543 results about "Topographic model" patented technology

A control method and system for precise landing of an unmanned aerial vehicle. The method comprises the following steps: on the basis of a multi-sensor fusion technique, using a lidar and a stereo vision algorithm to collect environmental data and perform primary processing, and generating comprehensive environmental perception data (step S1); on the basis of the comprehensive environmental perception data, using a digital elevation model algorithm to re-construct a three-dimensional terrain of a landing area, and generating a three-dimensional terrain model (step S2); on the basis of the three-dimensional terrain model, using an A* search path-planning algorithm to perform risk assessment and plan a safe landing path, and generating an optimized landing path (step S3); on the basis of the optimized landing path, using an adaptive control algorithm to adjust a flight attitude in real time by means of a fuzzy logic controller, and generating flight parameter adjustment (step S4); on the basis of the flight parameter adjustment, using machine vision and a decision tree algorithm to execute autonomous obstacle avoidance and emergency response, and generating a safe landing execution scheme (step S5); and on the basis of the safe landing execution scheme, using an ultrasonic sensor and a ground feedback system to confirm and fine-adjust a landing point, and completing final landing confirmation (step S6).

The invention discloses a dangerous rock falling motion feature prediction method based on multi-source data fusion, and belongs to the technical field of engineering geology. Comprising the steps of collecting dangerous rock multi-source data to construct a basic information base; processing dangerous rock multi-source data based on a CNN algorithm, identifying a dangerous rock contour and calculating geometric features; the dangerous rock multi-source data is processed through multiple algorithms, and the terrain is reconstructed to generate a digital elevation and terrain model; analyzing a vibration signal frequency spectrum, quantifying dangerous rock multi-source data features and determining a fusion weight; fusing the multi-source data of the dangerous rock to construct a three-dimensional real scene model and construct a physical and mechanical model; establishing a historical database, selecting a machine learning algorithm to construct a data driving model, and adopting an optimization algorithm to predict a rockfall movement track and state; and determining a two-dimensional simulation key section, establishing a two-dimensional numerical model, and dynamically simulating and calculating rockfall movement and rock-soil body response. According to the scheme, the defects in the aspects of dangerous rock falling motion feature prediction and protection design in the prior art are overcome, and the prediction accuracy and efficiency are improved.

The invention provides a multi-construction-method collaborative dust fall intelligent control method based on deep learning. The method comprises the following steps: collecting mine field data of a mine field in real time; wherein the mine field data comprises mine field environment data, equipment operation data and topographic data; constructing a digital mine field model based on the mine field data; wherein the digital mine field model comprises a terrain model, an equipment model and a dust generation and diffusion model; based on the mine field data and the digital mine field model, constructing a reinforcement learning agent; based on the reinforcement learning agent, performing dust fall control on the mine field; the dust fall control is monitored on the basis of the pre-created human-computer interaction interface, intelligent and efficient control over the mine field dust fall process is achieved, the dust fall effect and the resource utilization efficiency are improved, and meanwhile the flexibility and reliability of the system are improved through human-computer cooperative control.

The invention discloses a VR-based unmanned aerial vehicle inspection method and system, a storage medium and a program product, and the method comprises the steps: calculating a low-polygon terrain model, and carrying out the subdivision smoothing processing, and obtaining a three-dimensional terrain image; matching and registering the panoramic image sequence and the three-dimensional topographic image to obtain a point cloud map; generating a virtual mining area environment map; calculating image quality parameters; when the image quality parameter is lower than a preset threshold value, generating a semi-real and semi-virtual fusion display picture; transmitting the semi-real and semi-virtual fusion display picture to a VR helmet for display, and synchronizing the attitude information of the unmanned aerial vehicle to the VR helmet; when it is determined that a fatigue feature appears according to the brain wave data, the unmanned aerial vehicle is controlled to be switched to a preset autonomous flight mode; constructing a virtual anti-collision boundary; and obtaining an optimized flight path according to the virtual anti-collision boundary, and controlling the unmanned aerial vehicle to inspect according to the optimized flight path. The continuity and reliability of the inspection task are improved, and the safety risk of the inspection task is reduced.

