322 results about "Sky" patented technology

The invention discloses a land-sea-air-space holographic sensing and collaborative decision-making system based on multi-mode edge intelligence. The system comprises a sensing layer which is used for carrying out three-dimensional monitoring on a ship driving process, the sea, the sky, a shore base and a space formed by the ship driving process, the sea, the sky, the shore base and the sea, the sky and the shore base; the network layer is used for constructing a global communication basis, preprocessing monitoring data, judging whether the ship has an abnormal condition or not, and realizing data transmission of the ocean, the sky, a shore base and a space formed by the ocean, the sky and the shore base; and the application layer is used for judging whether an abnormal condition exists in the ship driving process or not based on the data of the ocean, the sky, the shore base and the space formed by the ocean, the sky and the shore base transmitted by the network layer, performing collision early warning decision based on the abnormal condition, and performing dynamic channel capacity prediction. And navigation guidance and route tracking in extreme weather are carried out based on environmental risk early warning, underwater obstacle collision is avoided, and early warning information and decision information are fed back to a sensing layer.

The invention discloses a photovoltaic ultra-short-term power prediction method and system based on multi-modal information fusion, and belongs to the technical field of photovoltaic power generation prediction. The method comprises the steps: obtaining an all-sky image sequence, segmenting a cloud layer and a sky region, and extracting cloud layer boundary features; thickness features are analyzed by calculating cloud pixel point brightness indexes, overall motion features of a cloud layer are determined based on adjacent frame displacement vectors, a time sequence sub-image covering a sun area in the future is reversely captured in combination with sun position coordinates, and then time sequence features and image features are extracted by adopting a dual-channel fusion mechanism. And finally, introducing a weather-dependent decoder: identifying weather types through a lightweight classifier, dynamically weighting the fused features based on the types, and outputting a photovoltaic power prediction result. According to the invention, through a multi-scale feature cooperation and dynamic weighting mechanism, the prediction robustness under a complex meteorological condition is significantly improved.

The invention discloses a multi-modal photovoltaic power prediction method based on double-layer Transform, and the method comprises the steps: firstly carrying out the preprocessing of a sky image and historical meteorological data, and carrying out the similar day selection based on dynamic time warping and k-means clustering, so as to construct a historical data set similar to the current meteorological condition; inputting the sky image into a double-layer Transform structure, extracting spatial features and time features in a layered manner, and extracting meteorological features from historical meteorological data by using expansion convolution; and performing interactive fusion on the multi-source features through a cross-modal attention mechanism, and enhancing a global dependency relationship in combination with self-attention to obtain a multi-modal prediction result. And on the other hand, a photovoltaic power sequence is separated from historical meteorological data, a single-factor prediction result is generated by using a long short-term memory (LSTM) network, dynamic weighted fusion is performed on the two types of prediction results through adaptive gating, and a final photovoltaic power prediction value is output.

The invention relates to the technical field of weather forecast, discloses a method for classifying severe convection weather forecast, and aims to solve the problem that complexity of severe convection weather requires multi-dimensional data support, so that a three-dimensional data acquisition network covering'ground-air-sky 'needs to be constructed. Ground observation data need to include minute-level rainfall, hourly air temperature and humidity (emphatically paying attention to humidity difference between 850hPa and 500hPa and reflecting unstable stratification) and 10-minute average wind speed of a meteorological station, and high-altitude detection data need to extract temperature vertical profiles (calculating convective condensation height LCL) and wind speed vertical shear (shear values of 0-3km and 0-6km) at 08 o'clock and 20 o'clock every day. According to the method for classifying severe convection weather forecast, new signals (such as sudden cloud top brightness temperature drop) observed in real time are rapidly absorbed, and meanwhile, the method is adaptive to severe convection characteristic differences of different areas (such as mountainous areas and plains) and different seasons, so that the forecast precision is improved, and the requirements of refined disaster prevention for high-accuracy and high-timeliness forecast are met.

