observation data based on the carrier motion data and the satellite signal data using the collaborative correction function; and performing multipath error correction on the target BeiDou observation data after removing abnormal BeiDou observation data based on the multipath error correction parameters to obtain the path-corrected target BeiDou observation data.

[0028] The preset time period is set according to actual needs; the carrier motion data includes, but is not limited to, the carrier's formal velocity, acceleration, and attitude angles, such as pitch angle and roll angle; the satellite signal data includes satellite elevation angle and azimuth angle.

[0029] Specifically, taking the preprocessing of any type of target BeiDou observation data as an example, the first step is to calculate the average value of the target BeiDou observation data within a preset time period. and data standard deviation The threshold range is determined based on the data mean and data standards, such as... , will not Target BeiDou observation data within the specified range are identified as anomalous data, and these anomalous data are removed from the target BeiDou observation data. Furthermore, the collaborative correction function Δρ is as follows: Δρ = f (h) w1+ g (α) w2+ k (v,a,θ) w3 Where f(h) is the error function of the satellite elevation angle h, for example, when h < 15°, f(h) = 0.05 / h²; when 15° ≤ h < 30°, f(h) = 0.002 / h; when h ≥ 30°, f(h) = 0.000067. g(α) is the error function of the satellite azimuth angle α, which is assigned a weight coefficient by physically defining the range of the obstruction area α. k(v,a,θ) is the error function of the vehicle's speed v, acceleration a, and attitude angle θ, such as k = 0.001v + 0.02a + 0.01|θ|. w1, w2, and w3 are weight coefficients, which can be set according to actual needs or determined by least squares fitting, such as w1 = 0.4, w2 = 0.3, and w3 = 0.3. Subsequently, the vehicle's speed v, acceleration a, and attitude angle θ, along with the BeiDou satellite's elevation angle h and azimuth angle α, are substituted into the aforementioned collaborative correction function Δρ to obtain multipath error correction parameters. Then, the target BeiDou observation data (after removing abnormal BeiDou observation data) is subtracted from the corresponding multipath error correction parameters, and the subtraction result is taken as the path-corrected target BeiDou observation data. This embodiment of the invention improves the quality of BeiDou observation data by identifying and removing abnormal data and correcting path errors, thereby enhancing the accuracy of subsequent water vapor tomography.

[0030] Furthermore, after preprocessing the BeiDou observation data, techniques such as non-combined precise point positioning can be used to analyze the data, thereby calculating the zenith tropospheric delay parameter. This parameter is then decomposed into the zenith static delay parameter and the zenith wet delay parameter. The zenith tropospheric delay parameter refers to parameters such as the path extension time of a satellite signal as it passes through the Earth's troposphere due to atmospheric refraction. This embodiment of the invention, by decomposing the zenith wet delay parameter from the zenith tropospheric delay parameter, can separately extract the influence of water vapor on satellite signals, thereby obtaining more accurate information about water vapor in the atmosphere and achieving precise water vapor chromatography.

[0031] 104. Based on the zenith wet delay parameter, determine the atmospheric precipitable water at each observation location in the target monitoring area, determine the water vapor tomography observation function, and analyze the three-dimensional water vapor field in the target monitoring area based on the atmospheric precipitable water and the water vapor tomography observation function.

[0032] For embodiments of the present invention, after determining the zenith wet delay parameter ZWD, the atmospheric precipitable water volume PWV is determined according to the following formula: PWV=k×ZWD Where k is a reference coefficient for atmospheric precipitable water, which is set according to actual needs, such as k=0.15576.

[0033] Furthermore, based on atmospheric precipitable water and water vapor tomography observation functions, the three-dimensional water vapor field in the target monitoring area is analyzed. This mainly includes analyzing the water vapor density, grid horizontal resolution, grid spatiotemporal coordinates, and spatiotemporal distribution characteristics of water vapor in each grid cell of the three-dimensional grid within the target monitoring area, such as high water vapor density accumulation areas (precursors to heavy rain), water vapor vertical gradient (reflecting convection intensity), and water vapor migration paths in different time slices.

[0034] The present invention provides a three-dimensional water vapor tomography method based on a mobile BeiDou device. Compared with the current method of receiving satellite signals and retrieving atmospheric water vapor distribution through a fixed ground satellite system, the present invention plans an observation path for a mobile carrier equipped with a BeiDou receiving device and controls the mobile carrier to travel along the observation path. Water vapor is tomographically analyzed using BeiDou observation data collected during the mobile carrier's travel. This allows for flexible observation path planning, overcomes the spatial limitations of fixed stations, and provides a wide monitoring range, enabling full-area water vapor monitoring. This improves the accuracy and flexibility of water vapor tomography. Furthermore, a single mobile carrier can monitor water vapor in multiple areas, saving on water vapor tomography costs. By decomposing the zenith wet delay parameter from the zenith tropospheric delay parameter, the influence of water vapor on satellite signals can be extracted separately, thus obtaining atmospheric water vapor information more accurately and achieving precise water vapor tomography.

[0035] Furthermore, to better illustrate the above-described process of water vapor chromatography, and as a refinement and extension of the above embodiments, this invention provides another three-dimensional water vapor chromatography method based on a mobile BeiDou device, such as... Figure 2 As shown, the method includes: 201. Responding to the three-dimensional water vapor chromatographic signal of the target monitoring area, acquire regional characteristic data of the target monitoring area.