The invention belongs to the technical field of topographic mapping, and discloses a topographic mapping system and method based on an unmanned aerial vehicle, and the method comprises the steps: a data collection module collects map geological data; the route planning module plans an optimal driving route; the data acquisition module acquires topographic images and point cloud data; the environment parameter monitoring module monitors flight environment parameters in real time; the image data analysis module is used for preprocessing and analyzing the image data; the radar data analysis module preprocesses and analyzes the radar data; the feature extraction and matching module performs feature extraction and matching on the image and the point cloud data; the terrain model construction module constructs a terrain three-dimensional model; and the terrain analysis module performs quantitative analysis on the terrain. According to the method, key feature extraction is performed on images and point cloud data, and image splicing and point cloud registration are realized; the terrain model construction module constructs a three-dimensional terrain model according to feature extraction and matching results, and the terrain analysis module obtains accurate terrain information.

The invention relates to a terrain real scene modeling method, device and equipment and a storage medium thereof. According to the method, multi-source heterogeneous data related to the terrain in a target area is integrated, a multi-modal data cube is generated through noise filtering and data fusion under a unified coordinate system, then a data cavity area is identified based on density clustering and elevation gradient analysis, and geophysical features are extracted. Innovatively constructing a neural implicit inference model fused with physical constraints to perform joint modeling on the earth surface and underground structures, and finally converting implicit terrain representation into an explicit three-dimensional terrain model; seamless fusion modeling of the earth surface and the underground space under the complex shielding environment is achieved, the physical rationality of the model and the hidden area reconstruction precision are remarkably improved, meanwhile, it is ensured that the generated model strictly conforms to the geological physical law, and the geological engineering safety and the planning reliability are effectively guaranteed.

The invention relates to the technical field of image data processing, in particular to a difficult mountainous area slope three-dimensional modeling method and system based on a remote sensing technology. The method comprises the following steps: obtaining an original remote sensing data set of a target hard mountain area, and carrying out data preprocessing to obtain a standardized remote sensing data set; performing target hard mountainous area surface feature extraction on the standardized remote sensing data set to obtain hard mountainous area surface feature data; constructing a three-dimensional terrain model by using the earth surface feature data of the hard mountain area to obtain preliminary three-dimensional terrain model data; and performing time sequence analysis on the standardized remote sensing data set, and performing slope dynamic change analysis on the initial three-dimensional terrain model data by using a time sequence analysis result to obtain slope displacement change data. Through three-dimensional modeling, dynamic change analysis, stability evaluation and landslide early warning, a set of complete disaster prevention and reduction system for the hard mountainous area is constructed, and the prediction and prevention capability for landslide disasters is effectively improved.

The invention discloses a high-precision topographic mapping system and method based on multi-source remote sensing data, and relates to the technical field of topographic mapping, and the method comprises the steps: obtaining an optical remote sensing image, a radar remote sensing image, LiDAR point cloud data and meteorological index data of a target region, and carrying out the data preprocessing of the optical remote sensing image, the radar remote sensing image and the LiDAR point cloud data; obtaining the surface feature types of the target area and the coverage area of each surface feature type, and carrying out the weighted fusion of the optical remote sensing image and the radar remote sensing image of the target area according to the surface feature types of the target area and the coverage area of each surface feature type, and obtaining a self-adaptive fusion remote sensing image; according to the method, points in LiDAR point cloud data are divided into distinguished ground points and non-ground points, a digital elevation model is constructed according to the ground points in the LiDAR point cloud data, three-dimensional modeling of the terrain is performed on the basis of the digital elevation model in combination with texture information of a self-adaptive fusion remote sensing image, a three-dimensional terrain model is generated, and the terrain surveying and mapping precision is remarkably improved.

