23 results about "Polar orbit" patented technology

The invention provides a cloud condition adaptive geostationary satellite sea surface temperature inversion method based on deep learning, and relates to the technical field of sea surface temperature inversion, and the method specifically comprises the steps: obtaining geostationary satellite observation data, geographic information data, polar orbit satellite sea surface temperature and cloud products, and analyzing the sea surface temperature and atmospheric background data; performing standardization preprocessing on the obtained stationary satellite observation data; constructing a cloud detection data set; a cloud detection model of deep learning is constructed and trained; constructing a clear sky data set; a clear sky inversion model of deep learning is constructed and trained; constructing a data set for under-cloud inversion model training; constructing an under-cloud inversion model of deep learning and training the under-cloud inversion model; and integrating the cloud detection model, the clear sky inversion model and the under-cloud inversion model, adaptively calling the corresponding model according to a real-time cloud detection result, and generating a final sea surface temperature product. According to the technical scheme, the problem that in the prior art, the accuracy of a reconstructed product on the spatial structure cannot be comprehensively reflected is solved.

The invention belongs to the field of artificial intelligence, and particularly relates to a multi-source fusion perception air-space-ground integrated geological disaster identification method and system. According to the scheme, firstly, satellite images, collected by a stationary orbit satellite, a synthetic aperture radar satellite and a polar orbit satellite, of a target area are obtained in real time; performing time interpolation and spatial super-resolution reconstruction on the multi-source heterogeneous satellite image data to obtain three types of satellite images with consistent time and space and uniform resolution; synchronously inputting the three types of satellite images into a pre-trained coarse-grained disaster recognition model to obtain a macroscopic probability graph reflecting the geological disaster risk; after a high-risk local area is identified, a complete high-resolution image is obtained through mutual cooperation of ground monitoring equipment, an unmanned aerial vehicle and the like; and finally, inputting the high-resolution image into a pre-trained fine-grained disaster recognition model to obtain a geological disaster recognition result. According to the invention, the problems of the existing geological disaster monitoring scheme in the aspects of real-time performance and precision are solved.

This invention provides a method, apparatus, and device for identifying water bodies on a single orbit of a polar-orbiting meteorological satellite, comprising: acquiring first-band data, first-positioning information data, and second-band data, second-positioning information data, and product data at a first spatial resolution from a polar-orbiting meteorological satellite; sampling the data at the second spatial resolution to obtain second-band data, second-positioning information data, and product data at the first spatial resolution; acquiring high-quality binary classification data; training a decision tree model based on the first-band data, second-band data, normalized index data, band difference data, and band ratio data at the first spatial resolution corresponding to high-quality water body pixels and high-quality non-water body pixels within the target area, to obtain a target decision tree model; and obtaining the single-orbit water body identification area based on the target decision tree model. The solution of this invention accurately identifies water bodies in complex background conditions, improving monitoring accuracy and applicability.

The application relates to the field of internal solitary wave prediction, and discloses a marine internal solitary wave propagation prediction method based on an improved TimeXer model, which comprises the following steps: constructing an improved TimeXer model; collecting and pre-processing remote sensing image data of a stationary orbit satellite GK-2A and a polar orbit satellite; extracting internal solitary wave parameters based on the remote sensing image data, combining with hydrological environment parameters to construct an internal solitary wave prediction data set, and training a model; obtaining remote sensing image data of the stationary orbit satellite GK-2A and the polar orbit satellite of a target sea area, pre-processing the remote sensing image data, inputting the remote sensing image data into a qualified model, and performing internal solitary wave prediction. The method disclosed by the application can effectively improve the precision and stability of marine internal solitary wave propagation prediction; the model adaptability to complex marine environments is enhanced by introducing an innovative module, and a reliable scheme is provided for accurate prediction of marine internal solitary waves.

