754 results about "Mesh point" patented technology

The invention belongs to the field of data analysis, and discloses a data analysis method for engineering consultation digital intelligent management, which comprises the following steps: mapping multi-project heterogeneous data to a unified three-dimensional space-time grid through space-time grid division to form a grid mapping data set; detecting data format and attribute conflicts based on neighborhood correlation analysis, and distributing calibration data through dynamic weight; missing values and abnormal fluctuations are processed by using a time sequence autoregression model and a smoothing technology, and a complete data set with continuous time is constructed by combining linear interpolation and multi-dimensional data fusion; key indexes are extracted to construct a digital mirror image containing spatial positions, time sequences and attribute association, real-time data are synchronized, and outlier grid points are corrected; and multi-scene operation conditions are constructed based on the mirror image data, and a dynamic adjustment scheme is realized. According to the method, heterogeneous data are integrated through space-time grids, digital twinning and multi-scene simulation technologies are combined, and full-period management and risk intelligent decision-making of engineering data are achieved.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, are described for implementing a mission space platform. The platform is configured to identify radio frequency (RF) signals and analytics and generate a graphical interface with a map of a geographic area, where the map includes multiple grid points. For one or more RF signals: the platform determines a respective geolocation of an emitter that emits the RF signal and assigns the RF signal and its corresponding emitter to a grid point of the map based on the respective geolocation. Visual characteristics of grid points in the map are dynamically adjusted, in real time, base on new RF information about the area. The new RF information is provided as an output at the interface by displaying adjustments to the visual characteristics of the grid points.

The invention discloses a three-dimensional scene and object reconstruction method, system and device based on SDF and a Gaussian field, belongs to three-dimensional scene reconstruction in the technical field of computer vision, and aims to solve the technical problem that the three-dimensional scene reconstruction quality is not high due to the fact that geometric precision and rendering quality cannot be achieved at the same time in the three-dimensional reconstruction process in the prior art. The method comprises the following steps: initializing and updating a TSDF voxel volume by using a depth map and an RGB image to obtain a camera external parameter and a scene three-dimensional initial model; sDF prediction is carried out on the scene three-dimensional initial model through an SDF neural network, scene surface points are generated according to the light direction, and a high-precision scene geometric model is obtained; training the SDF neural network; performing grid division on a bounding box of the scene three-dimensional initial model, outputting an SDF predicted value of each grid point by using the trained SDF neural network, and extracting a refined scene grid model; and performing Gaussian rendering by using the high-precision scene geometric model to generate a final rendered image.

The invention relates to the technical field of computer information processing, and discloses a high-fidelity terrain surface interpolation method and system for large-scale point cloud data, and the method comprises the steps: carrying out the multi-level cleaning of original point cloud data, and generating a cleaned point cloud data set; performing adaptive tile grid division based on the cleaned data to generate a tile set covering the target area; in each tile, taking the to-be-interpolated grid point as a query point, constructing and optimizing a local Gaussian process model, and obtaining a real elevation predicted value of the query point; processing all query points in the tiles in parallel to obtain a tile elevation interpolation result set; performing weighted average on each tile result to generate a global seamless terrain surface; according to the method, the problems of poor expandability and surface discontinuity caused by local interpolation in large-scale point cloud data processing are effectively solved, and high-precision and high-fidelity terrain surface construction is realized.

The invention belongs to the field of electromagnetic particle simulation, and relates to a vacuum confluence region electromagnetic particle simulation method, system, equipment and medium, and the method comprises the following steps: S1, constructing a particle simulation domain of an electric field and a magnetic field of a vacuum confluence region, injecting particles into the particle simulation domain, and carrying out the regional decomposition of the particle simulation domain to obtain a plurality of sub-domains; s2, acquiring charge density and current density of grid points in each sub-domain; discretizing a Maxwell equation set into a form of a Cx = D equation, substituting the charge density and the current density of the grid points in each sub-domain into the Cx = D equation, and solving the Cx = D equation by adopting a GMRES algorithm to obtain potential and vector magnetic potential distribution in each sub-domain; s3, the electric field intensity and the magnetic induction intensity of the grid points in each sub-domain are solved, the electric field and the magnetic field borne by the particles are obtained, and therefore the positions of the particles in the next time step in each sub-domain are determined; and S4, updating the electric field and the magnetic field borne by the particles in each sub-domain in the next time step.

