142 results about "Troposphere" patented technology

The invention discloses a troposphere delay model construction method based on a numerical meteorological model and an unmanned aerial vehicle, and the method comprises the steps: obtaining meteorological parameter values in the numerical meteorological model for a target region; a troposphere observation value obtained by the target unmanned aerial vehicle through the airborne GNSS receiver and the airborne multi-source meteorological equipment in the process of moving along the preset path in the target area is obtained; determining first troposphere delay data according to the meteorological parameter values and a corresponding preset oblique troposphere delay model; determining second troposphere delay data by adopting a preset ambiguity fixing algorithm based on the satellite observation value; and according to the first troposphere delay data and the second troposphere delay data, determining troposphere delay data of the target area. According to the method, accurate estimation of troposphere delay in a complex region and a meteorological condition rapid change region is realized, and a reliable troposphere delay model is provided for realizing high-precision monitoring of InSAR (Interferometric Synthetic Aperture Radar) deformation monitoring.

The invention relates to the technical field of mine environment risks, and discloses a mine environment risk multi-modal analysis and early warning decision-making method, which comprises the following steps of: performing time and space reference alignment on multi-source observation data, constructing a unified spatio-temporal data set, and establishing a troposphere disturbance model to realize observation disturbance coupling. And constructing a physical evolution operator and a rainfall-driven external input operator based on a seepage mechanical relationship, and generating a state evolution mechanism. Semantic direction parameters are generated by mapping semantic query information to a target attention dimension, and a lagging propagation operator is constructed by setting a rainstorm ending moment as a starting point. And determining a non-regular spectrum transition index and a peak lag moment through the non-regularity measurement and the dynamic change rate of each lag propagation operator, and setting a reference threshold value based on the spectrum transition index of a historical non-risk time period. Finally, when the early warning intensity meets the condition, early warning is output, and a query result is generated in combination with the lagging propagation operator and the semantic direction parameters.

The invention belongs to the crossing field of space geodetics, satellite navigation positioning technology and atmospheric science, and discloses a real-time troposphere delay modeling method for enhancing a global forecasting system. The method comprises the following specific steps: firstly, acquiring zenith fluid static delay and zenith wet delay predicted by earth surface GFS, and constructing a regional grid difference time sequence by taking a fusion result of ERA5 data and a GNSS troposphere delay product as a reference; secondly, fitting the difference to form a GFS enhanced core model; meanwhile, a troposphere delay correction model from the grid height to the target site height is constructed based on ERA5 stratified atmosphere data, time sequence modeling is carried out on model coefficients, and finally refined troposphere delay output at different heights is achieved. The method has the advantages that (1) the real-time troposphere model is high in precision; (2) real-time application can keep robust performance without depending on a GNSS network; (3) expansion and deployment are facilitated; and (4) the real-time performance is strong, and seamless integration precision positioning application can be realized.

The invention discloses a troposphere BrO vertical profile inversion method, medium and equipment based on machine learning, and the method comprises the steps: obtaining BrO vertical profile data, inputting the profile data, aerosol characteristic parameters, geometric angle parameters and earth surface characteristic parameters into an atmospheric radiation transmission model, and obtaining BrO DSCD data; the obtained DSCD and the profile data set are preprocessed; training a troposphere BrO vertical distribution inversion model combining a convolutional neural network CNN and a long short-term memory network LSTM by using the preprocessed DSCD and profile data set; and performing QDOAS processing on MAX-DOAS spectral data to be inverted to obtain DSCD data, inputting the preprocessed DSCD data, aerosol parameters and geometric angle parameters into the trained CNN-LSTM troposphere BrO vertical distribution inversion model to perform data inversion, and finally obtaining an inversion result of troposphere BrO vertical distribution. According to the invention, the accuracy and stability of an inversion result can be significantly improved.

The invention relates to the technical field of engineering monitoring, in particular to an unmanned aerial vehicle dynamic monitoring and early warning system and method for the whole subway tunnel excavation process, and the system comprises a virtual base station differential positioning module which is used for carrying out the unmanned aerial vehicle dynamic monitoring and early warning according to a carrier phase observation value transmitted by a ground active control target and a satellite signal observation value obtained by an airborne receiving end, and calculating ionosphere residual values and troposphere residual values between the current position of the unmanned aerial vehicle and the three adjacent ground active control targets. According to the method, the pixel gradient vector of the thermal inertia matrix is further calculated, the edge candidate points exceeding the threshold value are extracted, and the edge candidate points are closed in the gradient vertical direction to form the geometric region, so that the fuzzy thermal field anomaly is converted into the quantized graph with the definite physical boundary, and the hidden danger area and the internal gradient mean value are combined for calculation; the risk early warning level can be dynamically generated according to the tunnel design tolerance, so that recognition and hierarchical management and control of hidden geological disasters are realized on the premise of not contacting the ground.