The invention belongs to the technical field of sea fog monitoring, and particularly relates to a sea fog monitoring method and system based on multi-source satellite remote sensing data, and the method comprises the steps: collecting satellite radiation and microwave observation data, discriminating the cloud top phase state in combination with infrared ground microwave channel response differences, dividing clear sky and low cloud shielding scenes, and outputting identification data. And sea fog is detected in combination with the single-time infrared brightness temperature difference and the empty pixel parameters, optical parameters are inverted, and a sub-scene sea fog physical parameter set is formed. Carrying out normalized coupling reconstruction on the parameter set, constructing a sea fog exclusive feature space, separating a fog region from a non-fog region through phase state constraint to obtain an initial judgment feature field, correcting the edge of the fog region through neighborhood correlation and brightness temperature gradient constraint, strengthening spatial continuity to generate a spatial distribution field, locking a credible region, and outputting a final sea fog detection result. According to the invention, through layer-by-layer progressive design of scene division, feature optimization and multi-source verification, the precision and integrity of sea fog identification are significantly improved.

The invention discloses an atmosphere and ocean integrated atmosphere temperature and humidity profile inversion method based on multiple sources and multiple frequency bands. The method comprises the following steps: S1, acquiring multi-source collaborative observation data, and preprocessing the acquired data; s2, constructing an integrated state vector and coupling forward model, and obtaining an integrated state vector X; s3, performing optimal estimation based on the preprocessed data and the integrated state vector X, and performing joint inversion to realize integrated inversion solution; and S4, outputting an inversion result and theoretical uncertainty output. According to the method, integrated cooperative inversion is carried out through a physical model and an optimal estimation theory, and the inversion precision of the atmosphere temperature and humidity profile in the clear sky and in the presence of clouds, especially in the air above the ocean, is remarkably improved.

The invention relates to a method for verifying a Mars sky radiance simulation result based on a Mars real-shot photo, and belongs to the technical field of Mars sky background radiance. Comprises: image acquisition; performing radiation calibration; correcting dark current; performing flat field correction; converting a radiation value; and geometric correction. The Mars sky radiance simulation method breaks through the dependence of an existing model on idealized hypothesis, performs dynamic verification by using actual shot image data, remarkably improves the authenticity and reliability of a Mars sky radiance simulation result, and effectively solves the problem of systematic deviation under a specific wave band; by constructing a complete process from image acquisition, radiation calibration, geometric modeling to brightness inversion and comparison verification, dynamic feedback and closed-loop correction of a theoretical radiation model are realized, model adaptability is improved, and fine modeling under multi-temporal and multi-meteorological conditions is supported; the method can be applied to an existing Mars rover navigation camera and an image processing link of the Mars rover navigation camera, does not need additional modification, has good engineering practicability and task compatibility, and is convenient to popularize and apply.

The invention discloses a radiation correction method and system for an airborne hyperspectral imager. The radiation correction method and system are used for improving the radiation correction precision in complex weather. The method comprises the following steps: calculating a theoretical sun position based on unmanned aerial vehicle initial coordinates, ephemeris data and atmospheric parameters; performing course and differential compensation on a solar azimuth angle by combining IMU course and wind speed and direction data, performing refraction correction on an elevation angle, and outputting a high-precision sun position parameter; hyperspectral images and irradiance data are synchronously acquired, quaternion interpolation is combined with IMU data to realize space-time alignment, and attitude disturbance is eliminated; a hemispherical space irradiance model is constructed based on alignment data, cloud layer modes (clear sky, thin cloud and thick cloud) are divided according to atmospheric optical thickness variance, and Lambert body proportion correction, a discrete longitudinal standard method or a deep convolutional spectral network are respectively adopted for radiation correction. The method remarkably improves the correction precision and generalization ability, supports large-area image splicing, and is suitable for quantitative application of geological exploration, environment monitoring and the like.

