115 results about "Earth observation" patented technology

A system and method for integrated optimization of autonomous electric vehicle fleets across transportation and electricity networks which employs artificial intelligence to dynamically allocate autonomous electric vehicles between mobility services and electricity grid services based on real-time conditions. The platform acquires data including energy mix forecasts, earth observation measurements, vehicle owner schedules, and emission-based route penalties to generate coordinated allocation decisions. Vehicle owners specify availability through a scheduling interface. The system optimizes vehicle utilization through a hierarchical optimization approach implementing mobility demand-side flexibility and electricity demand-side flexibility simultaneously. Multi-objective genetic algorithm optimization balances revenue generation, energy costs, emissions reduction, and battery health. The integrated approach maximizes value creation across both transportation and energy domains, reducing urban emissions while enhancing grid stability through coordinated management of distributed energy resources in autonomous electric vehicle fleets.

The invention discloses an airborne laser radar sounding data processing method and system, and relates to the technical field of marine surveying and mapping and earth observation, and the method comprises the following steps: collecting original full-waveform data of an airborne laser radar sounding system, the original full-waveform data comprising infrared laser channel data and blue-green laser multichannel data; joint denoising processing is carried out on the original full-waveform data to obtain denoised waveform data, and the joint denoising processing comprises background noise modeling and removing based on machine learning and random noise filtering based on frequency domain low-pass filtering; a collaborative joint denoising strategy is formed by fusing background noise modeling based on machine learning and frequency domain low-pass filtering based on signal-to-noise ratio optimization. According to the method, complex background noise can be accurately estimated and removed, random noise can be adaptively filtered out, weak underwater echo signals are reserved to the maximum extent, and the problem of water depth information loss caused by excessive smoothness is effectively avoided.

This disclosure relates generally to system and method for estimating crop water requirement using multi-sensor data fusion. Increasing global population is imparting pressure on both agriculture for food demand and limited freshwater resources for consumption. Estimating crop water requirement reduces water demand for crop production. The method divides soil and crop into multiple vertical and horizontal profiles to estimate water balance thereby reducing the errors in estimation of crop water requirement. Additionally, the method has capability to interlink the multiple data sets such as satellite based earth observations, weather observations from IoT sensors, Weather forecasts from global circulation models, and crop knowledge base for crop water requirement estimation. The method is based on spatio-temporal modeling for multi-layer crop and soil water balance and helps to generate the additional insights on crop water requirement like moisture at different levels in soil profile, crop canopy growth at different locations.

The invention relates to the technical field of remote sensing earth observation, in particular to a satellite video multi-target tracking method and system based on space-time state propagation and progressive trajectory association, and the method comprises the steps: obtaining a target detection result and a state transition result of adjacent frames in a video sequence frame image through a target tracking model; the target detection result comprises a target detection frame position representation and a target category representation, the state transition result comprises a coordinate transition result and a foreground probability, calculating a spatial position matching degree by using an intersection-to-union ratio, and calculating an adjacent frame target appearance feature similarity by using a cosine distance; and combining the spatial position matching degree and the appearance feature similarity to calculate a target space-time matching affinity, associating each target tracking frame in each video sequence frame based on the target space-time matching affinity, and adding the tracking frames to the corresponding target trajectory fragments to generate each target tracking trajectory. The core intelligence information can be accurately and efficiently extracted from the satellite video data, and the utilization efficiency of the satellite video data is improved.

The invention discloses a large-scale complex correlation earth observation task planning method based on reinforcement learning, and relates to the technical field of task resource planning. The method comprises the following steps: acquiring historical data of earth observation task planning, and constructing a sample data set; constructing a graph neural network and a reinforcement learning network; using the sample data set to train the graph neural network and the reinforcement learning network at the same time; acquiring a demand information list, a satellite information list, a data transmission task information list and an observation information list, and processing the information lists into demand feature vectors, satellite feature vectors, data transmission task feature vectors and observation feature vectors; and inputting the four feature vectors into a trained graph neural network to obtain an environment feature vector, inputting the environment feature vector and the demand feature vector into a trained reinforcement learning network, and outputting an earth observation task planning result. The method can solve the scheduling optimization problem under the condition of multiple tasks and limited resources, improves the task planning efficiency, and can be widely applied to the fields of satellite task scheduling, intelligent manufacturing, automatic driving and the like.