The invention discloses an atmospheric turbulence phase screen generation method based on layered physical constraints, and belongs to the crossing field of optical communication and artificial intelligence. According to the method, a diffusion probability model is combined with layered atmospheric physical constraints, independent physical constraint loss functions are established for a boundary layer, a troposphere and a stratosphere of the atmosphere, and it is ensured that a generated phase screen conforms to turbulent flow statistical characteristics of all layers through power spectrum density constraints and structure function constraints; enhancing feature learning of each layer of phase screen by adopting a physically guided attention mechanism; and designing a time-dependent constraint weight strategy, and adaptively adjusting the physical constraint strength in the diffusion denoising process. The method solves the technical problems that the vertical layering difference is ignored, the physical consistency is insufficient, and the generation quality depends on a large amount of labeled data in the existing method, is particularly suitable for high-fidelity atmospheric turbulence modeling of a satellite laser communication link, and can also be widely applied to the fields of free space optical communication system simulation, adaptive optical system design and the like.

The invention relates to the technical field of satellite navigation meteorological remote sensing, and discloses a water vapor ionized layer snow depth integrated detection method and system. The method comprises the steps that direct and reflected signals of a Beidou satellite are received through fusion antenna array differentiation, carrier phase and pseudo-range observation values are obtained through carrier tracking loop synchronous demodulation, the total atmospheric rainfall amount and the total ionosphere electron content are extracted through a troposphere and ionosphere combined calculation algorithm, the snow depth is inverted through reflection path geometric difference, and the snow depth is calculated. And carrying out space-time synchronization constraint processing on the extended Kalman filter to realize multi-parameter integrated detection. The problems of low efficiency, insufficient precision and lack of cooperative processing caused by independent observation of water vapor, ionized layer and accumulated snow parameters in the prior art are solved, and the observation efficiency and the measurement precision of multi-parameter integrated detection are improved.

The invention provides a weather forecasting method based on big Beidou three-dimensional water vapor and weather model cooperative driving, and the method comprises the steps: carrying out the point-by-point registration of the obtained prediction data of a GraphCast model and ERA5 measured data, obtaining residual field data, taking the residual field data as the input of a deep learning residual correction network, and obtaining predicted residual field data; a terrain adaptive algorithm is adopted, predicted ERA5 meteorological parameters corresponding to the predicted residual field data are converted into a three-dimensional grid structure under height coordinates, and zenith troposphere delay is determined through an integration method; based on the dynamic correction term, converting the zenith troposphere delay into a precipitable water amount through a space-time inversion network; inputting the predicted ERA5 meteorological parameters and the rainfall data into a parameter efficient adapter and a big ancient meteorological model to obtain meteorological forecast factors output by the big ancient meteorological model; through the above technical scheme, real-time positioning enhancement and gradual improvement of meteorological element forecasting capability can be realized.

The invention discloses a Beidou / GNSS differential service fault analysis method and system, and relates to satellite positioning. The method comprises the following steps: carrying out pseudo-range single-point positioning on Beidou / GNSS observation data to obtain a general position; reporting the approximate position to a Beidou / GNSS differential service platform to request Beidou / GNSS differential data of the current position; carrying out observation data quality analysis on the Beidou / GNSS observation data, wherein observation data quality analysis indexes comprise an integrity rate, a satellite number, a carrier-to-noise ratio, multiple paths, pseudo-range noise, carrier noise, a cycle slip ratio and a PDOP value; differential data quality analysis is carried out on the Beidou / GNSS differential data; rTK calculation is carried out on the Beidou / GNSS observation data and the Beidou / GNSS differential data; calculating a troposphere residual error and an ionosphere residual error; and performing fault detection according to the data. Aiming at the problem that Beidou / GNSS differential service fault positioning precision is low in the prior art, accurate identification and positioning of differential service faults are realized.