The invention discloses an intelligent rainfall forecasting method and system based on real-time assimilation driving of sky-air-ground multi-mode sensing data, and relates to the field of machine learning, and the method comprises the steps: carrying out the coordinate alignment of an obtained standardized multi-source meteorological data set, distributing a weight according to the time-space credibility of a data source, and carrying out the calculation of the time-space credibility of the data source; generating an enhanced radar image feature set implying multi-modal information, and inputting the enhanced radar image feature set into the double-branch-UNet-GAN collaborative optimization model for training to obtain an optimal model adaptive to multi-modal data; based on severe convective weather characteristics and business requirements, precision correction and lightweight processing are performed on a forecast result after test set adversarial optimization through a regional attention mechanism, visual display is realized through an APP and a webpage terminal, positioning query and early warning push functions are synchronously provided, and a closed loop from data to service is completed. According to the method, full-chain innovation is formed from data fusion, model performance, aging precision, resource adaptation to service landing, and the scientificity and application value of intelligent rainfall forecasting are remarkably improved.

The invention discloses a star-sky dim and small target detection method fusing coordinate attention and a convolutional feedforward neural network, and belongs to the technical field of dim target detection. The method comprises the steps of obtaining a starry sky image data set, outputting an enhanced feature map by applying a coordinate attention mechanism, constructing a network model fusing the coordinate attention mechanism and a ConvFFN module through the ConvFFN module of a convolutional feedforward neural network, training a verification model based on simulation data, and finally outputting the centroid position and bounding box information of a target. According to the method, features are extracted in the transverse and longitudinal directions through a coordinate attention mechanism, the feature expression ability of a weak and small target in a low signal-to-noise ratio environment is effectively enhanced, the detection precision is remarkably improved, the omission ratio is reduced, the calculation efficiency is improved by combining the lightweight structure of ConvFFN and deep convolution optimization, and the method is suitable for large-scale popularization and application. A reliable and efficient detection solution is provided for astronomical observation and space debris monitoring.

The invention relates to the technical field of building thermotechnical testing, solves the technical problem that in the prior art, due to the fact that an experimental environment lacks the sky background radiation cold effect, the accuracy of enclosure structure performance testing is low, and provides an enclosure structure performance testing method and system coupled with the sky cold and hot radiation effect. The method comprises the following steps: establishing an equivalent sky effective temperature control model according to a meteorological database; acquiring test environment parameters through a test environment parameter control module according to the equivalent sky effective temperature control model; acquiring real-time test data of the enclosure structure test piece under the control of the test environment parameters through a test data acquisition module according to the test environment parameters; and analyzing the real-time test data through a test data analysis module to obtain a test result. The controllable equivalent sky effective temperature model is introduced, and the problems that in the prior art, the sky background radiation cold effect is lacked, and the deviation between the test result and the actual building service environment is large are effectively solved.

The invention relates to the technical field of irradiance estimation, in particular to an irradiance estimation method and device, electronic equipment and a storage medium, and the method comprises the following steps: obtaining ground site historical data of a research region, reanalysis data of the research region and an aerosol public data set; dividing weather types into clear sky samples and cloudy sky samples according to the obtained historical ground station data of the research area; inputting the clear sky sample, the reanalysis data and the aerosol public data set into a solar irradiance model to calculate clear sky expected irradiance GHIcs; obtaining observation data of a geostationary orbit meteorological satellite, and estimating a cloud cover coefficient CI by using satellite reflectivity; inputting the multi-cloud sky sample and the cloud cover coefficient CI into a cloud index-based semi-empirical model, and calculating a clear sky coefficient Kc; and multiplying the clear sky expected irradiance GHIcs by the clear sky coefficient Kc to obtain an irradiance estimation value under the all-sky condition. Through the improvement of the method, the regional adaptability and the estimation accuracy of irradiance estimation are improved.

