96 results about "Satellite imaging" patented technology

The invention provides an intraday high-frequency automatic monitoring method and system for lake cyanobacterial bloom based on a GOCI-II satellite, and aims to solve the problems that an existing method is susceptible to interference of thin cloud, low in recognition precision, high in false positive rate, low in efficiency and the like, and the processing flow depends on manpower. The system is based on an improved AFAI index, fine cloud detection, cloud expansion processing and classification correction strategies are combined, misrecognition caused by thin clouds and shadows is effectively restrained, and the extraction accuracy and robustness are improved. The system has the whole-process unattended processing capacity from GOCI-II data automatic downloading, preprocessing, algal bloom recognition, thematic map making to report output, can generate a monitoring report within one hour after satellite imaging, and supports intra-day multi-temporal cyanobacterial bloom dynamic monitoring. The method has been successfully applied to lakes such as Taihu Lake, lakes, Chaohu Lake and Hongze Lake, is particularly suitable for monitoring and early warning cyanobacterial bloom in large and medium lakes, and has wide application prospects in the fields of water environment supervision, water quality risk control, ecological assessment and the like.

The invention relates to a remote sensing satellite group adaptive task planning method and system based on a large language model, and the method comprises the steps: building an optimization model based on decision variables, constraint conditions and optimization targets of remote sensing satellite group task planning; generating an initial task planning strategy by adopting a greedy algorithm based on the optimization model; performing iterative optimization on the initial task planning strategy through a large language model, generating a new round of task planning strategy in each iteration, performing scoring by taking an optimization target as an evaluation function, stopping optimization until a preset number of iteration optimization times is reached, and outputting the task planning strategy with the highest score; and based on the task planning strategy with the highest score, performing remote sensing satellite group adaptive task planning. According to the method, multi-satellite distributed task planning can be effectively carried out on the dynamic task, the task income is improved, and the satellite imaging time consumption is reduced.

The invention provides an AIS beacon guided SAR satellite imaging method fused with a Beidou short message. The method comprises the following steps: receiving a target imaging instruction; analyzing the acquired AIS beacon signal of each ship, and extracting ship characteristic attribute information and state information of each ship; matching the ship characteristic attribute information of each ship with the target identification information, and screening out at least one target ship; based on the state information and orbit parameters of the satellite, selecting at least one target to be imaged from the at least one target ship, and generating imaging task parameters; controlling an SAR load to execute imaging operation on a corresponding area of the at least one to-be-imaged target, and generating original SAR imaging data; and the data are transmitted back to a ground terminal according to the priority level through a dual-channel transceiving channel, so that the dynamic response capability of a satellite is improved, the reliability of a data transmission link is enhanced, and the real-time performance of emergency imaging data is improved.

The invention relates to the technical field of spaceflight microwave remote sensing, and provides a spaceborne synthetic aperture radar in-orbit autonomous task planning method, device and equipment, and the method comprises the steps: obtaining imaging parameter information; the imaging parameter information is determined by the satellite imaging system based on task annotation information, orbit information and an imaging parameter preset table, and the task annotation information is obtained by the satellite imaging system by analyzing observation requirements of a user; the orbit information is determined based on satellite forecast information. According to the method, imaging parameter information is determined by a satellite imaging system based on task uploading information, orbit information and an imaging parameter preset table, partial parameter calculation and instruction generation processes of traditional satellite-borne SAR task planning are moved to a satellite, manual calculation and ground uploading steps are omitted, and dependence of the task planning process on ground calculation is reduced; the task uploading information is obtained by analyzing the observation demand of the user through the satellite imaging system, the observation demand can be uploaded in advance, satellite resources are fully utilized, and the task execution efficiency is greatly improved.

The invention discloses a satellite image definition improving method based on elliptic Gaussian distribution, and relates to the technical field of remote sensing image processing, and the method comprises the steps: calculating and generating motion data according to collected physical imaging parameters, and constructing a reference motion vector based on the motion data, the motion data comprising a long-axis reference value and a reference fuzzy direction angle; a constraint space is constructed based on statistical characteristics of a real satellite image, and random degradation parameters are collected from the constraint space and comprise a long-axis disturbance item, a direction angle jitter item and a short-axis standard deviation; performing fusion processing on the reference motion vector and the random degradation parameter to generate a composite elliptical Gaussian degradation convolution kernel; according to the method, a long-axis reference value, a reference fuzzy direction angle, a random degradation parameter and alignment reference data are introduced in the construction process of a training sample pair set, so that the training sample pair better fits real satellite imaging in the aspects of fuzzy structure and space matching.