[0036] Specifically, when a three-dimensional water vapor chromatography signal is received, regional characteristic data of the target monitoring area are obtained through sensors and other devices.

[0037] 202. Based on regional feature data, plan an observation path for a mobile carrier equipped with a BeiDou receiver, and control the mobile carrier to travel along the observation path. During the travel of the mobile carrier, acquire BeiDou observation data collected by the BeiDou receiver.

[0038] In this embodiment of the invention, in order to meet the water vapor monitoring requirements and improve the monitoring range, it is first necessary to plan the observation path for the mobile carrier. Based on this, step 202 specifically includes: obtaining water vapor tomography requirement information; determining the path planning strategy based on the regional feature data and the water vapor tomography requirement information; and planning a grid cross-observation path for the mobile carrier equipped with Beidou receiving equipment based on the path planning strategy.

[0039] The information required for water vapor chromatography includes the region to be chromatographically focused and the chromatography resolution.

[0040] In an embodiment of the present invention, the method for determining a path planning strategy based on regional feature data and water vapor chromatography demand information includes: determining a regional feature vector corresponding to the regional feature data and a demand feature vector corresponding to the water vapor chromatography demand information; performing feature-level cross processing on the regional feature vector and the demand feature vector to obtain a feature cross vector; performing element-level cross processing on the regional feature vector and the demand feature vector to obtain an element cross vector; performing low-order cross processing on the regional feature vector and the demand feature vector to obtain a low-order cross vector; performing transformation processing on the feature cross vector, the element cross vector, and the low-order cross vector to obtain a path cross feature vector; and inputting the path cross feature vector into a preset path strategy prediction model for strategy prediction to obtain the path planning strategy corresponding to the transfer carrier.

[0041] Specifically, the feature-level cross processing involves: multiplying the elements at the same positions in each vector; concatenating the results horizontally according to element position to obtain an initial feature cross vector; and multiplying this initial cross feature vector by a first weight coefficient determined based on actual needs to obtain a feature cross vector. The element-level cross process involves: multiplying the elements at the same positions in each vector; assigning a corresponding second weight coefficient to each multiplication result; and then concatenating the results horizontally according to element position to obtain an element cross vector. The low-order cross process involves: concatenating the vectors horizontally; assigning a third weight coefficient to the concatenated result based on actual needs to obtain a low-order cross vector. Finally, the feature cross vector, element cross vector, and low-order cross vector are concatenated horizontally to obtain a path cross feature vector. This invention, through cross-processing of demand feature vectors and regional feature vectors, can automatically or explicitly combine different features to generate new feature combinations. These combined features may contain complex nonlinear relationships between the original features, enabling the model to capture more refined and richer information in the data. In other words, it can make full use of the relationships between various data, extract more latent features, and take into account both high-order and low-order processing, making the data utilization more efficient and the subsequent prediction results more accurate, thus meeting the needs of practical application scenarios.

[0042] In this embodiment of the invention, to improve the prediction accuracy of the preset path strategy prediction model, it is first necessary to train and construct the preset path strategy prediction model. Based on this, the method includes: constructing a preset initial path strategy prediction model; obtaining a sample dataset, wherein the sample dataset includes regional feature data and water vapor chromatography demand information of sample water vapor monitoring areas labeled with path strategies; dividing the sample dataset into a training set and a test set; training the preset initial path strategy prediction model using the training set; and testing the trained preset initial path strategy prediction model using the test set; finally, the trained preset initial path strategy prediction model that meets the testing conditions is taken as the preset path strategy prediction model. Specifically, in the model training process, the preset initial path strategy prediction model is first constructed, and then the sample dataset is obtained. It is ensured that the dataset contains all necessary files. The data is converted to a format that the preset initial path strategy prediction model can understand, and finally, the model is trained and tested. Specifically, the dataset can be divided first: the sample dataset can be divided into a training set and a test set using random or specific strategies (such as stratified sampling). Then, the model is trained using the training set, and the trained model is tested using the test set to evaluate its performance on unseen data. Calculate and record metrics such as precision and recall on the test set. If the model performance does not meet the requirements, return to the training phase for further iterations or adjustments. This process yields a preset path strategy prediction model that meets the requirements. Finally, directly input the path intersection feature vectors into the preset path strategy prediction model to predict path planning strategies.

[0043] Furthermore, the mobile carrier moves along the observation path. During the movement, the BeiDou receiving equipment on board receives BeiDou satellite signals, i.e., BeiDou observation data, according to the data acquisition frequency.

[0044] 203. Based on BeiDou observation data, determine the zenith tropospheric delay parameter of BeiDou satellite signal, and decompose the zenith tropospheric delay parameter into the zenith wet delay parameter.

[0045] The BeiDou observation data also includes BeiDou satellite orbital parameters (orbital position coordinates x, y, z, etc.) and pseudorange. In this embodiment of the invention, to improve the quality of the observation data, clock correction needs to be applied to the BeiDou observation data after acquisition. Therefore, the method includes: acquiring a precise ephemeris file and a clock correction file, wherein the precise ephemeris file contains reference satellite orbital parameters at multiple times, and the clock correction file contains reference clock correction parameters at multiple times; determining the parameter correction amount for the BeiDou satellite orbital parameters based on the reference satellite orbital parameters at multiple times, determining the clock correction amount for the pseudorange based on the reference clock correction parameters at multiple times, correcting the BeiDou satellite orbital parameters based on the parameter correction amount, and correcting the pseudorange based on the clock correction amount.