The invention provides a high-precision topographic mapping and three-dimensional modeling system based on an unmanned aerial vehicle, and the system comprises an unmanned aerial vehicle cooperation module which is used for deploying a multi-source sensor and a sensor electronic interface on the unmanned aerial vehicle, and building a distributed network of the unmanned aerial vehicle; the real-time dynamic positioning module is used for acquiring unmanned aerial vehicle positioning data and an initial target terrain map; the autonomous control module is used for generating a flight path, performing dynamic adjustment, constructing an autonomous flight control model and outputting a flight control instruction; the data quality enhancement module is used for performing parameter adjustment on the real-time data and performing space and signal level combined processing on the real-time data so as to enhance the data quality; and the terrain model optimization module is used for processing the laser radar point cloud data so as to construct a three-dimensional terrain model post-processing module, and carrying out data visual display and flight suggestion generation. According to the method, the positioning and modeling precision is greatly improved, efficient surveying and mapping are achieved, the single-point fault risk is reduced, and it is guaranteed that tasks can be completed in a high-safety, high-precision and intelligent mode.

The invention provides a full-coverage cleaning modular control method and system for a photovoltaic cleaning robot. According to the method, a photovoltaic panel three-dimensional terrain model is constructed by collecting laser ranging, photovoltaic panel surface temperature distribution, environment airflow and position relation data; and generating an obstacle distribution map based on the model, and dynamically analyzing gap width and attachment height parameters of the cleaning area. Therefore, the bending angle and the telescopic amplitude of a connecting part of the cleaning module are adjusted in real time, and robot pose information is synchronously updated. And in combination with the position data, the obstacle map and the pose of the whole robot, an uncleaned area identifier and a dynamic coverage path are generated, and information is shared through a wireless network. The system dynamically distributes working areas and advancing directions of the multiple robots, and efficient cooperative full-coverage cleaning of the photovoltaic array is achieved. According to the technical scheme provided by the invention, through multi-source environment perception and dynamic pose adjustment, intelligent path cooperation and full-coverage operation of multiple cleaning robots are realized.

The invention provides a dynamic change monitoring method and system based on a multi-temporal river channel image, and relates to the technical field of image monitoring, and the method comprises the steps: obtaining a multi-temporal multispectral remote sensing image and an unmanned plane oblique photogrammetry image; identifying a riverway water body boundary and constructing a water area mask; dense point cloud data are generated and cut; generating a balanced riverbed point cloud through density compensation sampling and local curvature constraint; constructing a terrain model to generate a section sequence; calculating hydrodynamic correlation strength to construct an evolution propagation sequence; and recursively calculating the erosion and deposition change rate and performing early warning. According to the invention, high-precision monitoring and early warning of river form changes are realized.

The invention discloses a side slope stability intelligent monitoring and supporting optimization method based on digital twinning, which comprises the following steps: extracting gradient, curvature and geological layering characteristics from a holographic terrain model, calculating a preliminary change trend of stress distribution of a rock-soil body in combination with a finite element analysis method, and determining spatial position distribution of a potential sliding surface of a side slope; according to the space coordinate set of the real-time monitoring point position, the data acquisition frequency of the sensor is adjusted through a time sequence analysis method, and a high-frequency monitoring data set reflecting dynamic changes of stress and underground water is obtained; extracting stress peak values and underground water level fluctuation characteristics from the high-frequency monitoring data set, and generating a multi-dimensional information matrix containing terrain, stress and water dynamics by combining spatial characteristics of the holographic terrain model and adopting a data fusion algorithm; according to the state parameters of the digital twinborn body, if it is judged that the stress distribution exceeds a preset threshold value, the stress distribution of the supporting structure is recalculated through finite element analysis, and an adjusted slope supporting design scheme is obtained.

The invention provides a three-dimensional visual model construction method and system for a mine slope, and relates to the technical field of data processing, and the method comprises the steps: obtaining the inclined image data of the mine slope; performing error correction on the inclined image data; performing live-action modeling according to the inclined image data after error correction to obtain a three-dimensional grid model and a point cloud data file; generating a digital terrain model according to the point cloud data file; extracting a contour line of the digital terrain model, and exporting a contour line file; generating a three-dimensional terrain curved surface by using a terrain data generator according to the contour line file; the three-dimensional terrain curved surface extends downwards by a preset depth, and a three-dimensional entity slope model is generated; physical parameters of side slope rock soil are set, and a Moire-Coulomb intensity criterion is given to the three-dimensional entity side slope model so as to simulate shear failure characteristics of the rock soil; on the basis of shear failure characteristics of rock and soil, grid division is carried out on the three-dimensional solid slope model; and generating a three-dimensional visual model of the mine slope.