The invention discloses an off-network block sparse orthogonal matching pursuit underwater acoustic time delay Doppler domain channel estimation method, and belongs to the technical field of underwater acoustic channel estimation. The method solves the problems that a channel estimation method based on traditional orthogonal matching pursuit cannot estimate frequency shift parameters on non-grid points and is high in calculation complexity. According to the method, channel parameters of integer grid points are obtained based on a BOMP algorithm, and then residual Doppler factors on non-grid points are subjected to further fine estimation based on maximum likelihood criterion fitting. The problem that a traditional OMP channel estimation method in underwater OTFS communication can only estimate channel parameters on grid points is solved, and the estimation precision of channel frequency shift parameters is further improved by estimating frequency shift parameters on non-grid points; and meanwhile, a fractional order dictionary is prevented from being established in a channel parameter process, so that the system complexity is reduced to a certain extent. The method can be applied to underwater sound time delay Doppler domain channel estimation.

The invention relates to the technical field of atmospheric dust pollution prevention and environmental protection, and discloses a multi-objective optimization layout method for dust monitoring points of a bulk cargo port, which comprises the following steps: processing historical meteorological data and port geographic information, and calculating the comprehensive evaluation concentration of each candidate grid point in combination with a pollutant diffusion model; constructing a multi-target nonlinear mixed integer programming model taking maximization of environment sensitive point coverage and minimization of concentration interpolation deviation as target functions, wherein the model comprehensively considers multiple reality constraints; solving the model by adopting an improved genetic algorithm to obtain an optimal solution set capable of forming tradeoff among different targets; and carrying out quantitative evaluation on the solution set through preset monitoring area coverage rate and monitoring accuracy indexes, and determining an optimal monitoring point position layout scheme. According to the invention, a scientific and quantitative optimized layout scheme can be provided for bulk cargo port dust monitoring, and the reliability and spatial representativeness of a monitoring network are improved.

The invention relates to the technical field of hot-line work assessment, and discloses a hot-line work risk assessment method and system based on multi-source data, and the method comprises the steps: collecting equipment data, environment data and geological data, and carrying out the preprocessing; the method comprises the following steps: constructing a knowledge graph structure based on connection of electrified equipment, calculating link cost, analyzing node priority change to carry out dynamic shortest path calculation, optimizing risk propagation of abnormal points, calculating risk change of each grid point, and carrying out anomaly detection. According to the method, the physical and logic relations between the nodes are determined through the knowledge graph, multi-dimensional risk modeling and analysis are facilitated, the method can adapt to field data changes and reflect the newest risk distribution state through real-time monitoring and updating of node priority ranking, negative weight edges are supported through the Bellman-Ford algorithm, and the method has the advantages of being high in reliability and high in reliability. Possible negative influence factors in risk propagation can be effectively processed, the risk diffusion range and intensity of nodes can be accurately described through a Gaussian diffusion model, and the influence of the nodes on surrounding grid points is quantified.

The invention discloses a coal seam working face floor detection and analysis method, and relates to the technical field of detection and analysis. Potential change conditions of different positions and different elevations are observed through a parallel electrical method instrument, resistivity distribution conditions of different depths in a working face and a bottom plate of the working face can be obtained through three-dimensional electrical method inversion, and the resistivity distribution conditions provide technical support for objective and accurate geological interpretation. The hydrogeological condition of the working face floor rock stratum can be better understood, so that an important reference basis is provided for safe mining; the thermal effect and the electromagnetic effect existing in the environment are evaluated and corrected, so that the deviation of the measured conductivity value can be accurately corrected, and the accuracy and the reliability of conductivity measurement data are improved; and inputting the corrected conductivity value SR (xi, yi, zi) of each grid point into a three-dimensional model, and marking to construct a conductivity three-dimensional model, so as to visually display the electrical property distribution information of the underground medium.