A space surveillance method for detecting space objects in orbit around the Earth in images captured during the daytime, the method including the following steps: capturing a plurality of infrared images of the daytime sky using a camera including at least one infrared sensor, detecting space objects in orbit around the Earth on the basis of the images, the detection of bright spots being implemented by a deep-learning artificial intelligence system, and identifying each object detected from a catalogue of known space objects in orbit around the Earth.

The invention relates to the technical field of augmented reality, in particular to a 24-solar-term astronomical space-time presentation method and system based on mixed reality. The method comprises the following steps: firstly, reading augmented reality scene initialization data, configuring virtual scene parameters, and executing three-dimensional scene registration to generate a registration matrix; executing visual tracking by collecting an image stream, and generating a viewpoint transformation matrix; the system performs real-time sky semantic segmentation on an image stream to generate a binarized sky mask, and constructs an augmented reality rendering pipeline: synthesizing registration and viewpoint matrix calculation rendering operators, using the sky mask as an Alpha mask to perform pixel-level fusion of a virtual starry sky and a real sky, and combining sparse point clouds to perform depth occlusion synthesis, so as to obtain an augmented reality rendering pipeline. An atmospheric optical coloring model and a dynamic volume particle system are loaded for environmental atmosphere enhancement; and optical consistency fusion of a virtual image and a real environment is further realized through HDR luminosity alignment and tone mapping, and finally high-fidelity augmented reality superposition is realized.

The invention provides a wide-area tomography calculation astronomical imaging system and device, and the system comprises a snapshot spectral imaging module which is used for capturing full-view three-dimensional hyperspectral data of an observation view field; the red shift resolving module is used for processing the three-dimensional hyperspectral data through a hybrid algorithm based on the three-dimensional hyperspectral data, and inverting a target red shift value, three-dimensional space coordinates and physical parameters of the target celestial body; the chromatography data visualization module is used for generating a three-dimensional chromatography map through pseudo-color labeling and a three-dimensional modeling method based on the target red shift value, the three-dimensional space coordinates and the physical parameters; and the control module is used for configuring the snapshot spectral imaging module based on the observation target parameters. According to the method, high-precision cosmic chromatography of a wide-area sky area is realized, three-dimensional hyperspectral data is converted into a visual and reliable three-dimensional space distribution model and a physical parameter map, and reliable technical support is provided for frontier research of cosmic large-scale structures, galaxy evolution and dark matter distribution.

The invention relates to the technical field of atmosphere PM2.5 concentration early warning, and discloses an urban atmosphere PM2.5 concentration inversion and dynamic early warning system fused with multi-source remote sensing data. Comprising a main control module, a sky-land-sea three-dimensional monitoring network module, a multi-source data fusion module, a digital twin deduction module, a dynamic emission reduction strategy generation module, a safety early warning module and an auxiliary module, and the signal control module is used for performing signal control on the sky-land-sea three-dimensional monitoring network module, the multi-source data fusion module, the digital twinborn deduction module, the dynamic emission reduction strategy generation module, the safety early warning module and the auxiliary module and is used for coordinating operation and data scheduling of the modules. According to the invention, monitoring blind areas are eliminated through satellite-unmanned aerial vehicle-ground-ocean cooperation, full-space coverage is realized, and PM2.5 inversion error lt is realized through multi-source data fusion; and high-precision inversion is realized, environment and economic targets are balanced through an MORL algorithm, and an abnormal root is positioned through causal reasoning, so that an intelligent decision-making effect is achieved.

The invention provides a self-adaptive sky-ground-water integrated algal bloom monitoring method and platform, which are used on the basis of establishing an intelligent algal bloom identification facility for dense time sequence sky-air-ground collaborative observation by using three-dimensional monitoring means such as an unmanned aerial vehicle, satellite remote sensing and near-ground hyperspectrum. According to the method, a dynamic calibration mechanism for capturing a dynamic mapping relation from inherent optical attributes to apparent optical attributes is combined to realize self-adaptive calibration of spectral feature positions of algae, so that real-time, efficient and accurate intelligent algal bloom recognition processing is promoted, an algal bloom change trend is presented in a spatial-temporal distribution mode in a multi-dimensional, multi-view and multi-scale manner, and the algal bloom recognition accuracy is improved. And effective data support is provided for algal bloom early warning of a major water source.