The invention relates to an agile satellite visibility analysis method based on an along-longitude push-broom mode, relates to the technical field of satellite task planning and visibility analysis, and solves the technical problem that an existing target visibility analysis method is difficult to accurately reflect a real visibility state in a satellite continuous imaging process. The method comprises the following steps: acquiring an imaging center point coordinate, an imaging duration, satellite imaging parameter information, satellite orbit information and a target shooting period; the visibility of the imaging center point in the shooting period is calculated, division is carried out according to the number of orbital circles, and a visible information set of the center point is obtained. The agile satellite visibility analysis method based on the along-longitude push-broom mode is suitable for efficient visibility calculation of an agile optical remote sensing satellite and oriented to an along-longitude imaging scene, the visibility state of a target in the imaging process can be accurately evaluated on the basis of considering satellite attitude maneuver characteristics and orbit constraints, and the accuracy of the visibility analysis is improved. Therefore, accurate support is provided for task arrangement and resource scheduling.

The invention relates to the technical field of geological disaster monitoring, and discloses an InSAR hidden danger point automatic identification method based on hotspot analysis, and the method comprises the steps: S1, carrying out the mask and format conversion of an unreliable region of an InSAR deformation field; due to geometric distortion caused by imaging geometry of satellites, areas with low vegetation coherence may mislead subsequent hotspot analysis. According to the invention, through combination of remote sensing and GIS technologies, accurate screening models and algorithms are respectively established, and automatic and efficient elimination of unreliable areas is realized; a hotspot analysis technology is introduced into the field of automatic extraction of an InSAR deformation field, and element points are innovatively set according to characteristics of InSAR deformation data and actual requirements of geological hidden danger detection and serve as extraction standards of reliable deformation points with spatial clustering properties when specific conditions are met. The method can accurately extract the points really having the possibility of geological hidden troubles from the complex deformation data.

The present invention discloses a method for mission planning of a giant remote sensing constellation for regional targets, comprising the following steps: Step 1, construct a global regional reference system, determine the reference grid of the regional target and the corresponding observation grid, and obtain the observation grid information; Step 2, determine the observation priority, and calculate the comprehensive observation priority of each reference grid; Step 3, pre-allocate the constellation mission, generate the one-to-one correspondence between the observation grid and the imaging satellite within the observation demand period in the observation demand information, and obtain the constellation mission pre-allocation plan; Step 4, single-satellite mission planning, generate the satellite imaging and data transmission plans in the single-satellite mission planning stage based on the constellation mission pre-allocation plan, satellite special constraint conditions, satellite imaging characteristic parameters, satellite data transmission scheme and its optimization strategy. The present invention fully considers the constellation orbit heterogeneity, highly symmetric spatial structure and the law of global periodic motion, which helps to achieve the instant observation of the giant remote sensing constellation.

The invention discloses a satellite planning and scheduling method, medium and equipment based on enhanced multi-population inheritance, and relates to the field of multi-satellite imaging task scheduling, and the method comprises the steps: constructing a constraint model and a target function of multi-satellite task scheduling; calculating the conflict degree of the visible time window of each satellite resource, and allocating the visible time window with the conflict degree of 0 to a task to complete scheduling preprocessing; generating satellite resources and visible time window initial solution individuals of satellite task scheduling by adopting a bisection method; a double-population genetic algorithm is adopted, one population is used for exploring a new allocation scheme, the other population is used for optimizing a task planning result under a specific allocation scheme, and population communication is carried out based on reinforcement learning; and performing task insertion based on time relaxation according to a multi-satellite task scheduling solution obtained by the double-population genetic algorithm, and if task insertion cannot be performed, performing task replacement to obtain a final scheduling scheme. According to the method, the problem of complex multi-satellite imaging scheduling can be solved.

A system, method, and device for predicting a risk of wildfire are provided. The system includes a satellite imaging device for collecting data covering a target area and a processing server including an indices module for processing the data to generate key vegetation indices, a map generation module configured to generate weather and static maps, an analysis module configured to analyze historical wildfire data to identify past fire locations in the target area, an integration module configured to integrate the received, generated, and analyzed data to obtain a comprehensive dataset for the target area, and a risk prediction module configured to analyze the comprehensive dataset using a risk prediction model trained to predict the risk of wildfire for the targeted area, the risk prediction model including a machine-learning-based pattern detection model for receiving the comprehensive dataset as an input and generate prediction data describing a predicted risk as an output.