The application provides a cloud condition adaptive static satellite sea surface temperature retrieval method based on deep learning, relates to the technical field of sea surface temperature retrieval, and specifically comprises the following steps: obtaining static satellite observation data, geographic information data, polar orbit satellite sea surface temperature and cloud products, reanalysis sea surface temperature and atmospheric background data; performing standardization preprocessing on the obtained static satellite observation data; constructing a cloud detection dataset; constructing a deep learning cloud detection model and training the same; constructing a clear sky dataset; constructing a deep learning clear sky retrieval model and training the same; constructing a dataset for cloud retrieval model training; constructing a deep learning cloud retrieval model and training the same; integrating the cloud detection model, the clear sky retrieval model and the cloud retrieval model, adaptively calling corresponding models according to real-time cloud detection results, and generating a final sea surface temperature product. The technical scheme of the application overcomes the problem in the prior art that the accuracy of the reconstructed product in the spatial structure cannot be comprehensively reflected.

The present application belongs to the field of artificial intelligence, and particularly relates to a space-air-ground integrated geological disaster identification method and system based on multi-source fusion perception. The scheme first acquires satellite images of a target area collected by stationary orbit satellites, synthetic aperture radar satellites and polar orbit satellites in real time; then performs time interpolation and spatial super-resolution reconstruction on multi-source heterogeneous satellite image data, and further obtains three types of satellite images with consistent time and space and unified resolution; the three types of satellite images are synchronously input into a pre-trained coarse-grained disaster identification model to obtain a macro probability graph reflecting geological disaster risk; after identifying the local area with high risk, ground monitoring equipment and unmanned aerial vehicles are used to obtain complete high-resolution images; finally, the high-resolution images are input into a pre-trained fine-grained disaster identification model to obtain the identification result of the geological disaster. The present application overcomes the problems of existing geological disaster monitoring schemes in real-time and precision.

The application relates to the field of high-precision positioning technology and discloses a troposphere delay product generation method combining GNSS and polar orbit remote sensing satellites, which comprises the following steps: calculating the difference between real-time GNSS true value points and a remote sensing satellite troposphere delay background field to generate a group of differential anchor points; after reliability arbitration is performed on the differential anchor points, a continuous troposphere differential correction field is generated through a terrain-constrained interpolation algorithm, the weight of the interpolation algorithm is based on the effective path distance considering the terrain obstacle penalty, and finally the correction field is superimposed on the background field; through generation and application of a dynamic correction field based on physical deviation, the method replaces the direct mathematical fitting of different source data in the prior art, the interpolation method of terrain constraint is used, space propagation of correction information can follow the restriction of real physical barriers, and unrealistic correction results in complex terrain areas are avoided.

A method implemented by a computer for maintaining a spacecraft near an orbit includes a step (3) of detecting that a distance from the spacecraft to the orbit is greater than a spacecraft threshold, and, in response thereto, a step (5) of linearizing the dynamics of the spacecraft from the current time over a certain time horizon with respect to a high-fidelity reference trajectory to generate a state transition matrix (STM) for uncontrollable motion of the spacecraft within the time horizon. The STM includes non-expanding eigenvectors having a magnitude of 1 or less and expanding eigenvectors having a magnitude greater than 1. The method further includes a step (7) of determining a control action that changes the next state of the spacecraft to a linear combination of non-expanding eigenvectors of the STM, and a step (9) of generating a control command to an actuator of the spacecraft.

The application provides a precipitation prediction method and device, electronic equipment and storage medium, the method comprises the following steps: obtaining a plurality of frequency polarization channel brightness temperature data and infrared channel brightness temperature data of a target area based on a polar orbit satellite and a geosynchronous orbit satellite; determining whether a target area has a precipitation event according to the obtained data; if so, filtering the target frequency polarization channel brightness temperature data according to the sea-land classification result of the target area; determining the precipitation prediction result of the target area according to the target frequency polarization channel brightness temperature data and the infrared channel brightness temperature data. By combining the meteorological monitoring data of the polar orbit satellite and the geosynchronous orbit satellite, the temporal and spatial resolution of the meteorological monitoring data is improved, and the passive microwave data, infrared data including water vapor channel data are integrated, thereby improving the accuracy of the precipitation prediction.