The invention relates to a method of determining one or more conditions, of a geographical line, GL, or its surroundings. The method comprises: acquiring geo-referenced earth observation data representing one or more spatially overlapping imagery layers covering from an aerial or space perspective a specific region of interest, ROI, of the Earth's surface, the ROI comprising the GL; geometrically transforming the geo-referenced observation data, at least in parts, into a local internal frame of reference of the GL within the ROI to obtain a mapping of the geo-referenced observation data to respective corresponding coordinates within the local internal frame of reference of the GL; and evaluating the mapped earth observation data as represented in the local internal frame of reference of the GL according to a classification scheme to obtain therefrom evaluation data representing a classification of one or more properties of the GL or of its surroundings according to one or more conditions of the GL.

The invention discloses a method for monitoring same-scale time sequence deformation information of a complex deformation body under a multi-source earth observation technology fusion background. The same-scale deformation information is accurately extracted from the multi-source observation data based on the multi-scale and multi-dimensional deformation characteristics of a complex deformation body, and the method has important application value for building safety operation, smart city construction, geological disaster monitoring and early warning and the like. According to the method, a high-resolution earth observation system and a single Beidou navigation positioning system in China are taken as main surveying and mapping technical means, and an intelligent extraction method for same-scale time sequence deformation of massive, complex-scale and multi-dimensional monitoring data is established according to an Msplit classification estimation theory, a time sequence model and a median function.

An aspect of the disclosure provides An earth observation apparatus to be carried by a moving aerial platform or satellite for obtaining images of the surface of the earth, the apparatus comprising: an optical train having an optical field of view for imaging a region of the surface of the earth and being configured to form an image of the region at an image plane; an image sensor disposed at the image plane providing an imaging field of view; a view adjuster configured to control the optical train to: provide forward motion compensation for a stare time; and to displace the image, relative to the imaging field of view, in an across-track direction in a sequence of discrete displacement steps during each stare time; wherein the image sensor comprises a plurality of active areas, each comprising an area array detector and the active areas being spaced apart by inactive areas at the image plane wherein each active area captures a frame of image data for each discrete displacement step thereby to capture a plurality of frames for each discrete displacement step and the plurality of frames captured for each discrete displacement step are displaced in the across-track direction, relative to the imaging field of view, from the plurality of frames captured for the next discrete step.

The invention discloses a differential measurement-based satellite-borne synthetic aperture microwave radiometer imaging correction method, which comprises the following steps of: respectively selecting a reference area and a correction area in a global range, and respectively intercepting scientific data and auxiliary data in a specific time period in the reference area and the correction area based on load normal earth observation data; averaging the visibility functions intercepted in the reference area to obtain a reference visibility function; generating a reference brightness temperature and a correction brightness temperature through a simulation model by using the auxiliary data intercepted in the reference area and the correction area respectively; performing difference and inversion processing on the normal earth observation visibility function to be subjected to imaging processing by using the reference visibility function to obtain a difference inversion brightness temperature; calculating a correction coefficient by using the reference visibility function, the reference brightness temperature, the visibility function intercepted in the correction area and the correction brightness temperature; and correcting and compensating the differential inversion brightness temperature by using the correction coefficient and the reference brightness temperature to obtain the final inversion brightness temperature.

The invention discloses a remote sensing satellite area coverage method based on greedy search, and belongs to the technical field of remote sensing satellite earth observation. The method comprises the following steps: firstly, gridding an area target to be observed according to the imaging breadth of a remote sensing satellite; secondly, calculating a grid set of potential coverage of the satellite based on the breadth and the side-sway capability of the satellite within the top-crossing access time of the satellite to the regional target; and then local greedy search and multi-round iteration are carried out to determine a final imaging satellite set and an imaging sequence, and an optimized multi-remote sensing satellite collaborative observation region target scheme is obtained. The method has the advantages of being simple in processing logic, high in flexibility, high in resource utilization rate, high in optimization efficiency and the like, and is suitable for the problem that multiple remote sensing satellites cooperatively cover area targets.