A method, device, equipment and medium for independent modeling of troposphere anisotropy of dry and wet convection layers, the method comprising: constructing a troposphere anisotropy model, which adopts a tilted plane horizontal gradient model to respectively describe dry delay anisotropy and wet delay anisotropy; deriving oblique dry delay through a numerical meteorological model, calculating a dry horizontal gradient parameter through the oblique dry delay, and correcting the dry delay anisotropy by using the dry horizontal gradient parameter; taking a wet horizontal gradient parameter as an unknown parameter to be estimated into an observation equation and performing dynamic estimation, and correcting the wet delay anisotropy by using the estimated wet horizontal gradient parameter. The present application adopts an asymmetric processing strategy of dry delay anisotropy model correction and wet delay anisotropy parameter estimation, which not only avoids the ill-conditioned problem of observation equation caused by simultaneous estimation of dry and wet gradients, but also utilizes the high accuracy of the numerical meteorological model in describing the dry delay anisotropy, so that the positioning stability and accuracy are improved at the same time.

The invention relates to the technical field of GNSS high-precision positioning calculation, and discloses a GNSS troposphere delay error real-time correction method and device and a medium, and the method comprises the steps: presetting a first process noise model and a second process noise model corresponding to different constraint values; acquiring motion state parameters of a GNSS receiver, atmospheric disturbance characteristic measurement of bypass information and a model mismatch index of a Kalman filter; when a preset dynamic motion condition is met, selecting a first process noise model; when the preset dynamic motion condition is not met, the first process noise model or the second process noise model is selected according to the atmospheric disturbance characteristic measurement and the model mismatch index, multi-source information is used for cooperative judgment, an algorithm closed loop capable of achieving autonomous recognition and avoiding carrier motion pollution and bypass information failure is constructed, and the algorithm closed loop is optimized. Mathematical coupling of elevation and zenith delay is avoided, and high-reliability rapid convergence can be achieved for independent users without network assistance.

The invention provides a troposphere anisotropy-considered real-time PPP positioning method, and relates to the technical field of satellite navigation and positioning, and the method comprises the following steps: S01, receiving real-time GNSS observation data, broadcast ephemeris data and precision correction data, carrying out detection and restoration of clock slip and cycle slip, data quality control and preprocessing of antenna phase correlation errors on the data to obtain a preprocessed data set; s02, calculating the solar altitude after atmospheric refraction correction according to each preprocessed data set and the geographic position and observation time of the observation station corresponding to each data set; and S03, based on the solar altitude and the satellite altitude. According to the method, solar altitude parameters are introduced, the troposphere anisotropy effect caused by solar radiation is effectively modeled, and the precision and convergence speed of real-time precise single-point positioning are remarkably improved.

The application discloses a Beidou satellite-based unmanned plane real-time tracking and positioning system and method, relates to the technical field of high-precision navigation and unmanned plane real-time tracking and positioning, and comprises a receiving module, which receives signals of Beidou satellites and global navigation satellite systems in real time through an antenna, converts and demodulates the signals to obtain pseudo ranges; a processing module, which detects and preliminarily corrects the pseudo ranges, and further corrects and optimizes the preliminarily corrected pseudo ranges according to delay effects of ionospheres and tropospheres; the application corrects the pseudo ranges according to the multipath effect, reduces the influence of reflection and refraction on GNSS signals, significantly improves the positioning precision, further reduces the pseudo range error through the correction of the ionosphere and the troposphere, thereby improving the position solution precision, and significantly improving the positioning real-time performance of the unmanned plane.

The invention discloses a bionic air-space cooperative atmosphere intelligent regulation and control system and method. The system comprises a twin digital earth, an atmospheric brain, an air-space AI mobile base comprising a troposphere special base and a stratosphere special base, a plurality of macroscopic telescopic pipelines, an array composed of macroscopic intelligent sunshade reflectors, and a multifunctional intelligent micro-unit cluster. A regulation and control strategy is generated through multi-source data assimilation and intelligent strategy optimization, physical states such as temperature and humidity of air masses in a pipeline are actively adjusted through an environment control section in a macroscopic telescopic pipeline, and low-energy-consumption, stepped and directional transportation of cloud water substances is achieved by actively utilizing the chimney effect formed by the atmospheric environment; controllable adjustment of solar radiation input is achieved through dynamic management of the intelligent sunshade reflector array. The system has four operation modes which can be evolved according to technical capability stages from macroscopic direct intervention to global intelligent collaboration, and is configured with a module recovery and platform stability anchoring mechanism so as to realize emergency intervention on disastrous weather.