The present application relates to the technical field of spacecraft electromagnetic propulsion, and particularly relates to an electromagnetic propulsion device for polar orbit satellite and a propulsion control method, aiming at solving the technical problem of short service life of artificial satellite in the prior art. The electromagnetic propulsion device comprises a power supply assembly and a propulsion assembly; the power supply assembly is electrically connected with the propulsion assembly, and the two form a circuit loop; the propulsion assembly is used for shielding current passing through itself and is used for connecting with a spacecraft. The electromagnetic propulsion device does not need to use working medium such as liquid, gas and plasma, and obtains propulsive force through cooperation of the earth space magnetic field and the current, thereby reducing the cost of the propulsion device and greatly improving the service life of the on-orbit satellite.

The invention provides a power grid mountain fire monitoring method and device, electronic equipment and a storage medium, and relates to the field of mountain fire monitoring. The method comprises the following steps: acquiring fire data corresponding to a target area based on a polar orbit satellite; determining power grid equipment influenced by the fire behavior according to the fire behavior data and power transmission line ledger data corresponding to the target region; determining a burning forbidden area corresponding to the target area according to burning forbidden area equipment corresponding to the target area; and displaying the fire data, the power grid equipment influenced by the fire and the burning prohibition area on a map in an overlapping manner. According to the method, high-precision positioning of the fire can be realized based on the polar orbit satellite, automatic identification of the fire influence equipment can be realized based on the fire data and the ledger data of the power transmission line, and linkage analysis between the fire and the burning prohibited area is realized through overlapped display of the fire data, the fire influence equipment and the burning prohibited area; and whether the fire relates to the burning prohibited area can be quickly judged, and the manual confirmation burden is reduced.

The present application belongs to the technical field of geophysics, and more particularly relates to a method and device for drawing a temperature-logarithmic pressure map by satellite joint observation, the method comprising: determining the position and altitude information of an image to be drawn, and converting the altitude into a ground pressure value; obtaining atmospheric temperature and humidity profile data of a polar orbiting meteorological satellite and a geostationary meteorological satellite respectively, and matching satellite orbit scanning points on the position of the image to be drawn; extracting vertical profile data information of temperature and specific humidity of the satellite orbit scanning points at the altitude according to the atmospheric temperature and humidity profile data, and drawing a temperature-logarithmic pressure map. The joint observation of the polar orbiting meteorological satellite and the geostationary meteorological satellite provides observation data with higher spatial coverage and time frequency, and the drawn temperature-logarithmic pressure map can serve as an effective supplement to conventional observation and play an important role in meteorological services.

The application discloses a polar orbit satellite cloud phase state product quality inspection method, device, equipment and medium. The method comprises the following steps: acquiring satellite data to be inspected and inspection source satellite data, wherein the satellite data to be inspected is polar orbit meteorological satellite FY-3E, FY-3D and FY-3F satellite data, and the inspection source satellite data comprises other similar meteorological satellite MODIS data and CALIPSO data. The satellite data to be inspected and the inspection source satellite data are subjected to data processing respectively to obtain target satellite data to be inspected and target inspection source data. According to the target satellite data to be inspected and the target inspection source data, a quality inspection index corresponding to the satellite data to be inspected is determined, and a quality inspection result corresponding to the satellite data to be inspected is determined according to the quality inspection index. The technical scheme of the embodiment of the application builds a business real-time inspection system of satellite cloud phase state products, improves the inspection efficiency and accuracy of data quality, and provides a correction basis for error adjustment of satellite cloud phase state products.

The invention discloses a cloud motion vector estimation method and cloud motion vector estimation equipment based on polar orbit satellite remote sensing images, and relates to the crossing field of meteorological remote sensing and computer vision. The method comprises the steps of obtaining multi-temporal cloud image data based on a polar orbit satellite remote sensing image; calculating a global motion vector and a local motion vector based on the multi-temporal cloud image data; and estimating and obtaining a cloud motion vector based on the global motion vector and the local motion vector. According to the scheme, challenges of a traditional optical flow method in complex cloud layer motion and satellite image noise can be dealt with, and a more accurate and robust wind speed estimation result is provided.