The invention discloses a one-dimensional plasma simulation method based on deep learning optimization and related equipment, and the method comprises the steps: firstly constructing a one-dimensional basic model containing specific parameters, and then constructing and training a neural network of a multi-layer sensor (MLP) structure for predicting a potential function; then, a particle simulation method (DL-PIC) based on deep learning optimization is executed. Under the condition that 1000 grid points are included, compared with a traditional particle simulation method (PIC), the simulation time of the DL-PIC neural network is shortened by about 33.37%. According to the invention, complex physical phenomena such as reflection oscillation caused by heat effect and space charges can be effectively processed, and the method has good expansibility. The method is not only suitable for one-dimensional simulation, but also can be popularized to higher-dimension and electromagnetic particle simulation. Therefore, the invention provides an efficient and accurate solution for plasma simulation research, and can be widely applied to the technical field of plasma simulation.

The invention discloses an electromagnetic field simulation grid adaptive generation method based on a neural network. The method comprises the following steps: performing mesh generation on a semiconductor device simulation model to obtain original generation data, and constructing node features; an undirected graph is constructed, graph nodes of the undirected graph adopt node features of grid points, and connecting edges adopt Euclidean distances between the grid points and adjacent grid points; inputting the undirected graph into a double-branch neural network, and outputting a predicted node position; and correcting each node of the original subdivision data by using the predicted node position obtained by the double-branch neural network to form new subdivision data for electromagnetic field simulation. According to the method, physical field information can be fused to efficiently adjust the node density, and the geometric boundary and topological structure characteristics of the device can be strictly kept.

The invention relates to an earthwork balance calculation method, system and device and a storage medium, and relates to the technical field of earthwork balance design. The method comprises the steps of performing fusion processing on oblique photography data and laser radar point cloud data to generate a live-action three-dimensional model; performing grid division on the live-action three-dimensional model to obtain a grid model; based on the gridding model, defining a decision variable set including the design elevation of each grid point, the overall slope of the site, the slope height of each slope unit and the earthwork allocation amount, and constructing a comprehensive objective function including an earthwork balance objective, an economical objective and a safety objective; and under the engineering constraint condition, performing multi-objective optimization solution on the comprehensive objective function to obtain a Pareto optimal solution set, and selecting a final implementation scheme from the Pareto optimal solution set. According to the method, the problem of topographic data missing of the dense vegetation region is effectively solved, the limitation of traditional single-target optimization is broken through, and the maximization of comprehensive benefits is realized.

The invention relates to the technical field of 5G communication, in particular to a 5G network signal low-altitude coverage test method and system, and the method comprises the steps: obtaining regional geographic information and base station layout information; based on geographic information and base station layout, constructing a three-dimensional digital map, dividing a dynamic test grid, and determining an initial flight path; according to a multi-source sensor of the unmanned aerial vehicle, in combination with the initial flight path, collecting 5G signal parameters and environmental data of the grid points through a preset frequency; a wavelet transform filtering algorithm is adopted for calibration, abnormal values are removed, and feature vectors are generated; according to the feature vectors, a coverage evaluation model is constructed in combination with a three-dimensional digital map, and a low-altitude coverage blind area and an interference type are identified; and if a low-altitude coverage blind area or abnormal interference is detected, dynamically adjusting the flight path of the unmanned aerial vehicle through an A-star algorithm, testing a target area, and generating a coverage optimization scheme based on a test result. Therefore, the problems of low test efficiency, lagging data processing and analysis and the like in the prior art are solved.