The invention discloses a wharf shoreline terrain reconstruction method based on remote sensing data, and belongs to the technical field of three-dimensional terrain reconstruction. The method comprises the following steps: acquiring a multi-temporal multispectral remote sensing image, a synthetic aperture radar image, a laser radar point cloud and synchronous tidal water level data of a target wharf area; processing the multispectral image to generate an initial land and water segmentation map; carrying out tide correction by utilizing the tide water level data, fusing the multi-polarization characteristics of the synthetic aperture radar image, and correcting the ground feature type to obtain an accurate land and water boundary diagram; processing the laser radar point cloud to generate a digital surface model, extracting a shoreline contour with sub-pixel-level precision from the digital surface model, and endowing the shoreline contour with an elevation value; and superposing the shoreline contour with the elevation with the multispectral image to generate a three-dimensional terrain model. According to the method, the problems of low terrain reconstruction precision, large tide influence and insufficient automation degree of a traditional method in a complex wharf environment are solved, and high-precision and high-efficiency wharf shoreline three-dimensional automatic reconstruction is realized.

The invention relates to the technical field of freeze-thaw mud flow simulation, in particular to a freeze-thaw mud flow chain disaster power simulation method and system. The method comprises the following steps: obtaining regional topographic measurement data and carrying out point cloud conversion and three-dimensional modeling, generating a digital topographic model, collecting regional meteorological data and extracting features, carrying out multi-source fusion with the digital topographic model, forming a data fusion model, and based on the model, identifying freeze-thaw critical conditions and positioning freeze-thaw susceptible regions. The method comprises the following steps: carrying out geological structure calculation and stability analysis on a susceptible area, generating mud flow risk data, carrying out dynamic change simulation by utilizing the risk data, obtaining a simulated mud flow node and generating a disaster formation track, carrying out disaster risk assessment on the disaster formation track, and carrying out emergency early warning processing based on an assessment result to generate corresponding early warning data. According to the invention, a more accurate freeze-thaw mud flow chain type disaster-forming power simulation method is realized.

The invention relates to the technical field of geophysical exploration, in particular to an exploration surveying and mapping method based on remote sensing and a surveying and mapping instrument thereof. The exploration surveying and mapping method based on remote sensing comprises the following steps: step 1, multi-platform collaborative data dynamic acquisition; step 2, multi-modal data fusion and feature enhancement: vegetation noise filtering is performed on the laser radar point cloud data, and a surface terrain model under vegetation coverage is reconstructed; seismic wave speed data and ground penetrating radar dielectric constant data are combined to construct an underground medium physical property combined distribution model; associating the reflectivity characteristics of the multispectral image with the underground physical property parameters, and identifying a geological abnormal region; and step 3, hidden geologic body dynamic modeling and risk assessment. By means of the method, real-time monitoring and risk assessment of the complex geologic body can be achieved, and the geological disaster prediction and prevention and control capacity is greatly improved.

The invention relates to the technical field of intelligent forestry management, and particularly discloses a forest farm intelligent comprehensive management and control system, which comprises a space-air-ground collaborative sensing module, a fire danger dynamic modeling module and an intelligent decision execution module. The method comprises the following steps: acquiring temperature field data through multispectral satellite remote sensing, constructing a high-precision terrain model through a laser radar, extracting vegetation features through hyperspectral imaging, extracting a thermal anomaly structure by adopting topological continuous coherence analysis and a Morse-Smal complex method, and establishing an adaptive fire danger model in combination with a quantum annealing optimizer. The system can generate a fire danger thermodynamic diagram in real time and divide risk levels, and drives the unmanned aerial vehicle to perform priority patrol and obstacle avoidance path planning. The problems of difficulty in pseudo hot area identification, low fire danger prediction precision, non-intelligent path planning and the like in a complex environment are solved, and the intelligent level of forest farm fire prevention and control is improved.