The invention discloses a transmission line icing state analysis and early warning method and system based on a synthetic aperture radar satellite image, and belongs to the technical field of radar satellite remote sensing monitoring, and the method comprises the steps: S1, carrying out the data collection of a synthetic aperture radar image of a transmission line monitoring region based on meteorological condition forecasting, and carrying out the data collection; obtaining background data of the power transmission conductor in an uniced state; s2, performing data acquisition and preprocessing based on the synthetic aperture radar satellite image in the icing state of the power transmission line monitoring area to obtain icing data in the icing state of the power transmission line; and S3, performing analysis and early warning based on the background data of the power transmission conductor in the uniced state and the iced data of the power transmission conductor in the iced state. According to the invention, through the SAR satellite imaging technology, rapid power transmission line icing state monitoring and real-time early warning work are carried out, the problem of limited monitoring capability and range of current manual and online monitoring sensors is solved, and new added value is provided in the aspect of power transmission line operation and maintenance.

The invention discloses a distributed satellite metadata coverage analysis method based on recursive segmentation and aggregation. The method comprises the following steps: recursively segmenting a target space region to be analyzed into a plurality of equally divided grids; performing coverage analysis on the metadata set corresponding to each equally-divided grid based on a distributed computing framework, and generating a basic metadata coverage area graph and a basic coverage area corresponding to each equally-divided grid; and aggregating metadata coverage area graphs and coverage areas corresponding to all equally divided grids, and outputting a coverage analysis result. According to the method and the device, coverage calculation is fractionally decomposed into small-area calculation according to the requirement of matching calculation of the coverage range of the ten-million-level metadata and the target space area, then the coverage result of the whole area is obtained through recursion and merging, the method and the device are suitable for achieving the purpose of quickly calculating the coverage graph and the coverage rate by using a distributed calculation framework, and the calculation efficiency is improved. The coverage range of the satellite metadata set can be visually displayed; and meanwhile, the observation missing range of the target space region can be dynamically analyzed and calculated, so that subsequent satellite imaging planning is facilitated.

This invention proposes a high-dynamic real-time yaw rate adjustment and image shift compensation optical scanning imaging method and device, belonging to the field of optical remote sensing technology. It solves the technical problem of ensuring the quality of satellite on-orbit imaging. The method includes: using a combined imaging mode of vertical orbit scanning with a tilting mirror and pitch return to perform high-dynamic vertical orbit wide-area scanning imaging, determining the satellite imaging motion law, and establishing a high-precision multi-coordinate system object-image geometric mapping and image shift calculation model to calculate the variation law of image shift compensation parameters; measuring satellite orbit information, attitude information, and camera optical axis pointing information through a high-precision sensor, predicting the camera optical axis motion law using filtering, and substituting it into the image shift calculation model to obtain the line frequency; and achieving graded yaw rate adjustment through fixed yaw rate adjustment, curve fitting, and adjustment of the installation angle. This invention is applied to optical remote sensing satellites with high-dynamic vertical orbit wide-area scanning imaging, achieving on-orbit image shift compensation imaging that balances wide-area coverage and high resolution.

The invention discloses a ground station control method and system for executing real-time shooting and real-time transmission tasks by combining satellites. Belongs to the technical field of remote sensing satellite ground station control. The method comprises the following steps: defining a task plan template executed by a ground station, wherein the task plan template comprises a task plan type; a satellite data transmission stage is divided into different time nodes, and the control process of each task plan is divided through the time nodes; and selecting a corresponding task plan according to the actual working condition of the satellite, and executing a corresponding control process. The method can be combined with a satellite to complete orderly and rapid switching of modes of a ground station in one arc section, so that it is possible to complete instruction uploading to the satellite, satellite attitude adjustment, satellite imaging and data transmission, data receiving and production, and data identification and interpretation in one arc section.