The invention relates to the technical field of satellite observation task scheduling, in particular to a low-orbit satellite large-scale earth observation task self-adaptive scheduling method and system. The method comprises the following steps: generating a task allocation result according to a task candidate resource mapping table, namely generating an initial allocation scheme by using a greedy strategy of double factors of time and load, and establishing an allocation frequency memory matrix; constructing an inverse correlation selection probability model by utilizing the distribution frequency memory matrix, and outputting a task distribution result considering global revenue and load balance; task scheduling optimization is carried out based on a task allocation result, wherein conflict resolution fine adjustment is carried out by utilizing a time elastic adjustment mechanism of conflict perception; inter-satellite link collaborative rescheduling based on task characteristics; and global optimization and real-time response capability are effectively considered. According to the method, a complex joint scheduling problem is decoupled into two sub-problems with clear logic and low coupling degree, and the calculation complexity of single scheduling is greatly reduced.

This application provides a method, device, and computer-readable storage medium for evaluating the on-orbit calibration error of a microwave radiometer calibration system used in geostationary orbit. The application evaluates the on-orbit calibration error of the microwave radiometer calibration system by determining the errors of the calibration cold source, calibration heat source, Earth observation radiation brightness temperature, and Earth target brightness temperature. By separately evaluating the errors of the calibration cold source, calibration heat source, Earth observation radiation brightness temperature, and Earth target brightness temperature in the microwave radiometer calibration system used in geostationary orbit, each error is quantified, thus quantifying the on-orbit calibration error of the microwave radiometer calibration system. Furthermore, the different radiation transmission paths are considered during the evaluation of each error, making the evaluation of the sources of on-orbit calibration error of the microwave radiometer calibration system used in geostationary orbit not only effective and accurate but also highly implementable.

This invention discloses a method for collaborative Earth observation and data transmission scheduling across heterogeneous space platforms. The method employs integer encoding to represent the execution sequence of observation tasks from multiple space platforms, proposes a three-stage decoding strategy to repair infeasible chromosomes, and designs feasible observation time window selection strategies, as well as observation task insertion strategies based on time-based benefits, task urgency, and attitude transition time, to construct an initial chromosome population. Crossover operations are performed on the current population, constructing three neighborhood search operators: inter-platform exchange, intra-platform exchange, and insertion based on relaxation time, to perform local searches on the chromosomes within the current population. The algorithm terminates if the maximum number of iterations or the maximum computation time limit is reached, generating a scheme for collaborative Earth observation and data transmission scheduling across heterogeneous space platforms, providing technical support for space-based Earth observation.

The invention is applicable to the technical field of satellite remote sensing earth observation, and provides a vegetation canopy vegetation parameter inversion method based on an MOBCSM (Multi-output Band-Correlative Convolution Mixture Kernel) kernel, a storage medium and a processor. By introducing the MOBCSM kernel, a complex nonlinear relation in the hyperspectral data can be better processed, a stronger modeling capability is provided in multi-task collaborative optimization, in addition, the MOBCSM kernel can effectively model interaction between wavebands, and the precision and reliability of hyperspectral data analysis and vegetation parameter inversion are further improved. The storage medium for storing the method and the processor for operating the method also have the same technical effects.

The application discloses a kind of multi-star on-orbit cooperation observation task planning method and system, by designing heuristic initial solution generation strategy, roulette selection algorithm based on Boltzmann selection probability, adaptive crossover operator and mutation operator based on population dispersion degree, stop condition based on population convergence coefficient, from initial solution, selection operator, crossover operator, mutation operator, stop condition etc. Various angles improve the genetic algorithm for multi-star cooperative observation task planning, compared with the genetic algorithm based on circle next cross, variation, significantly improve the execution benefit of observation task and the observation number of target point, construct the scheduling system of constellation cloud computing system, reach the purpose of on-orbit cooperation multi-star efficient execution observation task.

The invention provides a radar satellite three-dimensional attitude guiding method and system, and the method comprises the steps: calculating the geocentric distance and geocentric latitude and longitude of a satellite according to satellite orbit parameter information, calculating the height of the satellite and the geodetic latitude and longitude of a droop point through a WGS-84 reference ellipsoid model, and further obtaining the geocentric latitude and the earth radius of the droop point. The position vectors of the droop point and the satellite in a WGS-84 earth-fixed coordinate system are obtained respectively, the position vectors of the droop point and the satellite are compared to obtain the position vector from the satellite to the droop point, then the position vector is converted into a satellite orbit coordinate system, and rolling and pitching guide angles are calculated. Doppler frequency deviation caused by earth rotation is compensated by adjusting the yaw guide angle. According to the method, the problem that loads such as a spaceborne radar altimeter vertically point to the earth surface of the earth reference ellipsoid model is successfully solved, meanwhile, Doppler frequency deviation generated by earth rotation is compensated, and important technical support can be provided for a subsequent radar satellite earth observation task.