The invention discloses a DEM-based earth surface solar radiation prediction method, equipment and a medium. The method comprises the following steps: correcting a direct radiation reference value based on nonlinear attenuation of a cloud layer to direct radiation to obtain actual direct radiation; based on the enhancement effect of the cloud layer on the scattered radiation, correcting the scattered radiation reference value to obtain first actual scattered radiation; according to a preset shadow judgment criterion, calculating actual horizontal plane direct radiation after the actual direct radiation reaches the earth surface by taking the condition that the slope surface back to the sun has no direct radiation as a constraint; calculating second actual scattered radiation after the first actual scattered radiation reaches the earth surface according to the control of the sky vision field factor of the earth surface area on the scattered radiation; calculating reflected radiation generated after the actual direct radiation and the first actual scattered radiation reach the earth surface based on the Lambert reflection law; therefore, the total solar radiation is obtained. According to the invention, high-precision quantification of earth surface solar radiation under complex terrain conditions is realized.

A media application provides, as input to a diffusion model, an initial image and a request to change a lighting in the initial image, wherein the initial image includes a subject and a sky. The media application outputs, with the diffusion model, an output image that satisfies the request. The media application determines, from the initial image, a sky segment and a subject segment. The media application generates a sky mask that corresponds to the sky segment and a subject mask that corresponds to the subject segment. The media application modifies a coloring of the initial image to match a coloring of the output image. The media application blends the modified initial image with the output image to form a blended image while using the subject mask to prevent modification to the subject from the modified initial image and the sky mask to prevent modification to the sky from the output image during the blending.

This invention discloses a method and system for intelligent weather image acquisition and recognition, specifically relating to the field of weather image recognition technology. It involves continuous polarization imaging of the sky region while simultaneously acquiring spatial attitude and temporal information; preprocessing the polarization image data and extracting Stokes parameters to obtain standardized sky polarization light field data; then using a theoretical Rayleigh scattering model to analyze the polarization degree distribution pattern at different wavelengths to obtain theoretical sky polarization pattern characteristics; based on the polarization light field data, identifying the spatial distribution of actual clouds, aerosols, and haze in the sky to form actual atmospheric composition distribution characteristics; extracting anomalous polarization regions through difference analysis between theoretical and actual characteristics, and accurately classifying halo polarization anomalies and scattering polarization anomalies based on geometric and spectral characteristics; generating ultralocal weather change early warning signals based on the classification results; thus improving the accuracy and real-time performance of early warnings for ultralocal anomalous weather phenomena.

The application belongs to the technical field of sea fog monitoring, and particularly relates to a sea fog monitoring method and system based on multi-source satellite remote sensing data, which comprises the following steps: collecting satellite radiation and microwave observation data, combining the response difference of infrared and microwave channels to distinguish the cloud top phase state, dividing clear sky and low cloud blocking scenes, and outputting identification data; combining single-time infrared brightness temperature difference and air pixel parameters to detect sea fog and retrieve optical parameters, forming a scene-specific sea fog physical parameter set; normalizing and coupling the parameter set for reconstruction, constructing a sea fog-specific feature space, separating the fog area and the non-fog area through phase state constraint to obtain an initial judgment feature field, correcting the fog area edge through neighborhood correlation and brightness temperature gradient constraint, strengthening the spatial continuity to generate a spatial distribution field, and locking a reliable area to output the final sea fog detection result. Through the progressive design of scene division, feature optimization and multi-source verification, the accuracy and integrity of sea fog identification are significantly improved.