This invention discloses a method, device, and medium for detecting polar daytime sea fog / low clouds using multi-source polar-orbiting satellites. The method includes: acquiring and preprocessing remote sensing image data collected by multi-source polar-orbiting satellites; calculating a sea surface identification index using two preset band data from the preprocessed remote sensing image data; then, based on the sea surface identification index and near-infrared band reflectance data from the remote sensing image data, jointly removing areas related to seawater and sea ice / snow from the preprocessed remote sensing image data; calculating the gray-level co-occurrence matrix for each pixel in a third preset band of the remote sensing image data after removing seawater, sea ice, and snow, and statistically analyzing several texture features based on the gray-level co-occurrence matrix; inputting the statistically analyzed texture feature values ​​corresponding to all remote sensing images from polar-orbiting satellites into a trained random forest model to identify and remove mid-to-high clouds, leaving the remaining clouds as sea fog / low clouds. This invention is less affected by satellite differences and variations in solar altitude angle.

To transmit flying object information to a coping system or a satellite integrated command center without interposing a satellite information transmission system.SOLUTION: In the polar orbital satellite system 442, the monitoring system has a group of six or more polar orbital satellites that fly in polar orbits having the same average orbital altitude on the same orbital plane. A polar orbital satellite constellation forms communication crosslinks with forward and aft flying polar orbital satellites. At least one or more polar orbit satellites form a communication crosslink with a countermeasure system or a satellite integrated command center provided with a communication route searching device for satellite information. The monitoring system transmits the flying object information to a coping system or a satellite integrated command center without interposing a satellite information transmission system.SELECTED DRAWING: Figure 11

The application provides a domestic passive meteorological satellite cloud bottom height high-precision inversion method and system, and belongs to the field of atmospheric cloud parameter remote sensing inversion and quantitative remote sensing mechanism. The application fuses satellite multi-channel atmospheric top reflectivity observation, brightness temperature observation and atmospheric temperature profile reanalysis data, develops a complex nonlinear feature extraction and modeling method, improves the nonlinear mapping capability among the atmospheric top reflectivity, the brightness temperature and the cloud bottom height, combines the whole period infrared channel characteristics and the stratification information, enhances the night and all-time inversion capability, improves the generalization adaptability of the model through the multi-source sample expansion and the stacking learning strategy, designs the sample expansion and the auxiliary training mechanism, effectively alleviates the problem of insufficient high-quality training data, and finally realizes the high-precision inversion of the all-time cloud bottom height suitable for the domestic stationary or polar orbit meteorological satellite.

The application discloses a kind of based on Fengyun polar orbit meteorological satellite South China Sea summer monsoon double-index monitoring method, this method obtains 850hPa atmospheric temperature and specific humidity by polar orbit meteorological satellite FY-3D vertical detection instrument group VASS, 850hPa false equivalent potential temperature index is calculated;Ocean surface wind speed and wind direction are obtained by ocean surface wind field data of the wind field measurement radar WindRAD inversion of polar orbit meteorological satellite FY-3E, average zonal wind index is calculated;By evaluating the accuracy of FY-3D / VASS temperature and specific humidity relative to ERA5, and the accuracy of ocean surface wind of FY-3E / WindRAD relative to MetOp-C / ASCAT is evaluated index, the accuracy of the double-index monitoring South China Sea summer monsoon outbreak process is verified from the evaluation result.The application uses FY-3D to calculate false equivalent potential temperature and FY-3E ocean surface wind double-index monitoring South China Sea summer monsoon, double-index is well monitored 2022 South China Sea summer monsoon outbreak process temperature and humidity field and wind field conversion, so as to verify the application ability of two kinds of satellite data in South China Sea summer monsoon climate monitoring.