The invention discloses a frozen soil roadbed hot melt settlement laser scanning measurement method and system, and relates to the technical field of measurement, the method comprises the following steps: obtaining gridding surface data, and obtaining an elevation data sequence of each grid point; acquiring an elevation change index of each grid point according to the elevation data sequence of each grid point; acquiring a plurality of grid points adjacent to the ith grid point and taking the plurality of grid points as a plurality of reference grid points of the ith grid point, acquiring each relative difference quantity of the ith grid point, and acquiring a correction proportion of the ith grid point according to the plurality of relative difference quantities of the ith grid point; and obtaining target elevation data of each grid point according to the correction proportion of each grid point and the measured elevation data at the current moment, and forming a measurement result including the gridding surface data according to the target elevation data of each grid point. The method has the advantages of identifying abnormal values, dynamically correcting measurement and improving data reliability.

The invention provides an evolution tracking method and device for a composite material ablation morphology interface. The method comprises an initialization step, an ablation rate calculation step, a grid point coordinate calculation step, a morphology reconstruction step, a burning tip judgment step, an enhancement body grid updating step and an evolution tracking and output step. The invention provides an evolution tracking mode of a composite material ablation morphology interface based on a Lagrangian method, and the method is combined with the ablation regression of a virtual top end surface and the strategy cooperative application of reinforcement burning tip judgment, thereby greatly reducing the judgment and reconstruction difficulty of non-physical distortion in an interface grid evolution process. According to the method, the problems of grid distortion and distortion possibly occurring under the ablation deformation condition are solved, the method has the advantages of being high in morphology interface tracking accuracy and easy in simulation tracking strategy implementation, meanwhile, the overall grid calculation amount of the scheme is small, and the calculation efficiency is improved.

The invention provides a high-resolution emission flux inversion system and method. The method comprises the following steps: collecting atmosphere multi-source data; determining a distance weighting function, and calculating the correlation between the grid points in the simulation area and the observation value; generating a set sample meeting physical constraints of the assimilation object; performing singular value decomposition and dimension reduction on the set samples; replacing a tangent line and an adjoint mode of a regional air quality mode with a mixed assimilation method, and obtaining a simulated regional space grid point analysis increment; obtaining corrected concentration and flux distribution data; the data is used for carrying out emission flux inversion, and the unit time emission flux of different positions is estimated. According to the method, a traditional four-dimensional variation mode is replaced with a mixed assimilation method, and the calculation and programming difficulty is reduced; generating a set sample by using a four-dimensional sliding sampling algorithm, reducing dimensions, and calculating resource consumption; a joint assimilation algorithm is introduced to optimize the concentration and flux field, and accurate inversion of the high-temporal-spatial-resolution emission flux is achieved.

The invention provides a dynamic geologic model updating and predicting method based on tunnel face information, which constructs and dynamically updates a geologic model by combining face grid point data acquired in a tunneling process and adopting Kriging interpolation and variation function fitting technologies. The method comprises the steps of collecting tunnel face data, cleaning standard data, and extracting a starting end face and a terminating end face of a tunnel; generating an initial geologic model by using the three-dimensional variation function model and Kriging interpolation; newly added tunnel face data are integrated, model parameters are dynamically adjusted, and geological distribution is updated; and finally, displaying the dynamically updated geologic model through a three-dimensional visualization technology. The problem that a traditional static model is difficult to adapt to dynamic changes of geological conditions in the tunneling process is solved, the geological model can be optimized in real time, accurate and reliable geological information support is provided for tunnel construction, and construction efficiency and safety are remarkably improved.

The invention relates to a complex medium inversion imaging method and system guided by a physical information neural network, and the method comprises the steps: constructing a two-dimensional grid model of a block structure with different medium distributions, obtaining out-of-plane displacement data at grid points through staggered grid finite difference, and forming a wave field full-waveform data set; constructing a physical information neural network, wherein the physical information neural network comprises a first feed-forward network for modeling a mapping relation of a displacement field of the sample, a second feed-forward network for modeling a velocity field of the sample, and a residual network; based on the wave field full-waveform data set, training a physical information neural network by taking minimization of compound loss as a target; and taking the space-time coordinates of the sample as input, and utilizing the trained physical information neural network to obtain predicted displacement and sound velocity of the corresponding position of the space-time coordinates, so as to realize inversion imaging of sound velocity medium distribution. According to the method, the ultrasonic propagation model of the complex medium can be quickly and accurately established under the condition that a small amount of marked data is used.