The invention relates to the technical field of ocean engineering surveying and mapping, and particularly provides an ocean engineering surveying and mapping terrain correction method based on multi-beam sounding. The method comprises the following steps: constructing a tremor-sound velocity coupling model through multi-source data synchronous acquisition, and generating a sound velocity dynamic correction term; fusing the static sound velocity profile, the internal wave disturbance term and the sound velocity correction term, and establishing a time-shifting sound velocity field of spatio-temporal evolution; realizing dynamic space homing calculation through a double-shaft decoupling rotation matrix based on a hull attitude and a time shifting sound velocity field; tunnel effect noise is suppressed by adopting an airspace adaptive filtering technology; the terrain deformation rate is calculated in combination with continuous cycle data, and a deformation threshold value is dynamically set through soil mechanical parameters to trigger graded safety early warning; and outputting the high-precision three-dimensional terrain model without the sound velocity error and the noise interference. According to the method, the problems of geological activity interference compensation deficiency, tunnel effect noise suppression insufficiency, large dynamic environment homing error and the like in traditional surveying and mapping are solved, and the reliability of complex sea area topographic survey is remarkably improved.

The invention discloses an intelligent method and system for multi-source heterogeneous data fusion management, and belongs to the field of data processing, and the intelligent method for multi-source heterogeneous data fusion management comprises the following steps: deploying a sensor network in a historical ponding area based on historical ponding point data and urban hydrological geographic information, acquiring real-time monitoring data, wherein the real-time monitoring data comprises rainfall intensity, road waterlogging depth, community waterlogging condition and drainage pipe network water level / flow; compared with the prior art, the method has the beneficial effects that sensors are arranged in the historical ponding area to obtain real-time monitoring data, and weather forecast, a terrain model and a pipe network model are combined to construct a waterlogging prediction model to predict whether a ponding risk exists in the historical ponding area in future set time (such as 0.5-3 hours in the future); the ponding risk is treated in advance, so that the problems of traffic interruption caused by ponding, citizen travel obstruction and the like are solved.

A method, system, medium and program product for measuring a volume based on elevation measurement, the method comprising: determining historical topographic feature data; elevation values of all positions in the mining area in different time periods are extracted; calculating a topographic relief change rule according to the elevation value, and establishing a topographic evolution model according to the topographic relief change rule; extracting terrain boundary feature points and ponding area contour lines from the unmanned aerial vehicle inclined image data; dividing a plurality of local terrain units according to the terrain boundary feature points, and calculating an elevation difference to obtain a gradient change coefficient; determining a terrain prediction model of each local terrain unit; splicing and reconstructing the terrain prediction model of each local terrain unit to obtain underwater terrain estimation data of the ponding area; constructing a mining area terrain model according to the underwater terrain estimation data and the terrain data; and calculating the earthwork excavation volume in the mining area according to the mining area terrain model. According to the invention, the accuracy of mining volume measurement is improved.

The invention discloses a power distribution network intelligent planning method, system and device and a storage medium, and the method comprises the steps: obtaining point cloud data, carrying out the topographic feature information extraction of the point cloud data, and obtaining a topographic data set; acquiring remote sensing data, and performing earth surface change information extraction on the remote sensing data to obtain an earth surface change data set; fusing the topographic data set and the surface change data set to obtain a topographic point cloud data set; according to the terrain point cloud data set, a debris flow scouring path of the gully edge collapse area is analyzed, and a first terrain model is constructed; acquiring unmanned aerial vehicle monitoring data, simulating a line cross-trench path in combination with the first terrain model, optimizing cross-trench points and tower footing coordinates, and obtaining a power grid planning scheme; and the stability of the power grid planning scheme is evaluated, tower footing reinforcement parameters are adjusted, a final power grid planning scheme is obtained, and technical support is provided for power grid construction in the desert area.