[0046] Specifically, based on reference satellite orbit parameters at multiple times, the parameter correction amount of the BeiDou satellite orbit parameters at observation time t is determined using interpolation. If the orbital parameters of the BeiDou satellite are Then the corrected BeiDou satellite orbit parameters corresponding to the observation time t are: Based on reference clock error parameters at multiple times, the clock error correction at observation time t is determined using interpolation. Then, the pseudorange is calculated according to the following formula. Make corrections:

[0047] in, denoted as the corrected pseudorange, and c is the speed of light at observation time t.

[0048] In another embodiment of the present invention, in order to improve the data quality of the observation data, it is also necessary to perform data completion on the observation data. Based on this, the method includes: determining the data acquisition reference time and the actual acquisition time of the BeiDou observation data; determining the missing acquisition time based on the acquisition reference time and the actual acquisition time; completing the BeiDou observation data at the missing acquisition time based on the difference between the missing acquisition time and the corresponding acquisition reference time; determining the data acquisition reference position and the actual acquisition position of the BeiDou observation data; determining the missing acquisition position based on the acquisition reference position and the actual acquisition position; determining the neighboring actual acquisition positions corresponding to the missing acquisition position; determining the positional relationship between the missing acquisition position and the neighboring actual acquisition positions; and completing the BeiDou observation data at the missing acquisition position based on the BeiDou observation data at the neighboring actual acquisition positions at the same time and the positional relationship.

[0049] Specifically, the data acquisition reference time is determined by pre-divided time slices. For example, if the pre-set data acquisition time slice is from 00:00:00 to 00:15:00 on a certain day, and the time interval of the data acquisition reference time is 1 minute, then the data acquisition reference times are 00:00:00, 00:01:00, 00:02:00, 00:03:00, ..., 00:14:00, 00:15:00. However, during the actual acquisition process, due to factors such as equipment failure, communication interruption, or environmental interference, data at some time points may be missing. For example, if the actual acquisition time is 00:00:00, 00:01:00, 00:03:00, ..., then the missing BeiDou observation data is determined to be acquired at 00:02:00. The baseline acquisition times before and after the missing acquisition time were then determined to be 00:01:00 and 00:03:00, respectively. The differences between the missing acquisition time of 00:02:00 and the baseline acquisition times of 00:01:00 and 00:03:00 were calculated accordingly. and Then, the BeiDou observation data corresponding to the missing collection time is determined according to the following formula. :

[0050] in, To collect BeiDou observation data corresponding to the reference time 00:01:00.

[0051] Furthermore, the reference location is a pre-set location where BeiDou observation data needs to be collected, based on actual requirements. For a given time t, by comparing the actual collection location with the reference location, the missing collection location with missing observation data can be determined. Then, the neighboring actual collection locations of the missing collection location are determined, and the BeiDou satellite observation data at that neighboring actual collection location i at time t is determined. Then, the missing BeiDou observation data for the acquisition locations is supplemented using the following formula:

[0052] in, The missing data points represent the completed BeiDou observation data, where n is the total number of actual data points in the neighborhood. P represents the spatial distance between the missing acquisition location and the actual acquisition location i in the neighboring area, and P is the distance weighting index. This embodiment of the invention improves data quality by correcting and completing BeiDou observation data, thereby increasing the accuracy of subsequent water vapor tomography based on BeiDou observation data.

[0053] Furthermore, after correcting and supplementing the BeiDou observation data, it is also necessary to predict the zenith tropospheric delay parameter based on the corrected and supplemented BeiDou observation data. Therefore, the method includes: the BeiDou observation data includes satellite elevation angles. carrier wavelength of band i Geometric distance between the BeiDou satellite and the mobile carrier Obtain the carrier phase function and pseudo-distance function ; Obtain reference data for solving the zenith tropospheric delay parameters, wherein the reference data includes the speed of light c and the receiving clock bias of the mobile carrier. carrier wavelength Whole week blur Carrier phase observation noise pseudorange observation noise Based on the BeiDou observation data, the solution reference data, and the carrier phase function and the pseudo-distance function Determine the zenith tropospheric delay parameters of BeiDou satellite signals. ,in, , , This is a process mapping function.

[0054] Specifically, the observation data input includes preprocessed BeiDou observation data, including carrier phase observations (L1 and L2 bands), pseudorange observations (P1 and P2), BeiDou precise ephemeris (including satellite orbital three-dimensional coordinates x_sat(t), y_sat(t), and z_sat(t)), BeiDou precise clock bias products (satellite clock bias Δt_sat(t)), and the receiver's real-time initial position (latitude, longitude, and elevation). The carrier phase function and pseudorange function are shown below: ;