The present application provides an earth observation system based on a single measuring station, and the working modes of its earth observation payload include: record first and then replay mode, in which the imaging window is earlier than the data transmission window, and the imaging window and the data transmission window do not overlap; replay first and then record mode, in which the data transmission window is earlier than the imaging window, and the data transmission window and the imaging window do not overlap, and the record file and the replay file are not the same file; replay first and then record and play mode, in which the imaging window is located in the data transmission window, and the record file and the replay file are not the same file; replay first and then quasi-real transmission mode: the data transmission window includes two data transmission segments, the first data transmission segment is used to replay historical files, and the second data transmission segment is used for quasi-real transmission, the imaging window does not overlap with the first data transmission segment, and partially overlaps with the second data transmission segment. The present application ensures the flexibility of the user's observation area, the timeliness of data, and the observation efficiency by designing a new payload mode, and effectively improves the earth observation efficiency of a single measuring station.

The invention discloses an in-orbit calibration method for correcting self-radiation of a heat mirror of a microwave imager based on reference radiation. The method comprises the following steps: calculating an included angle between the heat mirror of the microwave imager and the sun; calculating the earth observation brightness temperature of the microwave imager; calculating the observed brightness temperature of the reference microwave radiometer; simulation brightness temperature of the reference microwave radiometer and the microwave imager is obtained based on radiation transmission model simulation; calculating an observation brightness temperature deviation and a simulation brightness temperature deviation, and calculating a system error between the reference microwave radiometer and the microwave imager; based on the system error, the included angle between the microwave imager heat mirror and the sun is adopted for function relation fitting, and the heat mirror self-radiation brightness temperature of the reference microwave radiometer is calculated; the included angle between the microwave imager heat mirror and the sun is calculated on orbit in real time, and the earth observation brightness temperature of the microwave imager is corrected based on the self-radiation brightness temperature of the heat mirror. The self-radiation of the heat mirror is solved in real time by taking double deviations of observation brightness temperature and simulation brightness temperature as constraints, and the problem that the temperature of the heat mirror of the microwave imager cannot be actually measured in orbit is solved.

The present application belongs to the technical field of space-to-earth observation (satellite remote sensing) and watershed hydrology, geographical environment disciplines, and discloses a watershed scale high spatio-temporal resolution river network remote sensing information extraction method and system. After cloud and cloud shadow processing of optical remote sensing images, a simple non-iterative clustering superpixel segmentation algorithm is used to segment homogeneous landscape objects, and a hierarchical decision tree is constructed using a water body index and a vegetation index. In the area where the optical remote sensing image is seriously covered by clouds or the image is missing, the SAR image is filtered, the dual polarization water body index is calculated using the VV and VH polarization images, the maximum inter-class variance method is executed, and the image is binarized. After obtaining the water body result extracted from the remote sensing image, the river cut-off is repaired in combination with the water system diagram generated by the DEM model. The present application can automatically extract accurate, continuous and high spatio-temporal resolution river network remote sensing information, and can be expanded to global scale river network feature extraction.

We provide the system. [Solution] As a means of data collection, it has the function of receiving remote sensing data from Earth observation instruments, A function to acquire weather data from weather information providers, It has a function to collect soil data from soil condition detectors installed on the ground, A method for integrating collected data and performing data cleaning, A means of analyzing data using a generative model to generate optimized agricultural management guidelines based on crop growth and environmental changes, A system that includes means for notifying users of the above guidelines.

This invention discloses a method and apparatus for extracting three-dimensional deformation data of mining subsidence in desert areas, relating to the field of Earth observation technology. The invention calculates the angle between the normal vectors of each point in the point cloud data and performs tangent plane projection analysis to form multiple pairs of point cloud contour sets. The overall approach is based on the local geometric characteristics of the point cloud, accurately extracting feature points reflecting the shape of the point cloud contours. Then, using these multiple pairs of point cloud contour sets as registration objects, the K-4PCS and VGICP registration algorithms are employed to register the three phases of point cloud data, ensuring precise alignment and obtaining the registered point cloud and transformation matrix. The three-dimensional deformation of the land surface is extracted from the transformation parameters in the transformation matrix. This process eliminates the need for subsidence extraction based on point DEMs and planar displacement extraction based on rigid body matching, enabling accurate extraction of planar displacement in desert areas and precise acquisition of three-dimensional deformation data of the land surface caused by mining in desert regions.