The invention discloses an underwater topographic survey method and system based on unmanned ship data acquisition, and relates to the technical field of underwater topographic survey, and the method comprises the steps: generating a dynamic environment map based on acquired multi-modal environment data; dynamically sensing the underwater environment by using a deep Q learning algorithm based on the dynamic environment map, and predicting a potential topographic change probability; judging whether to update the dynamic environment map or not according to the predicted potential terrain change probability, and planning a navigation path by utilizing the updated dynamic environment map based on an RRT algorithm; collecting topographic data based on the navigation path, generating a three-dimensional topographic model, and detecting a shadow region in the three-dimensional topographic model by using U-Net; according to the detected shadow area, generating a complementary collection point through geometric analysis, adjusting a navigation path according to the complementary collection point, performing complementary collection on the shadow area, and obtaining complementary collection data; and fusing the complementary collection data with the three-dimensional terrain model to generate a terrain survey report. According to the invention, through dynamic environment perception, path planning, shadow area detection and supplementary mining, the efficiency and precision of underwater topographic survey are improved.

The invention discloses a land comprehensive renovation planning method based on three-dimensional modeling and auxiliary decision analysis, and relates to the technical field of land comprehensive renovation planning, and the method specifically comprises the following steps: based on a generated three-dimensional terrain model, recognizing a region with a continuous slope surface and a slope toe having a height difference fracture, and calibrating the region as a sliding structure interference sensitive region; the sliding structure is uniformly divided into a plurality of sliding structure sub-regions; obtaining slope sliding interference configuration information of each sliding configuration sub-region, analyzing the slope sliding interference configuration information, evaluating the sliding risk potential degree of each sliding configuration sub-region, and dividing each sliding configuration sub-region according to an evaluation result; and on the basis of the division result of each sliding configuration sub-region, corresponding slope reinforcement measures are executed, and dynamic regulation and control are carried out on the sliding configuration sub-regions. The problem of risk misjudgment caused by unclear recognition of the slope toe fracture is solved, and accurate recognition and dynamic reinforcement response of the sliding slope are achieved.

The invention discloses a method and system for monitoring the lake water level based on remote sensing images, and particularly relates to the technical field of remote sensing monitoring, and the method comprises the steps: constructing a complete three-dimensional terrain model of a lake through historical remote sensing images and data of underwater detection equipment, including water surface and underwater shapes; a quantitative relation model of the terrain and the water level is established by utilizing a digital twinborn technology and actually measured water level data, the model is repeatedly tested and optimized, the precision is ensured, and the model is finally applied to real-time water level monitoring, so that the water level information of a target lake is automatically acquired and updated; the problem that a terrain-water level relation model is difficult to accurately monitor lake water level changes in the prior art is solved. The system further comprises a water body boundary correction module and a boundary contour processing module, the boundary of the lake is recognized and extracted more accurately through a remote sensing image and a machine learning model, the boundary is optimized, and accuracy and completeness of water body information are guaranteed.

The invention relates to the technical field of image data processing, in particular to an urban building three-dimensional reconstruction method and device, and the method comprises the steps: obtaining a multi-view satellite orthoimage from the same scene, satellite-borne laser height measurement data of a target region, a digital terrain model and two-dimensional building vector data; performing accurate geometric registration on the multi-view satellite orthoimage, and executing dense matching to generate an initial parallax point cloud; and combining azimuth angle information of the multi-view orthoimage to construct a disparity map with accurate plane positioning. And calculating an elevation value above the earth surface by using satellite-borne laser altimetry data and a digital terrain model. And jointly estimating a parallax elevation proportionality coefficient by using the elevation value and the parallax value so as to convert the parallax map into a height map. And generating three-dimensional building vector data of the target area in combination with the two-dimensional building vector data. Therefore, the problems that cost based on surveying and mapping level remote sensing data is high, data collection is limited, and the requirement for global city three-dimensional reconstruction cannot be met in the prior art are solved.