The invention discloses a double-shaft solar wing control method and device giving consideration to flexibility suppression, and belongs to the technical field of spacecraft control. The method comprises the following steps: respectively calculating nominal angles of an A axis and a B axis according to a unit vector of the sun in a satellite orbit system; wherein the nominal angle of the B axis is determined according to a flexible vibration suppression interval after discretization processing; the flexible vibration suppression interval is an angle avoiding interval set for avoiding the resonant frequency; calculating control errors of the A axis and the B axis according to the nominal angles and the rotation angle measurement values of the A axis and the B axis; and according to the satellite imaging state and the state of the double-axis solar wing, the rotation of the A axis and the rotation of the B axis are controlled by using the control error so as to eliminate the sun alignment error of the double-axis solar wing. According to the invention, the resonance interval between the driving frequency and the axial vibration frequency can be avoided, and the resonance risk is reduced.

The invention discloses a surface temperature and downscaling temperature inversion method based on remote sensing data, and belongs to the technical field of remote sensing data processing. The method comprises the following steps: 1) fusing measured data of a weather station at an interval of three hours all day with Landsat 8 / 9 satellite imaging time through a cubic spline interpolation method, generating a space-time matched land surface temperature (LST) inversion result, and eliminating abnormal values by using a Kutta distance method to optimize model precision; (2) the surface emissivity is calculated based on an NDVI threshold value method, and the vegetation coverage (Pv) is dynamically determined through an NDVI empirical threshold value (NDVIsoil = 0.05, and NDVIeg = 0.70); and 3) in a Google Earth Engine (GEE) platform, in combination with Landsat 8 / 9 (30 meters) and Sentinel-2 (10 meters) multi-source satellite data, constructing a random forest model with NDVI, NDBI and NDWI as inputs, downscaling the LST to a resolution of 10 meters, and smoothly improving detail precision through regression residual error. The problems that a traditional method is low in resolution, large in space-time matching error and remarkable in abnormal value interference are solved, the inversion precision index R is larger than or equal to 0.85, RMSE is smaller than or equal to 1.5 DEG C, and the method is suitable for urban heat island effect analysis, environment monitoring and climate research.

The invention provides a multi-satellite observation planning method and system based on a reinforcement learning algorithm, and the method comprises the steps: constructing a ground grid, a satellite in-orbit imaging geometric model, and a satellite imaging strip construction model, and taking the maximization of the coverage of a plurality of satellite strips on the ground grid as an optimization target. A PPO reinforcement learning algorithm is utilized to select a deflection angle and an imaging time action space of each satellite, imaging strip distribution of each satellite is generated according to the deflection angle and the imaging time action of each satellite, a multi-satellite imaging strip coverage problem is solved, a multi-satellite imaging strip coverage strategy is executed, and multi-satellite earth imaging coverage is realized. According to the invention, the scheme of the maximum coverage target of the affected area can be planned from the deflection angles and imaging time actions of a plurality of satellites in the emergency environment.

Intelligent In-orbit Micro-vibration Suppression System for Satellites. It belongs to the technical field of spacecraft systems, specifically involving the technical field of vibration suppression for remote sensing satellites. It solves the problem that the existing variable-parameter satellite vibration isolators cannot be actually controlled and applied. The system includes a variable-parameter satellite vibration isolator, a central control unit, and a power distribution and thermal control unit; the central control unit: includes a rotational speed acquisition module, a parameter calculation module, and a temperature control module; the power distribution and thermal control unit: includes a first power distribution and thermal control unit and a second power distribution and thermal control unit; the second power distribution and thermal control unit receives the temperature control command from the temperature control module and supplies power to the heating wire in the variable-parameter satellite vibration isolator according to the temperature control command. The system of the present invention can be applied in the fields of remote sensing satellite assembly and manufacturing, remote sensing satellite vibration suppression, and remote sensing satellite imaging system design.

The invention discloses an autonomous multi-target tracking method based on dynamic adjustment of a position relation between targets, and belongs to the field of remote sensing satellite task execution. According to the method, a plurality of targets in an imaging area are selected as follow-up tracking targets according to user requirements, and an initial tracking task is formed; and when each tracking target cannot be located in the same view field along with the movement in each direction, a new task is adaptively and dynamically split while the original task is continued to be executed. And the new task covers the target which cannot be continuously covered in the view field of the original task by adjusting the satellite imaging pointing area. And a plurality of imaging tasks are alternately executed, and imaging direction adjustment is carried out among the tasks, so that continuous coverage imaging and tracking of all tracking targets are realized. According to the invention, the efficiency of multiple target tracking tasks is improved, and the satellite target tracking capacity is improved.