The invention discloses a computational fluid mechanics-oriented parallel boundary layer grid generation method and device. The method comprises the following steps of: firstly, generating an initial background grid with boundary layer units according to an original CAD (Computer Aided Design) geometric model; then, according to the initial background grid and the topological connection relation thereof, obtaining an object plane boundary of the background grid and grid units connected with the object plane boundary so as to construct a fixed closed area; performing regional decomposition on the initial background grid by using a graph division tool; secondly, encrypting curved surface grids of the sub-regions; carrying out parallel calculation on normal vectors of curved surface grid points and a stratified progress long distance according to the boundary layer unit, and generating a triangular prism unit by applying a stratified progress method; and finally, carrying out quality detection and intersection judgment on all boundary layer units to obtain a complete boundary layer grid. According to the method, the defect of lack of a boundary layer grid parallel generation method in large-scale grid generation can be overcome, rapid parallel generation of large-scale boundary layer grids is realized, and the performance bottleneck in the aspect of generation efficiency is overcome.

The invention provides a curved surface grid generation method based on discrete grid parameterization, and belongs to the technical field of computer aided engineering (CAE) and computational geometry. Aiming at the problems of tedious geometric operation, parameter space fusion distortion, insufficient grid fitness and the like in grid subdivision of a complex curved surface formed by a plurality of sub-curved surfaces, the invention provides the following technical scheme: firstly, carrying out triangular grid pre-subdivision on an original curved surface, and constructing a virtual topological structure for inhibiting non-key features; the discrete grids are mapped to a low-distortion two-dimensional parameter space by adopting least square conformal mapping (LSCM), and seamless combination of multiple sub-surface parameter domains is realized; dynamically calculating a parameter space size field, and controlling grid density distribution; after a parameter space adaptive grid is generated through Delaunay triangulation, grid points are accurately attached to an original geometric surface by using a dual projection correction mechanism. According to the method, complex CAD geometric operation is avoided, the automation degree is remarkably improved, meanwhile, physical space grid uniformity and strict fitness are guaranteed, and the method is suitable for efficient and high-precision grid generation of complex curved surfaces in the fields of aerospace, automobiles, ships and the like.

The invention discloses a finite difference seismic travel time calculation method based on Fibonacci heap sorting, and the method comprises the following steps: S1, reading parameters and a speed model, and reading related parameters and the speed model in a file; s2, a seismic source and a narrow band are initialized; s3, selecting and arranging a Fibonacci pile; s4, selecting a travel time minimum point in the narrow band; s5, judging attributes of adjacent points; s6, judging whether the narrow band is empty or not; and S7, outputting first-motion wave travel time, performing circulation until a narrow band is empty so as to complete travel time calculation of all grid nodes, and outputting a final travel time calculation result. According to the finite difference seismic wave travel time calculation method based on the Fibonacci heap sorting, the minimum travel time point in the narrow band is screened by adopting the Fibonacci heap sorting, so that the finite difference seismic wave travel time is calculated. The efficiency of grid point travel time calculation is improved, and the finite difference seismic travel time calculation method based on Fibonacci heap sorting is realized.

The invention relates to the field of aviation safety, and provides a flight bumping area prediction method and system based on air-ground data fusion, and the method comprises the steps: obtaining a measurement area, and obtaining a barometric altitude through meteorological data; acquiring air detection data of the measurement aircraft so as to calculate a horizontal airspeed component; checking according to the horizontal airspeed component and the ground speed component to obtain a high-altitude wind speed component; generating an airborne data matrix, calculating the distance between a measurement point in the airborne data matrix and a grid point in a measurement area to obtain a latitude and longitude distance, and performing weight accumulation to obtain a grid point wind speed; wind field deformation is calculated, a jolting index is calculated according to the wind field deformation and normalized, a normalized jolting index is obtained, and a comprehensive jolting index is obtained through the normalized jolting index; and obtaining a target jolting index according to the ground measurement jolting index and the comprehensive jolting index to realize jolting prediction. According to the invention, accurate flight bumping prediction can be realized.