The invention discloses a polar region troposphere delay error model construction method, a polar region troposphere delay error calculation method, a polar region troposphere delay error calculation device, polar region troposphere delay error calculation equipment and a medium. The polar region troposphere delay error model construction method comprises the steps that a target data set is acquired, the target data set comprises basic observation data and space-time attribute data of a target observation point, and a target wet delay sub-model is calculated by adopting a trigonometric function fitting method based on the target data set; and obtaining a pre-constructed target dry delay sub-model, and constructing a target troposphere delay error model according to the target wet delay sub-model and the target dry delay sub-model. Through the technical scheme of the invention, the construction of the polar region troposphere delay error model and the calculation of the polar region troposphere delay can be realized, and the calculation efficiency of the polar region troposphere delay error and the accuracy of the calculation result are improved.

This invention relates to a method and system for broadcasting PPP-RTK corrections. The method includes acquiring grid point information; determining correction information according to a dynamic partitioning method based on the satellite's orbital direction, satellite signal coverage area, and the grid point information; the correction information includes a header file, the grid point information, tropospheric corrections, and oblique ionospheric corrections; and uploading the correction information to an uplink station to control satellite broadcasting of the correction information. This invention solves the problems of satellite bandwidth allocation, correction area division, and correction data format encoding for PPP-RTK atmospheric delay corrections broadcast in low-Earth orbit satellite broadcasting areas.

The invention discloses a troposphere delay multi-layer grid modeling method fusing GNSS and ray tracing, which comprises the following steps of: performing ambiguity fixing processing on non-difference and non-combination PPP positioning data from GNSS reference stations, and estimating per-epoch parameters of each reference station, including troposphere delay, a satellite elevation angle and an azimuth angle; the longitude, the latitude and the altitude of the receiver are measured; the estimation parameters except for the troposphere delay are combined with meteorological data to serve as input of ray tracing calculation, so that the troposphere delay profile of the position of each receiver is determined to serve as ray tracing troposphere delay; and according to the troposphere delay estimated by the GNSS at the height of the reference station and the ray tracing troposphere delay, combining the ray tracing troposphere delays calculated at different height layers to obtain GNSS troposphere delays at different height layers, and forming a multi-layer GNSS troposphere delay product.

The invention discloses a geological disaster early warning method based on troposphere delay decoupling, and relates to the field of geological disaster monitoring and navigation positioning, and the method comprises the steps: carrying out the time-space synchronous collection of multi-modal data; geologically decoupling the troposphere delay component, and converting atmospheric noise into a geological signal; constructing delay-catastrophe parameter dynamic mapping; dynamically reconstructing a terrain adaptive reference station, and dynamically reconstructing a virtual GNSS reference point network with the same height as a monitoring point by using a digital elevation model (DEM); performing three-dimensional reconstruction on a disaster risk field, fusing the delay mapping factor and the earth surface deformation data, and generating a multi-dimensional risk field; constructing an early warning threshold self-evolution mechanism; and constructing a multi-stage joint control early warning decision. According to the invention, the accuracy of early warning of geological disasters can be improved, and intelligent technical support is provided for disaster prevention and reduction.

The application provides a multi-path signal snow thickness inversion method, device, storage medium and program product. It relates to the field of satellite measurement technology. The method comprises the following steps: obtaining the inter-satellite single difference between each target satellite and a reference satellite according to the carrier observation values of multiple satellites received by a base station at the same time; obtaining the slant path ionospheric delay of each target satellite and the zenith slant path tropospheric wet delay correction value of each target satellite according to the carrier observation value of each target satellite and the tropospheric delay wet component projection function; obtaining the inter-satellite single difference multi-path between each target satellite and the reference satellite based on the slant path ionospheric delay of each target satellite, the slant path tropospheric wet delay correction value and the inter-satellite single difference; and calculating the snow thickness according to the main frequency of the inter-satellite single difference multi-path of the target satellite. The application can achieve the effect of obtaining the snow thickness in time and accurately.