The invention discloses a satellite imaging jitter measurement system based on area array detection. The satellite imaging jitter measurement system comprises a camera management controller, a camera main body, an imaging / jitter measurement detector and a signal processor, wherein the camera management controller receives a primary power supply, a bus and a second pulse signal from a satellite, and manages and controls the camera main body, the imaging / jitter measurement detector and the signal processor; the camera main body is used for imaging a ground object to a rear focal plane of the camera main body; the imaging / jitter measurement detector is mounted on the rear focal plane of the camera main body, acquires an object optical image at the rear focal plane of the camera main body, converts the object optical image into an image electric signal through photoelectric conversion, and transmits the image electric signal to the signal processor; and the signal processor is used for receiving the image electric signal, processing the image electric signal and outputting the image electric signal to the data transmission compression encoder. The satellite imaging quality is effectively improved.

The invention discloses a future beneficial distributed satellite online scheduling method for emergency task arrival, and the method comprises the steps: building an emergency task arrival-oriented satellite online scheduling model for solving a problem that an SOS-ET problem lacks a standardized mathematical model and a high-performance distributed online task planning algorithm; the invention also provides a future beneficial distributed satellite online scheduling algorithm for emergency task arrival, and the algorithm comprises a distributed satellite online scheduling algorithm with beneficial bid invitation efficiency expectation and a distributed satellite online scheduling algorithm with beneficial bid invitation efficiency expectation. Therefore, the situation that low-income tasks arriving at the early stage occupy precious satellite imaging resources in the SOS-ET problem is avoided, and resources are reserved for high-income tasks at the later stage.

The invention provides a satellite imaging and data transmission joint scheduling method based on brainstorm optimization. The method comprises the following steps: generating an initial request population; adjusting the execution sequence of each request in the initial request population to obtain a target request population; determining a conflict request population corresponding to the current request in the target request population, and performing iterative optimization on the conflict request population through a niche-based brainstorm optimization algorithm, so that the current request and the requests in the corresponding conflict request population are successfully scheduled; and removing the current request and the conflict request corresponding to the current request from the target request population, and continuing to determine a conflict request population corresponding to the next request in the new target request population until the target request population is empty, so as to complete the joint scheduling of satellite imaging and data transmission. According to the method, the feasibility and the effectiveness of the algorithm can be remarkably improved, so that the joint scheduling of satellite imaging and data transmission is realized.

A system, method, and device for predicting a risk of wildfire are provided. The system includes a satellite imaging device for collecting data covering a target area and a processing server including an indices module for processing the data to generate key vegetation indices, a map generation module configured to generate weather and static maps, an analysis module configured to analyze historical wildfire data to identify past fire locations in the target area, an integration module configured to integrate the received, generated, and analyzed data to obtain a comprehensive dataset for the target area, and a risk prediction module configured to analyze the comprehensive dataset using a risk prediction model trained to predict the risk of wildfire for the targeted area, the risk prediction model including a machine-learning-based pattern detection model for receiving the comprehensive dataset as an input and generate prediction data describing a predicted risk as an output.

The present application relates to a kind of linear array swing scan type optical satellite on-orbit geometric calibration method based on equivalent surface array, comprising the following steps: step 1, by image matching or artificial measurement method, from high-precision digital orthophoto map and digital elevation model, obtain the ground control point on the single pendulum satellite image;Step 2, according to the geometric relationship between the rotating scanning mirror, motion compensation mirror and linear array CCD in satellite imager and its imaging process, construct linear array swing scan type optical satellite geometric calibration model based on equivalent surface array;Step 3, using ground control point, solve linear array swing scan type optical satellite geometric calibration parameter.The present application can realize linear array swing scan type optical satellite high-precision on-orbit geometric calibration, thereby providing support for linear array swing scan type optical satellite image high-precision geometric processing.

The invention discloses a hyperspectral target height inversion method and device based on a radiation transfer model, and belongs to the field of remote sensing data analysis. The method comprises the following steps: acquiring a corresponding relation between atmospheric height and atmospheric temperature in the weather based on atmospheric data, and establishing a relation equation between target surface temperature and atmospheric temperature to determine the corresponding relation between atmospheric height and target surface temperature in the weather; sequentially simulating and calculating target spectrum entrance pupil radiation brightness and target center brightness temperature so as to transmit and determine a target center spectrum brightness temperature curve corresponding to each atmospheric height under the weather; and after wave band selection is carried out based on channel correlation of the target center spectrum brightness temperature curve corresponding to each atmospheric height, spectral angles of the real single-star image brightness temperature curve and the target center spectrum brightness temperature curve under each atmospheric height are respectively calculated, so that the atmospheric height with the highest spectral similarity is determined as the target height obtained by inversion. Therefore, the height inversion of the single-satellite imaging aerial target is realized.