The invention discloses a thin-wall structure layered body grid generation method based on surface grid alignment, which comprises the following steps of: reading an integral surface grid with a thin-wall structure characteristic and a mapping relation, and pairing a source surface grid and a target surface grid in the integral surface grid according to the mapping relation; aligning the source surface grid and the target surface grid which are paired, updating the target surface grid, and extracting triangular mapping information of an aligned region; according to the mapping information, advancing a source surface grid to a target surface grid layer by layer to obtain a layered body grid; extracting the outer surface of the stratified body mesh, combining the outer surface of the stratified body mesh with the overall surface mesh to obtain a combined surface mesh, and performing mesh point classification; normalizing the unit normal direction of the combined surface grid, calculating the normal direction at grid points needing to be propelled according to the grid point classification, and interpolating points according to distances in the normal direction to form a constraint point set; and generating a cavity area body grid by taking the constraint point set and the combined surface grid as constraints, and combining the cavity area body grid with the layered body grid to obtain the layered body grid of the overall thin-wall structure.

The present invention discloses an unified multiple access (MA) based system for uplink transmission of data by multiple users. The system comprises an user interface integrated transmitter modules for transmitting the data from multiple user transmitters over waveforms through a cooperative unified data grid structure including grid points, said unified data grid structure including each user transmitter allocation of a few non-overlapping grid points for loading respective data bearing symbols, with zeros loaded onto unallocated grid points. The user transmitter is configured to transmit a sparsely loaded grid resembling to the unified two-dimensional data grid structure involving data-bearing Quadrature Amplitude Modulation (QAM), where a part of available grid points of the grid as allocated is loaded with QAM symbols and remaining grid points are loaded with zero symbols. A waveform modulator corresponding to user transmitter is also provided in the present system for waveform modulation of said sparsely loaded grid as per the waveforms enabling transmission for multi-antenna reception of the waveforms to a base station or an access point.

The invention discloses a GNSS (Global Navigation Satellite System) nonlinear deformation correction method based on a full-spectrum three-dimensional thermoelastic model. The GNSS nonlinear deformation correction method comprises the following steps: carrying out discrete Fourier decomposition on a temperature time sequence of each grid point; carrying out space spherical harmonic expansion and coefficient projection on each decomposed frequency; based on a space spherical harmonic expansion and coefficient projection result, considering the periodicity of the temperature, and performing sine / cosine representation of a frequency-by-frequency temperature item; performing spherical harmonic representation and time expansion on the deformed displacement field corresponding to the periodic temperature based on the spatial spherical harmonic expansion and coefficient projection result; solving a deformation equation in spherical coordinates in a Love number form to obtain an expression of a complex Love number; based on the complex spherical harmonic coefficient and the complex Love number of the temperature, full-spectrum synthesis of three-component displacement at the spherical surface is carried out; and performing internal consistency and external dispersion verification based on a full-spectrum synthesis result.

The invention discloses an ultra-large anchorage digital twinborn body construction method and system, and the method comprises the following steps: arranging 16-hole inclinometer tubes to form a three-dimensional monitoring array, collecting data in real time through the inclinometer tubes, and generating accurate grid point data through an IDW interpolation algorithm; carrying out optimization processing on the digital model, wherein the optimization processing comprises structure optimization, efficient compression algorithm application and instantiation rendering; three-dimensional visualization is achieved based on the WebGL technology, and the three-dimensional visualization comprises model translucency, grid data accurate alignment, thermodynamic diagram rendering achieved through a custom shader and the like; a comprehensive digital twin system platform is constructed, and full-life-cycle management and real-time monitoring of the super-large anchorage structure are achieved. According to the invention, by arranging a sensor acquisition and real-time monitoring mode, the precision and comprehensiveness of data acquisition are remarkably improved, real-time monitoring of overall deformation of the anchorage is realized, high-precision, real-time and interactive digital twinborn visualization of the super-large anchorage structure is realized, and powerful support is provided for engineering monitoring and decision making.