The invention belongs to the technical field of communication, and discloses a pruning and fine tuning troposphere waveguide prediction method and system based on multi-granularity evaluation, and the method comprises the steps: calculating edge loss and task loss; fusing edge loss and task loss to construct a channel importance evaluation system, and performing quantitative evaluation and dynamic sorting on the contribution degree of the atmospheric waveguide prediction channel; on the basis of the sorting of atmospheric waveguide prediction channels, redundant channels are gradually eliminated by adopting an iterative pruning algorithm until a preset pruning rate is reached; and calculating the prediction confidence of the atmospheric waveguide prediction model before and after pruning, positioning a high-sensitivity atmospheric waveguide sample of which the prediction result is remarkably reduced, establishing a dynamic sample weighting mechanism, and performing fine adjustment compensation on the residual channel weight by using error back propagation. According to the method, a multi-granularity importance evaluation cutting mechanism and a prediction information guiding method are adopted, lightweight compression and fine adjustment are performed on the model, the effectiveness of the prediction model is improved, and accurate prediction and interaction of the non-uniform atmospheric waveguide are realized.

The present application belongs to the technical field of flight test, and particularly relates to a kind of troposphere manned airship fuel system hot climate test flight method. Including: S1: determining test flight condition;S2: make airship climb to the minimum safe height after stable flight first time, gradually increase the power of transmitter to maximum continuous power;S3: after speed stabilization, climb to maximum use height at maximum continuous power;S4: monitor fuel pressure, fuel flow and engine operation during climbing, monitor whether there is gas lock phenomenon caused by fuel overheating, which leads to unstable engine operation;S5: if there is no gas lock phenomenon caused by fuel overheating, which leads to unstable engine operation, airship climbs to maximum use height, returns and lands;S6: if fuel pressure is within normal range, fuel flow is within normal range, and engine does not work abnormally due to fuel interruption during test, then fuel system hot climate test flight is completed.

A method and apparatus for constructing a crowdsourced tropospheric delay correction map using low-Earth orbit (LEO) satellite augmentation, includes: constructing a combined LEO satellite augmentation and ionospheric de-radicalization (PPP) function model; using the relative positions among crowdsourced GNSS users as additional constraints, and taking one crowdsourced GNSS user as the absolute position reference, constructing a tropospheric estimation function model based on the LEO satellite augmentation and ionospheric de-radicalization PPP function model; solving the tropospheric estimation function model to obtain the tropospheric parameters of the crowdsourced GNSS users, performing robustness processing to obtain a crowdsourced tropospheric correction product, and uploading the crowdsourced tropospheric correction product to the cloud to form a crowdsourced tropospheric map. This invention combines LEO satellite geometric augmentation with crowdsourced spatial redundancy, enabling users to achieve rapid, even second-level, independent convergence of tropospheric parameters based on their own observations. Simultaneously, reliable tropospheric parameter estimates can be obtained without relying on external bias products, achieving second-level convergence and highly reliable estimation of tropospheric parameters.

The present application belongs to the field of flight test technology, and relates to a kind of indication recording system test flight method suitable for troposphere manned airship.The method comprises: hovering 360 in the three time periods of sunrise, strongest sunlight and sunset respectively;In the above hovering process, it is observed whether the display data displayed by the display is easy to see under different angle illumination conditions;If there is an abnormal working condition in the above process, optimization improvement suggestions are proposed for it, and then the above steps are repeated until the qualified criterion is met.

The invention discloses an overshoot cloud top identification and area calculation method and device based on geostationary satellite data. The method comprises the following steps: acquiring geostationary satellite cloud radiation brightness temperature data and troposphere top temperature data of a target area in a required time period; extracting cloud radiation brightness temperature of water vapor, ozone and infrared channels; after space-time matching, a multi-channel threshold discrimination method is used to identify potential overshoot cloud top pixels; based on the infrared brightness temperature data, utilizing an isotherm analysis method to identify a potential overshoot cloud top area and an anvil cloud area corresponding to each potential overshoot cloud top pixel; identifying an overshoot cloud top region and calculating the area of the overshoot cloud top region by comparing the average brightness temperature difference between the potential overshoot cloud top pixel and the anvil cloud region; the device comprises a data receiving and caching module, a data processing unit and a result output unit, and all the steps in the method are achieved. According to the method, satellite multi-channel brightness temperature data and troposphere top temperature data are combined, interference of cirrus cloud pixels is effectively eliminated, the overshoot cloud top is accurately recognized, and overshoot cloud top area calculation is achieved.

This provides a real-time kinematic (RTK) solution for mobile devices with multi-constellation, multi-frequency (MCMF) capabilities, where a single base station may have a baseline much farther than that of a traditional base station. To achieve this, the embodiment addresses atmospheric effect differences between the rover and the base station when the GNSS positioning of the mobile device (rover) is fixed, thereby allowing the determination of individual tropospheric delay errors at the base station. The embodiment can utilize additional satellite measurements that are not available without RTK correction, and can also use orbital clock correction for these additional satellite measurements.