A method for predicting and analyzing the real-time image transmission capability of remote sensing satellite point targets belongs to the field of satellite mission planning and data transmission technology. Without relying on third-party simulation software, it achieves automated analysis of the real-time image transmission capability of point targets through geometric analysis under imaging attitude and joint determination of time windows. It is used to automatically determine whether a ground point target meets the condition of "real-time image transmission after imaging" under the condition that the satellite imaging attitude is not adjusted, comprehensively considering the satellite imaging attitude, phased array antenna beam scanning angle limitations, and imaging-to-data transmission time constraints. This avoids reliance on manual simulation and calculation, improving analysis efficiency and accuracy.

This invention discloses an intelligence generation method and system based on feature fingerprint storage and spatiotemporal geometric correction, belonging to the field of intelligent remote sensing image processing technology. The method involves: accessing heterogeneous data streams generated from multi-source remote sensing images in a synchronized time sequence; inputting a shared backbone network and a modality adaptation layer to generate a current feature stream in a unified semantic space; asynchronously retrieving historical baseline features from an in-memory feature fingerprint database based on geographic coordinates; fusing satellite imaging parameters with the current feature stream and inputting it into a spatial transformation network, resampling historical baseline features using a regression transformation matrix to achieve spatiotemporal geometric correction in the feature domain; weighted fusing of the current feature streams from each modality to generate a fused feature stream; and parallel interpretation and semantic encapsulation of the fused feature stream to generate a natural language intelligence report. This invention reduces memory usage and data throughput, shortens the intelligence generation cycle, reduces the false alarm rate, and achieves synergistic optimization of timeliness, accuracy, and automation.

The invention provides a satellite imaging control method and device, computer equipment and a readable storage medium. The method comprises the following steps: acquiring image quality attribute information of first real-time imaging of a target satellite to a satellite concerned position; if the image quality attribute information of the first real-time imaging is within a preset low-quality range, adjusting a first imaging control parameter of the target satellite; acquiring image quality attribute information of second real-time imaging of the target satellite on the satellite concerned position; if the image quality attribute information of the second real-time imaging is within a preset low-quality range, acquiring imaging quality associated information of the target satellite; and adjusting a second imaging control parameter of the target satellite based on the imaging quality associated information, the second imaging control parameter including an imaging gain. According to the technical scheme, the satellite imaging quality is improved.

The present application relates to the field of aerospace technology, especially to a kind of earth observation satellite attitude controller parameter self-tuning method, the scheme includes: obtaining the desired direction and actual direction of satellite, and determining the control torque of flywheel, the satellite is earth observation satellite;Based on the control torque, obtain initial PID parameter, initial PID parameter is PID controller simulation parameter;Based on the PID controller simulation method of flywheel physical constraint, construct the fitness function of PID controller simulation parameter based on different satellite imaging mode;Satellite attitude control is simulated by PID controller simulation parameter, based on fitness function and initial PID parameter, the optimal fitness corresponding to target PID parameter under each satellite imaging mode is determined by iterative updating through particle swarm algorithm, the optimal solution of PID parameter is target PID parameter by using particle swarm algorithm combined with fitness function for iterative updating, the accuracy and efficiency of parameter setting are improved.

The invention provides an optical remote sensing satellite drift angle compensation method and system considering a camera off-axis angle. The method comprises the following steps: 1, calculating a satellite attitude angle at an imaging starting moment; 2, calculating a drift angle at a satellite imaging moment; 3, calculating the compensation angle of the satellite rotating around the visual axis of the camera; and 4, calculating a new attitude angle after satellite drift angle compensation. The method fully considers that an off-axis angle exists between the optical axis and the visual axis of the camera when the optical system is designed. Therefore, when drift angle compensation is carried out, the camera view field center can be ensured to be unchanged, the drift angle compensation residual error can be reduced, the calculation efficiency can be considered, the method can be popularized and applied in orbit, the imaging quality of an optical remote sensing satellite is improved, and the maximum observation benefit is obtained.