The invention discloses a pressure vessel lower chamber model order reduction method combining sparse grids and POD, and the method comprises the steps: adding one to the grade of the sparse grids after iteration initialization, and obtaining test grid points according to important grid points; executing the lower chamber full-order computational fluid mechanics model corresponding to the test grid points to obtain a first snapshot; reconstructing a second snapshot by using the mapping relation and the POD modal matrix; calculating a root-mean-square error of the two snapshots, and if the root-mean-square error is smaller than a threshold value, completing construction of a reduced-order model Otherwise, the grid points with the errors meeting the requirements are stored in a non-important grid point set, the grid points which do not meet the requirements are marked as important grid points, and the snapshot matrix is updated. Performing singular value decomposition on the snapshot matrix, updating the mapping relation, judging whether the maximum sparse grid grade is reached or not, and continuing iteration if the maximum sparse grid grade is not reached. According to the method, the field distribution of the thermal hydraulic parameters in the lower chamber can be quickly obtained through matrix algebraic operation, and the method can be used for application scenes such as parameterization analysis, design optimization and digital twinning.

The invention discloses a multi-satellite direct positioning method based on CUDA (Compute Unified Device Architecture) parallel calculation, relates to the field of space-based electromagnetic signal positioning, and aims to be suitable for large-range and high-precision positioning of low-signal-to-noise-ratio signals. According to the technical key points, a positioning area is determined in a satellite coverage range according to prior information, and grid points are divided on the surface of the earth; two or more satellites with time-frequency synchronization obtain observed quantities of signals emitted by the same ground radiation source, a first signal model of the multiple observed quantities is constructed, and down-conversion is carried out on the first signal to obtain a second signal; constructing a cost function by using signal characteristics (such as time difference of arrival, frequency difference of arrival and the like) in a radiation source signal received by a satellite; a cost function corresponding to each grid point is subjected to multi-core parallel computing through the GPU; and summarizing results, and searching the maximum value of the cost function to determine the estimated position of the ground radiation source. According to the multi-satellite direct positioning method based on the CUDA, the characteristic that parallel calculation can be carried out when cost function grid searching optimization is carried out in direct positioning is utilized, calculation is directly carried out on satellites, satellite-ground data transmission is omitted, the positioning time is shortened by utilizing the independence of searching calculation among grids, and the real-time performance of a positioning system is guaranteed.

A method includes obtaining images of an environment captured by imaging sensors associated with a passthrough AR device and position data and depth data associated with the images. The method also includes generating a point cloud representative of the environment based on the images, position data, and depth data. The method further includes generating a mesh for a specified image. The mesh includes grid points at intersections of mesh lines. The method also includes determining one or more depths of one or more grid points of the mesh. The method further includes transforming the mesh from a viewpoint of a specified imaging sensor that captured the specified image to a user viewpoint of the passthrough AR device based on the depth(s) of the grid point(s). In addition, the method includes rendering a virtual view of the specified image for presentation by the passthrough AR device based on the transformed mesh.

The invention discloses an aircraft simulation method, device and equipment based on parallel block sparse matrix incomplete LU decomposition and a medium, and relates to the technical field of simulation, and the method comprises the steps: building a block sparse matrix comprising a plurality of zero sub-blocks and non-zero sub-blocks based on the topological relation of each grid point in an aircraft grid and simulation physical parameters, determining dependency pairs respectively corresponding to a plurality of non-zero sub-blocks from the non-zero sub-blocks, and storing the dependency pairs by adopting a preset data structure; wherein the dependent pair comprises a pair of matched non-zero sub-blocks; respectively distributing the plurality of non-zero sub-blocks to a plurality of GPU thread bundles for parallel processing so as to update the corresponding non-zero sub-blocks based on the updated dependency pairs after the GPU thread bundles complete updating on the dependency pairs corresponding to the corresponding non-zero sub-blocks; and after the plurality of non-zero sub-blocks are updated, updating the block sparse matrix based on the plurality of updated non-zero sub-blocks, and determining an incomplete LU decomposition result according to the updated block sparse matrix so as to perform aircraft simulation.