The present application belongs to the technical field of surveying and mapping, and discloses a regional troposphere delay grid fast generation method and system. In the present application, a regional troposphere delay grid fast generation model adaptive to terrain and GNSS station network is constructed, which includes three modules of GNSS station feature extraction, target grid point feature extraction and GNSS station to grid point mapping; by introducing a graph attention network and a multi-head cross attention mechanism, the local spatial correlation of different regional station network distribution can be dynamically described, and the global change characteristics of the troposphere delay can be captured at the same time; by further fusing the station position and the terrain attribute through geographical space feature embedding, the feature consistency expression under the condition of terrain difference is realized. While maintaining the local spatial dependence modeling capability, the present application enhances the capturing capability of global feature correlation, realizes the adaptive modeling of different GNSS station network distribution and terrain change, and improves the spatial continuity and prediction accuracy of the troposphere delay.

The embodiment of the invention provides a zenith troposphere delay prediction method, a zenith troposphere delay prediction device and electronic equipment. The method comprises the following steps: acquiring multi-source heterogeneous data; performing alignment on the multi-source heterogeneous data to obtain global grid data; according to the global grid data, zenith statics delay ZHD and zenith wet delay ZWD are modeled to obtain a ZHD long-period prediction model and a ZWD short-time prediction model; according to the global grid data, constructing a correction model which changes along with the elevation in the vertical direction; and according to the ZHD long-period prediction model, the ZWD short-time prediction model and the correction model, performing ZTD prediction on a to-be-measured station. And the prediction accuracy of the ZTD is improved, so that support is provided for improving the stability and precision of GNSS positioning.

The invention discloses an unmanned aerial vehicle over-the-horizon air-ground cooperative emergency communication system in a complex environment, and relates to the technical field of emergency communication and unmanned aerial vehicles. In order to solve the problem of'information isolated island 'in a disaster'three-break' environment and the problem that traditional communication highly depends on sight distance or relay, the system comprises an unmanned aerial vehicle platform, a beyond-sight-distance scatter communication load carried on a three-axis servo holder, a ground base station module, an air-ground collaborative networking module and a heterogeneous network fusion module. The system establishes a non-relay beyond-the-horizon link by utilizing troposphere forward scattering; driving a holder to execute narrow beam real-time alignment compensation based on the positioning and attitude data; and the pose of the unmanned aerial vehicle is solved in combination with a multi-target cost function to balance communication and energy consumption. According to the method, the defects of wave beam lock losing and meteorological multipath fading caused by platform shaking are effectively overcome, high-reliability emergency networking crossing geographical obstacles is realized without a physical relay condition, and priority stable return of core rescue services is ensured.

The present invention comprises the deployment of a product known as RubisCO Climate Vaccine® or simply RCV which contains a specialised adapted culture of psychrophile algae and accelerators. This RCV is inoculated into targeted tropospheric clouds. The cumulatively large air-liquid optical interface area of clouds enables conditions for potential exponential photosynthetic algal growth and replication during which carbon dioxide is processed and oxygen released directly in the troposphere. Optimal inoculation sites are determined by altitude, humidity, temperature, weather patterns and predicted direction and duration of travel for precipitation, The biomass produced in this process is intended to be precipitated over mid-ocean where it is sequestered within natural ocean food chains or sedimented as detritus essentially permanently. This nature-based solution through repeated deployments offers a feasible scalable pathway toward potential climate change reversal within a decade with minimal or no adverse environmental impact.

The application relates to the meteorological detection technical field and provides a water vapor density determination method and device and a computer readable storage medium. The method comprises the following steps: obtaining target information of each observation device in a plurality of observation devices; the target information comprises first information and air pressure data of an air pressure sensor; determining troposphere delay of a GNSS chip according to the first information; determining zenith troposphere wet delay corresponding to the observation device according to the troposphere delay of the GNSS chip and the air pressure data; taking the product of the zenith troposphere delay and a troposphere wet delay projection function as ray path troposphere wet delay corresponding to the observation device; and determining water vapor density of a target area according to the ray path troposphere wet delay corresponding to the plurality of observation devices. Through the scheme, the cost of water vapor density determination can be reduced, and the accuracy of water vapor density determination can be improved.