This invention proposes a satellite-ground collaborative mission management method for Earth observation space cloud services, belonging to the field of satellite application and management technology. This method first identifies three main roles in satellite-ground collaborative mission management; secondly, it selects a management mode based on the urgency and complexity of the needs; then, it generates mission plans and instructions for the remote sensing satellite constellation and telemetry and control station network, and executes the missions; finally, after mission execution, data is received through the space edge cloud service center and the ground station network, thereby achieving management under a cloud architecture. This method overcomes the shortcomings of existing methods, such as difficulty in coordinating satellite-ground missions, difficulty in coordinating multiple types of users, and slow data transmission speeds. It improves the collaborative management performance of remote sensing satellite missions under a satellite-ground integrated system and can meet the application requirements of rapid, accurate, and comprehensive remote sensing satellite mission planning and management.

Synthetic aperture radar (SAR) is a type of imaging technology that can be used for a wide range of applications, including Earth observation, mapping, object tracking, change detection (e.g., Arctic ice), natural disaster monitoring, and many other uses. A high-altitude unmanned aerial vehicle for performing synthetic aperture radar (SAR) imaging comprises a fuselage, wings attached to the fuselage to provide lift to the aircraft, one or more electric propellers to provide thrust to the aircraft, a SAR payload for SAR imaging the Earth's surface as the aircraft flies, solar cells to generate power to drive one or more electric propellers and operate the SAR payload, and one or more batteries to store the electrical energy generated by the solar cells.

This invention discloses a method and system for identifying planted and natural forests based on multi-source remote sensing and spatiotemporal joint optimization, belonging to the fields of remote sensing image processing, earth observation, and dynamic monitoring of forest ecology. Addressing the problems of high label noise and disordered temporal logic in existing technologies, this invention obtains high-purity training samples through multi-stage iterative purification by fusing CCDC mutation history and deep semantic features; obtains pixel-level confidence through independent initial classification by geographic partitioning; constructs an HMM model integrating ecological prior constraints and dynamic adaptive emission probabilities for Viterbi decoding; and performs constrained spatial restoration with cross-dimensional temporal security checks. This invention effectively suppresses temporal pseudo-variables and salt-and-pepper noise, achieving high-resolution thematic mapping year by year with no temporal logical contradictions and regular spatial patches, suitable for fine-grained forest classification and compliance monitoring of zero-deforestation laws in tropical and subtropical regions.

The invention discloses a remote sensing image multi-granularity collaborative recognition method and system based on satellite edge calculation, and the method comprises the steps: obtaining a high-resolution remote sensing satellite image, carrying out the in-orbit coarse granularity screening through maximizing an efficiency score, and obtaining an interested target region; based on a distributed task unloading method, an interested target area is sent to an optimal intelligent satellite through a remote sensing satellite; and the optimal intelligent satellite performs fine-grained target recognition processing on the interested target area to obtain a ground target recognition result. According to the invention, decision making can be carried out under the condition of meeting performance and time delay constraints, and the precision of a ground target identification result is improved. The remote sensing image multi-granularity collaborative recognition method and system based on satellite edge calculation can be widely applied to the technical field of satellite earth observation.

The invention provides a rotating arc ultra-light compact space remote sensing concave mirror device aiming at the pain points that an earth observation space telescope is difficult to deploy due to a large aperture, high in cost and inconvenient to transport, an integrated double-fan-shaped paraboloid primary mirror is taken as a core, and two fan-shaped sub-mirrors are symmetrically divided based on a complete paraboloid mirror of 10m or above; a stable-shape, high-temperature-resistant and low-temperature-resistant high-performance ceramic material including ultrahigh-modulus silicon carbide is adopted, water-based colloidal forming is used as a core process, and a'thickness gradient + honeycomb 'lightweight design is matched, so that the weight is reduced by more than 40%, and the surface precision reaches lambda / 50; a mainstream rocket fairing is adapted through vertical storage, a mirror body does not need a folding mechanism, a view field is complemented by means of coaxial rotation, fan-shaped scanning equivalent view field distortion generated by rotation of a double-fan-shaped primary mirror is accurately corrected through a ground AI image restoration system, 0.1 m-level and higher ground resolution and wide-view-field collaborative observation is achieved, and the system is simple in structure and convenient to use. The device has the advantages of being sufficient in rigidity, high in reliability and adaptive to the space environment, and meets the requirements of accurate measurement and wide coverage of earth observation.