We present a ground-based laser system for searching, ranging, and tracking that actively illuminates small resident space objects (RSOs) in low Earth orbit (LEO) and observes position and transit-time of reflections, enabling orbital custody of most one-to-few centimeter-sized objects. A diode-pumped alkali laser (DPAL) augmented with mode-locking and Q-switching serves as an illuminator and offers exceptionally high spectral brightness due to its output beam's sub-nanosecond pulse duration and picometer-level spectral linewidth. Kilohertz fast-rastering enables interrogations of distinct few-meter-sized sky-patches at megahertz rates. Paired on the observation side with one or more telescopes outfitted with Faraday anomalous dispersion optical filters (FADOFs), image intensifiers, multi-pixel arrays, and nanosecond timing, the combined system could offer nearly background-free discoveries of RSOs every hour, even during daytime. Periodically re-flashing previously discovered objects to maintain orbit custody expends only a small fraction of total observing time.

An adaptive rotation detection and measurement method for a small-scale aurora structure comprises the following steps: step 1, carrying out preliminary detection on an aurora arc in an all-sky aurora image through an aurora arc structure sensing module, and obtaining an ellipse approximation reconstruction region by adopting shape fitting; estimating the inclination angle of the aurora arc relative to the horizontal position by using the elliptical main axis direction; step 2, carrying out space correction on the coordinates of the all-sky aurora image and the labeling frame of the small-scale aurora structure, namely, carrying out anticlockwise rotation on the aurora image by taking the inclination angle as an angle, and simultaneously carrying out coordinate conversion on corresponding labels in the same direction; and step 3, establishing a target detection model of the small-scale aurora structure on the corrected spatial domain, realizing positioning and region identification of the small-scale aurora structure under the condition of direction alignment, rotating the detected small-scale aurora structure back to the original direction, and measuring the detection frame under the original spatial coordinates to obtain a target detection result of the small-scale aurora structure. And the spacing, the length-width ratio, the height and the width parameters of the small-scale aurora structure are obtained.

The embodiment of the application provides a false alarm suppression method, device and medium for ground-based telescope observation, through research on the constructed false alarm data set, various false alarm characteristics can be fully obtained for different false alarm categories, based on trajectory quality characteristics, sky light identification coefficient, target identification coefficient, hot pixel identification coefficient, space-time geometric consistency, gray consistency, speed size consistency, long axis and speed size consistency, long axis and speed direction consistency, the uncertainty of the traditional experience threshold discrimination method can be got rid of, not only various scene false alarms can be effectively identified, but also false suppression of real targets can be prevented to cause missed alarms, and the false alarm suppression method is suitable for target detection after false alarm suppression in different observation environments, and the false alarm suppression effect is good.

The invention relates to the field of remote sensing satellite observation task planning, in particular to a remote sensing satellite hotspot target observation method and system based on meteorological elements, which are used for carrying out priority division and analysis on tasks according to the conditions of importance degree, emergency degree, observation time window and the like of hotspot targets, determining hotspot target observation tasks, and carrying out real-time observation on the hotspot targets. And obtaining a corresponding geographic information data set. On the basis, simulation calculation of the satellite transit area is carried out in sequence, and a spatio-temporal data set of the hotspot observation target in the satellite transit process is generated. And in combination with CMA-GFS data, carrying out space-time screening on observable targets, determining hotspot targets with clear sky observation conditions, and forming a selected space-time data set. And finally, the whole process operation from satellite observation task planning, platform attitude maneuver and instrument pointing calculation to observation guidance generation and instruction uploading execution, and observation state tracking and effect evaluation is completed, invalid observation caused by cloudy and foggy weather is reduced, and the satellite observation efficiency is improved.