[0055] Where i represents frequency band (1, 2), ρ represents the geometric distance between the satellite and the BeiDou receiver, c represents the speed of light, Δtr represents the receiver clock bias, mi(ε) represents the tropospheric mapping function, ε represents the satellite elevation angle, λi represents the carrier wavelength, Ni represents the integer ambiguity, and εLi and εPi represent observation noise. Initial value of BeiDou receiver position: using BeiDou single-point positioning results or GPS-assisted positioning values; initial value of receiver clock bias Δt_r: set to 0 or roughly estimated based on pseudorange data; initial value of integer ambiguity Ni: estimated based on the difference between pseudorange and carrier phase, such as Ni + (Li × λi - Pi) / λi; initial value of ZTD: estimated using a standard atmospheric model, such as the ISA model. Iterative solution and convergence: First, the geometric distance ρ and the mapping function mi(ε) are calculated based on the initial parameters. These are then substituted into the above functional equation to construct the error equation. The least squares method is then used to solve the error equation, updating the BeiDou receiver position (Δx, Δy, Δz), the BeiDou receiver clock error Δt_r, ZTD, and integer ambiguity Ni. The "calculation-solution-update" process is then repeated, with parameters corrected after each iteration. Convergence is achieved when the parameter change is less than or equal to the threshold (position ≤ 0.1 mm, ZTD ≤ 0.01 mm, clock error ≤ 0.1 ns). After convergence, the final ZTD value is output.

[0056] Furthermore, the ZTD can be decomposed into the zenith static delay parameter (ZHD) and the zenith wet delay parameter (ZWD) using empirical formulas such as Satirov's formula.

[0057] 204. Based on the zenith wet delay parameter, determine the atmospheric precipitable water at each observation location in the target monitoring area and determine the water vapor tomography observation function.

[0058] In this embodiment of the invention, the atmospheric precipitable water content at each observation location in the target monitoring area is determined based on the zenith wet delay parameter. Simultaneously, the water vapor tomography observation function is determined as follows: PWV=∫ρ(r)·ds Where PWV is the atmospheric precipitable water, ρ(r) is the water vapor density of the grid cell, and ds is the path length of the satellite signal propagation within the grid.

[0059] 205. Determine the preset horizontal resolution and vertical height range of the target monitoring area. Based on the preset horizontal resolution and vertical height range, divide the target monitoring area into a three-dimensional grid and determine the propagation path length of the BeiDou satellite signal within the three-dimensional grid.

[0060] 206. Determine the regularization factor. Based on the regularization factor, introduce a regularization term into the water vapor tomography observation function. Based on atmospheric precipitable water and propagation path length, solve the water vapor tomography observation function after introducing the regularization term. Based on the solution results, determine the water vapor density value of each grid cell in the three-dimensional grid. Use the water vapor density value and spatiotemporal distribution characteristics of each grid cell as the three-dimensional water vapor field.

[0061] Specifically, a preset horizontal resolution and vertical height range are determined. Then, based on this preset horizontal resolution and vertical height range, the target monitoring area is divided into a three-dimensional uniform grid. For example, the preset horizontal resolution is 0.5-1 km, and the vertical height range is divided into 10-15 layers of three-dimensional grids from near-ground to 10 km. Using the water vapor density of each grid cell as the parameter to be inverted, a water vapor tomography observation function of the form "PWV=∫ρ(r)·ds" is constructed based on the PWV data of the virtual observation dataset and the satellite signal propagation path. To address the underdetermined nature of the water vapor tomography observation function, a regularization method is used. The regularization factor is adaptively determined using the L-curve method. This regularization factor introduces a regularization term into the water vapor tomography observation function to suppress oscillations in the inversion results. Then, based on atmospheric precipitable water and propagation path length, the water vapor tomography observation function with the regularization term introduced is solved to obtain a preliminary three-dimensional water vapor field. The preliminary three-dimensional water vapor field includes the distribution data of water vapor density and spatial location information of each grid cell.

[0062] Furthermore, after determining the preliminary three-dimensional water vapor field, in order to improve the accuracy of the determination of the three-dimensional water vapor field, it is necessary to correct the preliminary three-dimensional water vapor field. Based on this, the method includes: determining the initial three-dimensional water vapor field in the three-dimensional tomographic grid based on the atmospheric precipitable water and the water vapor tomography observation function. The system acquires reference observation data for the target monitoring area, including atmospheric precipitable water and radiosonde data received by fixed satellite signal receiving stations in the target monitoring area. The radiosonde data includes water vapor density at various altitudes in the target monitoring area calculated based on temperature and humidity. Based on the reference observation data and the initial three-dimensional water vapor field... The relationship between the observations is used to construct the observation matrix H, and to determine the observation vector corresponding to the reference observation data. And obtain the covariance matrix corresponding to the initial three-dimensional water vapor field. Based on the observation matrix H and the covariance matrix Determine the correction parameters for the initial three-dimensional water vapor field. ,in, R is the observation noise matrix of the initial three-dimensional water vapor field; using the correction parameters For the initial three-dimensional water vapor field The initial three-dimensional water vapor field is corrected and used as the three-dimensional water vapor field. ,in, .