This invention provides a polar-orbiting satellite navigation constellation system, a navigation method, and a user terminal. The polar-orbiting satellite navigation constellation system includes: four orbital planes, each with its intersection point with the equator evenly distributed along the equator, with a longitude interval of 45 degrees between adjacent orbital planes; nine satellites evenly distributed on each orbital plane, with a phase interval of 40 degrees between adjacent satellites; each satellite orbits at an altitude of 80,000–90,000 km and an orbital inclination of 90 degrees. It also employs an isotope power supply system and a redundant cold / hot backup system in the attitude and orbit control system. This invention utilizes a high-orbit scheme that avoids the influence of the Van Allen radiation belts, effectively solving the radiation effects caused by the Earth's radiation belts and increasing the reliability of the navigation system; the use of an isotope power supply system improves the operational lifespan of the navigation system; and the cold / hot redundant backup of the attitude and orbit control system enhances the reliability of the control system.

The present application relates to the technical field of quantitative remote sensing, in particular to a global surface temperature monthly range estimation method and system based on polar orbit satellite double time phase data, equipment and medium, the method provided by the present application mainly includes constructing a double time phase data set within a month to increase the information dimension, and establishing a double phase continuous variation model (DPCV) capable of describing two-day continuous variation, so as to more truly simulate the temperature dynamics on the monthly scale, and the precision is significantly improved: by constructing the double time phase data, the information dimension is expanded from 24 hours to 48 hours, and more abundant constraint information is provided for the model. The DPCV model can better capture the temperature fluctuations caused by factors such as weather system evolution within a month, instead of simple averaging, so that the estimated monthly maximum temperature and minimum temperature are closer to the true situation, and the precision of the monthly range is significantly improved.

The invention discloses a method, a device and equipment for estimating vegetation total primary productivity through geostationary satellite remote sensing and a medium. The method comprises the following steps: acquiring hourly geostationary satellite data in a preset territory day; determining coarse resolution hourly vegetation total primary productivity based on the hourly stationary satellite data; and based on polar orbit satellite data of a preset region, downscaling the gross primary productivity of the coarse-resolution hourly vegetation on the basis of vegetation types to obtain the gross primary productivity of the high-spatial-resolution hourly vegetation. According to the method, the gross primary productivity of the coarse resolution hourly vegetation in the day is obtained by utilizing the data of the stationary satellite, and then the gross primary productivity of the coarse resolution hourly vegetation is downscaled to the high spatial resolution by adopting a physical downscaling mode of a coupling vegetation type in combination with the high spatial resolution data of the polar orbit satellite; the hourly high-temporal-spatial-resolution fine monitoring of the vegetation photosynthesis is realized, and the accuracy of the hourly vegetation total primary productivity is improved.

The present application belongs to the field of remote sensing technology analysis, and particularly relates to a method for obtaining horizontal propagation phase velocity of gravity wave based on three satellites in the same series of micro light satellite networking. The method comprises the following steps: S1: obtaining night micro light data of three satellites, wherein the night micro light data comprises SVDNB and GDNBO; S2: preprocessing the night micro light data, and extracting gravity wave stripes in the night micro light image; S3: correcting the gravity wave stripes through a parallax correction model, drawing the corrected gravity wave stripes together for pairing, and obtaining the corresponding relationship of gravity wave propagation; and S4: extracting the interval distance between the gravity wave stripes, and then calculating the horizontal propagation phase velocity of the gravity wave. The satellites for obtaining the micro light data are increased from NPP to NPP, JPSS-1 and JPSS-2, thereby improving the time resolution of the night micro light data of the polar orbit satellite. The method for correcting the position of the gravity wave is proposed, the position of the gravity wave stripe after geometric correction is extracted for parallax correction, and then the horizontal propagation phase velocity of the gravity wave is calculated.

To transmit missile information to a countermeasure system in a semi-real time by detecting the launch of a missile which is a high temperature object.SOLUTION: The flying object handling system 401 includes a monitoring ground center 810 including a trajectory prediction device 803. If the monitoring satellite 307 detects a significant hot object, the monitoring satellite 307 transmits monitoring information to the monitoring ground center 810. A flying path prediction device 803 integrates flying object information by all monitoring satellites 307 detecting a high-temperature object, derives flying object position coordinates after deriving a line-of-sight vector and inversely estimating an error factor, and transmits the flying object information to a countermeasure ground center 802 via a satellite information transmission system 403.SELECTED DRAWING: Figure 9