The invention discloses a hyperspectral image compression network and compression method based on multi-scale spectrum and spatial feature enhancement, and mainly solves the problems of insufficient hyperspectral image spectrum modeling, insufficient spatial feature extraction and high network complexity in the prior art. The network comprises a main encoder, a main decoder, a super-prior encoder, a super-prior decoder and an entropy model. The main encoder comprises a spectral attention gating data unit, a convolution unit and a multi-scale spatial adaptive feature attention enhancement unit, and is used for converting an input image into potential representation and removing spatial and spectral redundancy; the main decoder and the main encoder are symmetrical in structure; the super-prior encoder comprises a convolution layer and an activation layer and is used for extracting auxiliary information from the output of the main encoder; the super-prior decoder and the super-prior encoder are symmetrical in structure; the entropy model is Gaussian distribution based on output parameters of a super-prior decoder. After the network is trained, lossy compression of a hyperspectral image can be realized. The method reduces the network complexity and spectral distortion, improves the reconstruction quality of complex ground feature details, and is suitable for earth observation, meteorological monitoring and the like.

This invention discloses a space-ground coordinated radiometric characteristic calibration method for spaceborne active microwave sensors in the field of radar Earth observation technology. It constructs a space-ground coordinated calibration system consisting of a radiation reference source satellite and a ground calibration processing station. The method includes: determining the orbital parameters of the radiation reference source satellite; the satellite transmitting signals to the ground station in Earth observation mode, using a known RCS target on the ground to calibrate its own antenna gain and link gain; receiving signals from the satellite to be calibrated in Earth observation mode, accurately calculating and transmitting echo signals based on the calibrated parameters; and the satellite to be calibrated calibrating its own transmit / receive link gain based on the received echo signals. This invention can be widely applied to the on-orbit radiometric calibration of active microwave sensors such as synthetic aperture radar, altimeters, and microwave scatterometers, significantly improving calibration frequency and accuracy, supporting multi-band, high-stability quantitative remote sensing tasks, and providing reliable technical support for precise observation in fields such as ocean monitoring, weather forecasting, and topographic mapping.

The application discloses a kind of agile satellite earth observation time window calculation method, belongs to satellite earth observation technical field.The present application is in view of the method for calculating agile satellite earth observation time window by orbit recursion in the prior art, it is difficult to realize the problem of long time mission planning in orbit due to large amount of calculation.Six numbers of orbit and flight time are considered according to the orbit of earth observation satellite, and orbit recursion is carried out considering J2 perturbation, the position vector is converted into geographical longitude and latitude considering the influence of earth rotation, and the analytical expression of subsatellite point trajectory about time is established;According to the expression of satellite subsatellite point trajectory, the time when the latitude of ground target is equal is screened out, and whether the relative distance constraint is satisfied at this time is judged, so as to estimate the time when the observation condition is met;The observation attitude angle is calculated according to the relative position vector of satellite pointing target, the maximum roll angle and pitch angle constraint are considered, and the over-the-top time and observation time window are iteratively solved near the estimated time.The application is used to calculate satellite earth observation time window.

The application provides a long-distance imaging camera internal and external parameter separation calibration method based on a precision three-axis turntable. In the calibration process, two groups of light point sub-pixel coordinates are automatically collected through the precision three-axis turntable, and the corresponding relationship of the homonymic points under the pure rotation motion is constructed, so that the initial estimated value of the main internal and external parameters is linearly solved, and finally, all the camera internal and external parameters are iteratively optimized with the minimum homonymic point corresponding error as the target. In the solving process, the calibration point vector is eliminated without solving. The application is mainly applied to the high-precision calibration of long-distance and large-view-field imaging cameras in the aviation and aerospace fields before leaving the factory, and has important significance for realizing the high-precision visual measurement of the aviation and aerospace earth observation and celestial body sensing.