[0063] The radiosonde data also includes data such as the radiosonde time and launch location. Specifically, fixed satellite signal receiving stations are strategically deployed within and around the target monitoring area. These stations continuously receive satellite signals to extract information related to atmospheric precipitable water. Radiosonde equipment is used to conduct probes in the target monitoring area at regular time intervals. Based on the obtained temperature and humidity data, the water vapor density at each altitude layer within the target monitoring area is determined. The correlation between each reference observation data point and each grid node in the three-dimensional grid is analyzed. The values ​​of each element in the observation matrix H are determined through mathematical modeling. Simultaneously, the atmospheric precipitable water data received by the fixed satellite signal receiving stations and the water vapor density data calculated from the radiosonde data are arranged in a specific order to form an observation vector. Meanwhile, based on the fluctuations in the water vapor field in historical meteorological data, the covariance matrix is ​​preliminarily estimated. The values ​​of each element are determined, and the variance of the water vapor density within a certain window is also determined. Based on this variance, the observation noise matrix R is determined. Then, based on the above information, the correction parameters for the initial three-dimensional water vapor field are determined. Finally, the corrected parameters are used. The initial three-dimensional water vapor field is corrected. This embodiment of the invention comprehensively utilizes multi-source reference observation data, including atmospheric precipitable water data received from fixed satellite signal receiving stations and water vapor density data calculated from radiosonde data. By constructing an observation matrix and other methods, these data from different sources and of different types are effectively fused together, fully leveraging the advantages of various data types and improving the accuracy and reliability of the three-dimensional water vapor field correction.

[0064] Furthermore, the corrected 3D water vapor field includes the water vapor density of each 3D grid cell within the target monitoring area, the grid's horizontal resolution, and the unique spatiotemporal coordinates (longitude, latitude, altitude, and time slice) corresponding to each grid. It may also include derived information: spatiotemporal distribution characteristics of water vapor across the entire region, such as high water vapor density accumulation areas, water vapor vertical gradients, and water vapor migration paths at different time slices. The corrected 3D water vapor field data (including water vapor density and spatiotemporal distribution characteristics of each grid) is then visualized and output. Subsequently, the 3D water vapor field is dynamically updated at set time slice intervals to achieve real-time dynamic monitoring of water vapor across the entire region.

[0065] According to another method for three-dimensional water vapor tomography based on mobile BeiDou equipment provided by the present invention, compared with the current method of receiving satellite signals and inverting atmospheric water vapor distribution through fixed ground satellite systems, the present invention plans an observation path for a mobile carrier equipped with BeiDou receiving equipment and controls the mobile carrier to travel along the observation path. Water vapor is tomographically analyzed using BeiDou observation data collected during the mobile carrier's travel. This allows for flexible planning of the observation path, overcomes the spatial limitations of fixed stations, and provides a wide monitoring range, enabling full-area water vapor monitoring. This improves the accuracy and flexibility of water vapor tomography. Furthermore, a single mobile carrier can monitor water vapor in multiple areas, saving on water vapor tomography costs. By decomposing the zenith wet delay parameter from the zenith tropospheric delay parameter, the influence of water vapor on satellite signals can be extracted separately, thus obtaining more accurate atmospheric water vapor information and achieving precise water vapor tomography.

[0066] Furthermore, as Figure 1 In specific implementation, embodiments of the present invention provide a three-dimensional water vapor chromatography device based on a mobile BeiDou system, such as... Figure 3 As shown, the device includes: an acquisition unit 31, a data acquisition unit 32, a decomposition unit 33, and a water vapor chromatography unit 34.

[0067] The acquisition unit 31 can be used to acquire regional feature data of the target monitoring area in response to the three-dimensional water vapor chromatography signal of the target monitoring area.

[0068] The data acquisition unit 32 can be used to plan an observation path for a mobile carrier equipped with a BeiDou receiving device based on the regional feature data, and control the mobile carrier to travel along the observation path. During the travel of the mobile carrier, the BeiDou observation data collected by the BeiDou receiving device is acquired.

[0069] The decomposition unit 33 can be used to determine the zenith tropospheric delay parameter of the BeiDou satellite signal based on the BeiDou observation data, and decompose the zenith tropospheric delay parameter into the zenith wet delay parameter.

[0070] The water vapor tomography unit 34 can be used to determine the atmospheric precipitable water at each observation location in the target monitoring area based on the zenith wet delay parameter, determine the water vapor tomography observation function, and analyze the three-dimensional water vapor field in the target monitoring area based on the atmospheric precipitable water and the water vapor tomography observation function.

[0071] In specific application scenarios, in order to preprocess BeiDou observation data, such as... Figure 4 As shown, the device also includes a preprocessing unit 35.

[0072] The preprocessing unit 35 can be used to take any type of BeiDou observation data from the BeiDou observation data as a target BeiDou observation data, determine path BeiDou observation data of different paths within a preset time period in the target BeiDou observation data, and detect and remove abnormal BeiDou observation data in the target BeiDou observation data based on the data mean and data standard deviation of the path BeiDou observation data; acquire the carrier motion data of the mobile carrier and the satellite signal data of the BeiDou satellite, wherein the carrier motion data includes the travel speed, acceleration, and attitude angle of the mobile carrier, and the satellite signal data includes the satellite elevation angle and satellite azimuth angle of the BeiDou satellite; acquire a collaborative correction function, and determine the multipath error correction parameters of the BeiDou observation data based on the carrier motion data and the satellite signal data; and perform multipath error correction on the target BeiDou observation data after removing abnormal BeiDou observation data based on the multipath error correction parameters to obtain the path-corrected target BeiDou observation data.