Disclosed are a method and an astrophotographic apparatus for acquiring images of targets in a sky area. The method includes: step 1, an image acquisition device is driven through a controlled rotatable component to point to the position near a target in a sky area, and images of the sky area are acquired through the image acquisition device; step 2, the images of the sky area are analyzed to obtain the right ascension coordinates and the declination coordinates of the center point of images for synchronizing the coordinates to the controlled rotatable component; step 3, the image acquisition device is driven by the controlled rotatable component to point to a target position of the target right ascension coordinates and the target declination coordinates corresponding to the target celestial body to acquire the images; and step 4, an image processing is performed on the images to obtain the processed images.

An object of a system according to an embodiment is to make starry sky observation easier and more enjoyable and to promote information sharing and exchange between users.SOLUTION: A system includes an imaging unit, an identification unit, an explanation providing unit, an interaction unit, an information sharing unit, and a community unit. The photographing unit photographs a starry sky. The identification unit analyzes the image captured by the imaging unit to identify celestial objects and constellations. The explanation providing section provides an explanation about the celestial body or the constellation identified by the identifying section. The interaction unit performs interaction with a user. The information sharing unit performs information sharing between users. The community component facilitates interaction between users.SELECTED DRAWING: Figure 1

The application discloses a kind of floating offshore solar radiation measurement data correction method and system, it includes the following steps: obtaining the pitch angle and roll angle of floating offshore solar radiation measurement system;Obtain the unit normal vector of the measuring plane pointing to the sky in the horizontal plane rectangular coordinate system;Calculate the angle between the measuring plane and the horizontal plane;Get horizontal plane solar zenith angle and azimuth angle;Construct the unit vector along the direction of sunlight incidence pointing to the sun;Correct the zenith angle;Calculate the horizontal plane scattered irradiance value;The horizontal plane total irradiance saved by floating offshore solar radiation measurement system is corrected, and the corrected horizontal plane total irradiance is obtained.The measurement data of the floating offshore solar radiation measurement system is corrected by the application, the measurement error caused by the inclination of the measurement platform caused by wind and wave is reduced, and more accurate measurement data is provided for the evaluation of offshore light resources and the planning of offshore photovoltaic power station.

To highly accurately measure cloud heights of clouds in the whole sky.SOLUTION: A cloud measurement system comprises: a stereo camera 30 that can change zoom magnification in an imaging direction and optically; a picture reception unit 204 for acquiring the imaged picture; a cloud edge detection unit 207 that recognizes a cloud displayed on the picture, detects a boundary of the cloud, and acquires an edge region including the boundary from a plurality of sub regions in the picture; a cloud imaging order setting unit 209 that on the basis of the edge region, sets target sub regions to be imaged while changing the zoom magnification of the camera and their imaging order; a camera control unit 210 that controls the stereo camera 30 so as to perform enlargement imaging on the target sub regions according to the set imaging order to acquire a stereo picture for each target sub region, a stereo vision distance measurement unit 202 for acquiring a distance to a cloud displayed on the stereo picture using a parallax, and a cloud bottom height estimation unit 203 for acquiring a cloud bottom height of the cloud on the basis of the acquired distance.SELECTED DRAWING: Figure 1

The application discloses a kind of inclined surface hourly solar radiation calculation method and related equipment, belong to solar energy resource assessment and building energy saving technical field.The method includes: obtaining horizontal plane solar radiation data and space-time information, and the inclination and azimuth of target inclined surface;Calculate solar elevation angle, solar incidence angle, clear sky index and horizontal plane scattering radiation ratio;Two scattering radiation conversion coefficients are obtained by using two basic models respectively;At least according to clear sky index, horizontal plane scattering radiation ratio and solar incidence angle to determine dynamic weight;Two scattering radiation conversion coefficients are weighted and summed with dynamic weight, to obtain combined scattering radiation conversion coefficient, and then obtain inclined surface hourly solar total radiation.The method is combined by dynamic weight based on weather state and solar position real-time change to two basic models with obvious difference in weather adaptability, overcome the limitation that single model is only accurate under certain weather, and does not depend on multi-regional long-term measured data, improve the calculation accuracy and applicability under all weather types.