The invention relates to the field of hydrological monitoring, in particular to a hydrological monitoring early warning method and system based on an unmanned aerial vehicle. The method comprises the following steps: acquiring a panoramic continuous aerial image of a to-be-monitored area; adaptive histogram equalization and image time delay interpolation optimization are carried out on the panoramic continuous aerial image of the to-be-monitored area to construct a time delay optimized continuous image; performing water body landform semantic analysis on the time delay optimized continuous image, performing real-time three-dimensional landform modeling, and constructing a real-time three-dimensional landform model; performing continuous frame optical flow tracking on the time delay optimized continuous image, performing inter-frame optical flow motion vector calculation, and generating a water level fluctuation curve and surface ponding area change characteristics; and carrying out instant hydrological state rendering on the real-time three-dimensional terrain model according to the water level fluctuation curve and the surface ponding area change characteristics so as to construct a dynamic hydrological state evolution model. According to the invention, accurate and efficient hydrological monitoring and early warning are realized, and the safety of the hydrological basin is improved.

The invention provides a three-dimensional terrain modeling method and system. The modeling method comprises the following steps: acquiring a plurality of aerial photos of a to-be-modeled region, wherein ground control points of the aerial photos are not marked; generating a first sparse point cloud set and a rough three-dimensional terrain model of the to-be-modeled region based on the aerial photo of each unmarked ground control point; automatically marking ground control points on each aerial photo based on the rough three-dimensional terrain model; generating a second sparse point cloud set of the to-be-modeled region based on the aerial photo of each marked ground control point; and generating a dense point cloud set and a fine three-dimensional terrain model of the to-be-modeled region based on the second sparse point cloud set. According to the modeling method provided by the invention, the marking speed is effectively improved while the marking precision of the ground control points is improved, and the efficiency of high-precision three-dimensional terrain modeling is remarkably improved on the whole.

The invention relates to a complex terrain surveying and mapping method, device and equipment and a medium. According to the complex terrain surveying and mapping method, device and equipment and the medium, laser beams with alternating polarization states are synchronously emitted through a dual-wavelength laser radar, an original point cloud with a space-time mark is captured, and earth surface points and noise points are analyzed based on time difference and polarization degradation characteristics; constructing a noise cluster function according to the noise points to identify vegetation artifacts; performing earth surface confidence evaluation on the earth surface points, filtering noise by using an elevation layering strategy, and positioning a fracture area; and finally, based on the denoised cloud layer, the fracture area and the earth surface point confidence coefficient, reconstructing a terrain curved surface, and generating a continuous terrain model. Therefore, precise reconstruction of the terrain sudden change area under vegetation coverage is realized, and the dual technical effects of resisting complex scattering interference and keeping the integrity of the terrain structure are achieved.

The invention relates to a road understanding method and device under the conditions of satellite denial and no prior map. The method comprises the following steps: generating global guide information by using a spline curve according to satellite map marking points; fusing the laser radar point cloud data to construct a three-dimensional terrain model, extracting roughness and a normal vector to obtain a corresponding graph, and constructing an environment trafficability graph; then, defining a credibility value for each graph, fusing a roughness graph and a normal vector graph evidence, and carrying out basic probability distribution fusion with a trafficability graph to obtain final data; determining a passable area based on the global guidance information and the final data, estimating the width of the passable area, and calculating the current position, angle expectation and standard deviation in combination with the local guidance information; and finally, calculating posteriori estimation by taking the distance as a measured value, and analyzing a boundary, so as to obtain a corrected guide path and a passable area. By adopting the method, the path generation accuracy can be improved.

The invention provides a modeling method and system for fusing live-action three-dimensional data and a digital model, and the method comprises the steps: obtaining real-time point cloud data in a preset terrain scene, taking the real-time point cloud data as the live-action three-dimensional data, and loading a digital model as a global terrain reference; carrying out optimization processing on the live-action three-dimensional data, and carrying out space-time alignment on the optimized live-action three-dimensional data and the digital model to generate an alignment data set; and determining a final fusion weight of the aligned live-action three-dimensional data and the aligned digital model based on the spatial distribution density and the terrain curvature value of the aligned data set so as to perform fusion processing on the aligned live-action three-dimensional data and the aligned digital model to generate a three-dimensional terrain model. Modeling of fusion of live-action three-dimensional data and a digital model is realized; according to the method, the problems of non-uniform space-time reference of multi-source data, surface distortion of a fusion model and detail loss in a complex terrain scene are solved, and high-precision and high-integrity live-action three-dimensional and terrain reference data fusion modeling is realized.