[0073] In specific application scenarios, the BeiDou observation data includes BeiDou satellite orbit parameters and pseudorange. To preprocess the BeiDou observation data, the preprocessing unit 35 can also be used to acquire precise ephemeris files and clock bias files. The precise ephemeris file contains reference satellite orbit parameters at multiple times, and the clock bias file contains reference clock bias parameters at multiple times. Based on the reference satellite orbit parameters at multiple times, the parameter correction amount of the BeiDou satellite orbit parameters is determined, and based on the reference clock bias parameters at multiple times, the clock bias correction amount of the pseudorange is determined. The BeiDou satellite orbit parameters are corrected based on the parameter correction amount, and the pseudorange is corrected based on the clock bias correction amount.

[0074] In specific application scenarios, in order to time-align BeiDou observation data, the preprocessing unit 35 can also be used to determine the data acquisition reference time and the actual acquisition time of the BeiDou observation data; based on the acquisition reference time and the actual acquisition time, determine the missing acquisition time; based on the difference between the missing acquisition time and the corresponding acquisition reference time, complete the BeiDou observation data under the missing acquisition time; determine the data acquisition reference position and the actual acquisition position of the BeiDou observation data; based on the acquisition reference position and the actual acquisition position, determine the missing acquisition position; determine the neighboring actual acquisition position corresponding to the missing acquisition position; determine the positional relationship between the missing acquisition position and the neighboring actual acquisition position; and based on the BeiDou observation data of the neighboring actual acquisition position at the same time and the positional relationship, complete the BeiDou observation data of the missing acquisition position.

[0075] In specific application scenarios, the BeiDou observation data includes satellite elevation angles. carrier wavelength of band i Geometric distance between the BeiDou satellite and the mobile carrier In order to determine the zenith tropospheric delay parameters of the BeiDou satellite signal, the decomposition unit 33 includes a first acquisition module 331 and a first determination module 332.

[0076] The first acquisition module 331 can be used to acquire the carrier phase function. and pseudo-distance function .

[0077] The first acquisition module 331 can also be used to acquire solution reference data for the zenith tropospheric delay parameters, wherein the solution reference data includes the speed of light c and the receiving clock bias of the mobile carrier. carrier wavelength Whole week blur Carrier phase observation noise pseudorange observation noise .

[0078] The first determining module 332 can be used to determine the BeiDou observation data, the solution reference data, and the carrier phase function. and the pseudo-distance function Determine the zenith tropospheric delay parameters of BeiDou satellite signals. ,in, , , This is a process mapping function.

[0079] In specific application scenarios, in order to analyze the three-dimensional water vapor field in the target monitoring area, the water vapor tomography unit 34 can be used to determine the preset horizontal resolution and vertical height range of the target monitoring area. Based on the preset horizontal resolution and the vertical height range, the target monitoring area is divided into a three-dimensional grid, and the propagation path length of the Beidou satellite signal within the three-dimensional grid is determined. A regularization factor is determined, and based on the regularization factor, a regularization term is introduced into the water vapor tomography observation function. Based on the atmospheric precipitable water and the propagation path length, the water vapor tomography observation function after introducing the regularization term is solved. Based on the solution result, the water vapor density value of each grid cell in the three-dimensional grid is determined, and the water vapor density value and spatiotemporal distribution characteristics of each grid cell are used as the three-dimensional water vapor field.

[0080] In specific application scenarios, in order to analyze the three-dimensional water vapor field in the target monitoring area, the water vapor tomography unit 34 includes a second determination module 341 and a correction module 342.

[0081] The second determining module 341 can be used to determine the initial three-dimensional water vapor field in the three-dimensional tomographic grid based on the atmospheric precipitable water and the water vapor tomography observation function. The system acquires reference observation data for the target monitoring area, wherein the reference observation data includes atmospheric precipitable water and radiosonde data received by fixed satellite signal receiving stations in the target monitoring area, and wherein the radiosonde data includes water vapor density at each altitude layer of the target monitoring area calculated based on temperature and humidity.

[0082] The second determining module 341 can also be used to determine the reference observation data and the initial three-dimensional water vapor field. The relationship between the observations is used to construct the observation matrix H, and to determine the observation vector corresponding to the reference observation data. And obtain the covariance matrix corresponding to the initial three-dimensional water vapor field. Based on the observation matrix H and the covariance matrix Determine the correction parameters for the initial three-dimensional water vapor field. ,in, R is the observation noise matrix of the initial three-dimensional water vapor field.

[0083] The correction module 342 can be used to utilize the correction parameters. For the initial three-dimensional water vapor field The initial three-dimensional water vapor field is corrected and used as the three-dimensional water vapor field. ,in, .

[0084] In specific application scenarios, in order to plan the observation path for a mobile carrier equipped with a Beidou receiving device, the data acquisition unit 32 includes a second acquisition module 321, a third determination module 322, and a path planning module 323.

[0085] The second acquisition module 321 can be used to acquire water vapor chromatography requirement information.

[0086] The third determining module 322 can be used to determine a path planning strategy based on the regional feature data and the water vapor chromatography demand information.

[0087] The path planning module 323 can be used to plan a grid cross-observation path for a mobile carrier equipped with a Beidou receiving device based on the path planning strategy.

[0088] It should be noted that other corresponding descriptions of the functional modules involved in the three-dimensional water vapor chromatography device based on mobile Beidou equipment provided in this embodiment of the invention can be found in the following references. Figure 1 The corresponding descriptions of the methods shown will not be repeated here.

[0089] Based on the above, Figure 1 Accordingly, this embodiment of the invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, performs the following steps: responding to a three-dimensional water vapor tomography signal of a target monitoring area, acquiring regional feature data of the target monitoring area; based on the regional feature data, planning an observation path for a mobile carrier equipped with a BeiDou receiving device, and controlling the mobile carrier to travel along the observation path, acquiring BeiDou observation data collected by the BeiDou receiving device during the travel of the mobile carrier; based on the BeiDou observation data, determining the zenith tropospheric delay parameter of the BeiDou satellite signal, and decomposing the zenith tropospheric delay parameter into an out-zenith wet delay parameter; based on the zenith wet delay parameter, determining the atmospheric precipitable water at each observation location in the target monitoring area, determining the water vapor tomography observation function, and analyzing the three-dimensional water vapor field in the target monitoring area based on the atmospheric precipitable water and the water vapor tomography observation function.

[0090] Based on the above, Figure 1 The method shown and as Figure 3 The embodiment of the device shown in the invention also provides a physical structure diagram of a computer device, such as... Figure 5 As shown, the computer device includes: a processor 41, a memory 42, and a computer program stored in the memory 42 and executable on the processor. Both the memory 42 and the processor 41 are mounted on a bus 43. When the processor 41 executes the program, it performs the following steps: responding to a three-dimensional water vapor tomography signal of the target monitoring area, it acquires regional characteristic data of the target monitoring area; based on the regional characteristic data, it plans an observation path for a mobile carrier equipped with a BeiDou receiver and controls the mobile carrier to travel along the observation path; during the travel of the mobile carrier, it acquires BeiDou observation data collected by the BeiDou receiver; based on the BeiDou observation data, it determines the zenith tropospheric delay parameter of the BeiDou satellite signal and decomposes the zenith tropospheric delay parameter into an out-zenith wet delay parameter; based on the zenith wet delay parameter, it determines the atmospheric precipitable water at each observation location in the target monitoring area, determines the water vapor tomography observation function, and analyzes the three-dimensional water vapor field in the target monitoring area based on the atmospheric precipitable water and the water vapor tomography observation function.

[0091] Through the technical solution of this invention, the invention plans an observation path for a mobile carrier equipped with BeiDou receiving equipment and controls the mobile carrier to travel along the observation path. The BeiDou observation data collected during the mobile carrier's travel is used to perform tomography on water vapor. This allows for flexible planning of the observation path, overcomes the spatial limitations of fixed stations, and provides a wide monitoring range, enabling comprehensive water vapor monitoring. This improves the accuracy and flexibility of water vapor tomography. Furthermore, a single mobile carrier can monitor water vapor in multiple regions, saving on water vapor tomography costs. By decomposing the zenith wet delay parameter from the zenith tropospheric delay parameter, the influence of water vapor on satellite signals can be extracted separately, resulting in more accurate acquisition of atmospheric water vapor information and ultimately achieving precise water vapor tomography.

[0092] It is obvious to those skilled in the art that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0093] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A three-dimensional water vapor chromatography method based on mobile BeiDou equipment, characterized in that, include: In response to the three-dimensional water vapor chromatography signal of the target monitoring area, regional feature data of the target monitoring area are acquired; Based on the regional feature data, an observation path is planned for the mobile carrier equipped with the BeiDou receiving device, and the mobile carrier is controlled to travel along the observation path. During the travel of the mobile carrier, the BeiDou observation data collected by the BeiDou receiving device is acquired. Based on the BeiDou observation data, the zenith tropospheric delay parameter of the BeiDou satellite signal is determined, and the zenith tropospheric delay parameter is decomposed into the zenith wet delay parameter. Based on the zenith wet delay parameter, the atmospheric precipitable water content at each observation location in the target monitoring area is determined, the water vapor tomography observation function is determined, and the three-dimensional water vapor field in the target monitoring area is analyzed based on the atmospheric precipitable water content and the water vapor tomography observation function.

2. The method according to claim 1, characterized in that, Before determining the zenith tropospheric delay parameter of the BeiDou satellite signal based on the aforementioned BeiDou observation data, the method further includes: Each type of BeiDou observation data is taken as a target BeiDou observation data. Path BeiDou observation data with different paths within a preset time period are determined from the target BeiDou observation data. Based on the mean and standard deviation of the path BeiDou observation data, abnormal BeiDou observation data is detected and removed from the target BeiDou observation data. The carrier motion data and BeiDou satellite signal data are obtained, wherein the carrier motion data includes the travel speed, acceleration, and attitude angle of the mobile carrier, and the satellite signal data includes the satellite elevation angle and satellite azimuth angle of the BeiDou satellite; Obtain the collaborative correction function, and based on the carrier motion data and the satellite signal data, use the collaborative correction function to determine the multipath error correction parameters of the BeiDou observation data; Based on the multipath error correction parameters, the target BeiDou observation data after removing abnormal BeiDou observation data is corrected for multipath error, resulting in the path-corrected target BeiDou observation data.

3. The method according to claim 1, characterized in that, The BeiDou observation data includes BeiDou satellite orbital parameters and pseudorange; Before determining the zenith tropospheric delay parameter of the BeiDou satellite signal based on the aforementioned BeiDou observation data, the method further includes: Obtain a precise ephemeris file and a clock error file, wherein the precise ephemeris file contains reference satellite orbit parameters at multiple times, and the clock error file contains reference clock error parameters at multiple times; Based on reference satellite orbit parameters at multiple times, the parameter correction amount of the BeiDou satellite orbit parameters is determined, and based on reference clock error parameters at multiple times, the clock error correction amount of the pseudorange is determined. The BeiDou satellite orbit parameters are corrected based on the parameter correction amount, and the pseudorange is corrected based on the clock error correction amount. The method further includes: Determine the data acquisition reference time and the actual acquisition time of the BeiDou observation data; based on the acquisition reference time and the actual acquisition time, determine the missing acquisition time; and based on the difference between the missing acquisition time and the corresponding acquisition reference time, complete the BeiDou observation data under the missing acquisition time. The data acquisition reference location and the actual acquisition location of the BeiDou observation data are determined. Based on the acquisition reference location and the actual acquisition location, the missing acquisition location is determined. The corresponding neighboring actual acquisition location is determined. The positional relationship between the missing acquisition location and the neighboring actual acquisition location is determined. Based on the BeiDou observation data of the neighboring actual acquisition location at the same time and the positional relationship, the BeiDou observation data of the missing acquisition location is completed.

4. The method according to claim 1, characterized in that, The BeiDou observation data includes satellite elevation angle. carrier wavelength of band i Geometric distance between the BeiDou satellite and the mobile carrier ; The determination of the zenith tropospheric delay parameter of the BeiDou satellite signal based on the BeiDou observation data includes: Obtain the carrier phase function and pseudo-distance function ; To obtain reference data for solving the zenith tropospheric delay parameters, the reference data includes the speed of light c and the receiving clock bias of the mobile carrier. carrier wavelength Whole week blur Carrier phase observation noise pseudorange observation noise ; Based on the BeiDou observation data, the solution reference data, and the carrier phase function and the pseudo-distance function Determine the zenith tropospheric delay parameters of BeiDou satellite signals. ,in, , , This is a process mapping function.

5. The method according to claim 1, characterized in that, The analysis of the three-dimensional water vapor field in the target monitoring area based on the atmospheric precipitable water and the water vapor tomography observation function includes: A preset horizontal resolution and vertical height range for the target monitoring area are determined. Based on the preset horizontal resolution and the vertical height range, the target monitoring area is divided into a three-dimensional grid, and the propagation path length of the BeiDou satellite signal within the three-dimensional grid is determined. A regularization factor is determined, and a regularization term is introduced into the water vapor tomography observation function based on the regularization factor. The water vapor tomography observation function after introducing the regularization term is solved based on the atmospheric precipitable water and the propagation path length. The water vapor density value of each grid cell in the three-dimensional grid is determined based on the solution result, and the water vapor density value and spatiotemporal distribution characteristics of each grid cell are used as the three-dimensional water vapor field.

6. The method according to claim 1, characterized in that, The analysis of the three-dimensional water vapor field in the target monitoring area based on the atmospheric precipitable water and the water vapor tomography observation function includes: Based on the atmospheric precipitable water and the water vapor tomography observation function, the initial three-dimensional water vapor field in the three-dimensional tomography grid is determined. And obtain reference observation data of the target monitoring area, wherein the reference observation data includes atmospheric precipitable water and radiosonde data received by fixed satellite signal receiving stations in the target monitoring area, wherein the radiosonde data includes water vapor density at each altitude layer of the target monitoring area calculated based on temperature and humidity; Based on the reference observation data and the initial three-dimensional water vapor field The relationship between the observations is used to construct the observation matrix H, and to determine the observation vector corresponding to the reference observation data. And obtain the covariance matrix corresponding to the initial three-dimensional water vapor field. Based on the observation matrix H and the covariance matrix Determine the correction parameters for the initial three-dimensional water vapor field. ,in, R is the observation noise matrix of the initial three-dimensional water vapor field; Using the correction parameters For the initial three-dimensional water vapor field The initial three-dimensional water vapor field is corrected and used as the three-dimensional water vapor field. ,in, .

7. The method according to claim 1, characterized in that, Based on the aforementioned regional feature data, an observation path is planned for a mobile carrier equipped with a BeiDou receiver, including: Obtain information on water vapor chromatography requirements; Based on the regional characteristic data and the water vapor chromatography demand information, a path planning strategy is determined. Based on the path planning strategy, a grid cross-observation path is planned for a mobile carrier equipped with a BeiDou receiver.

8. A three-dimensional water vapor chromatography device based on mobile BeiDou equipment, characterized in that, include: The acquisition unit is used to acquire regional feature data of the target monitoring area in response to the three-dimensional water vapor chromatography signal of the target monitoring area; The data acquisition unit is used to plan an observation path for a mobile carrier equipped with a BeiDou receiving device based on the regional feature data, and control the mobile carrier to travel along the observation path. During the travel of the mobile carrier, the unit acquires the BeiDou observation data collected by the BeiDou receiving device. The decomposition unit is used to determine the zenith tropospheric delay parameter of the BeiDou satellite signal based on the BeiDou observation data, and decompose the zenith tropospheric delay parameter into an out-zenith wet delay parameter. The water vapor tomography unit is used to determine the atmospheric precipitable water at each observation location in the target monitoring area based on the zenith wet delay parameter, determine the water vapor tomography observation function, and analyze the three-dimensional water vapor field in the target monitoring area based on the atmospheric precipitable water and the water vapor tomography observation function.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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