978 results about "Ground station" patented technology

The invention relates to power transmission line unmanned aerial vehicle inspection, and discloses a power transmission line unmanned aerial vehicle inspection path dynamic planning system, which comprises a quantum high-precision positioning unit, an environment perception and electromagnetic field modeling unit, a dynamic path planning unit, an unmanned aerial vehicle flight control unit and a ground station task management unit. The quantum positioning unit fuses quantum inertial navigation, GNSS and quantum magnetometer data to improve the positioning precision under strong interference; the environment sensing unit obtains a three-dimensional environment and electromagnetic field distribution of the power transmission line; the path planning unit dynamically optimizes an inspection path based on positioning and environment information; the flight control unit performs accurate execution; and ground station management tasks and data analysis. The anti-interference positioning precision of the unmanned aerial vehicle is remarkably improved, accurate path planning and electromagnetic field avoidance are realized, the inspection risk is effectively reduced, and the efficiency, the safety and the adaptability are improved.

The present invention provides an unmanned aerial vehicle-based electric power patrol inspection control method and system. The method comprises: creating a flight path on the basis of an electric power patrol inspection area, and collecting images and position information of electric power devices by means of various types of devices carried by an unmanned aerial vehicle, the images and the position information being transmitted to a receiving terminal at a ground station in a wireless transmission mode; the ground station receiving the images and the position information that are collected in real time, processing and analyzing the images to obtain analytic status, such as defects, damage and corrosion, of the electric power devices; and, on the basis of the analytic status from the ground station, using the position information as distinguishing features to generate an electronic patrol inspection report, providing service lives, maintenance costs and maintenance measures of the electric power devices on the basis of the electronic patrol inspection report, and notifying maintenance staff of the position information of the electric power devices. The system comprises an unmanned aerial vehicle control module, an image processing and analysis module and an electronic patrol inspection report generation module. The present invention is of great significance to maintenance and management of electric power devices.

The invention relates to the technical field of wind field simulation, and provides a wind field numerical simulation method based on multiple meteorological data sources. The objective of the invention is to solve the problems of large simulation error, rough terrain boundary processing and poor turbulence model parameter adaptability caused by non-uniform coverage of a single data source, insufficient precision and unscientific multi-source fusion. The method is characterized by comprising the following steps: step 1, constructing a CFD three-dimensional grid based on a geometric model of a target area; 2, collecting original data of a ground station, satellite remote sensing, numerical forecasting and the like; 3, performing standardized preprocessing (abnormal value elimination, missing interpolation, radiation / geometric correction and resampling), determining a multi-source fusion weight by combining historical data analysis, and generating comprehensive meteorological data by adopting a weighted average method; and 4, inputting the comprehensive data into a CFD-RANS model, dynamically adjusting turbulence parameters, accurately setting terrain boundary conditions, and obtaining a wind field space-time distribution result through numerical solution. According to the invention, through combination of multi-source data fusion and CFD simulation, the wind field simulation precision and stability are improved.

The invention relates to the technical field of unmanned aerial vehicle detection and recognition, in particular to an unmanned aerial vehicle detection system and method based on vision, laser radar and sound waves, and the system comprises a sensor unit, a data processing fusion unit and a target recognition tracking unit. The data processing fusion unit performs multi-source data alignment and weighted fusion to extract texture, shape and color features of the image, point cloud generates a depth map, sound wave signals are mapped into a two-dimensional feature map, and weights are dynamically distributed based on sensor reliability to generate a unified feature map; the target identification and tracking unit identifies the type of the unmanned aerial vehicle by using the optimized deep learning model and realizes accurate prediction and updating of position and speed states in combination with Kalman filtering, and the decision response unit triggers sound-light alarm and wireless alarm for the non-cooperative unmanned aerial vehicle in real time and transmits target dynamic information to the ground station. And the target detection accuracy of the unmanned aerial vehicle in a complex environment is improved.

The invention discloses a reliable communication system based on a publishing and subscribing mode in a satellite-ground weak network environment, and aims to solve the problems of high round-trip delay, limited link bandwidth, high instantaneous packet loss rate, easiness in blocking and switching influence of links and the like in a data transmission process between a low-orbit satellite and a ground station. A publishing and subscribing model is introduced into an application layer to realize service logic decoupling, deep fusion with an underlying enhanced QUIC transmission protocol is realized, and mechanisms such as message persistence, breakpoint resume, forward error correction and connection migration are combined, so that stable, orderly, complete and safe transmission of service data can still be ensured under the conditions of link instability, quality fluctuation and communication interruption, and the service data transmission efficiency is improved. And high availability and continuity of a satellite-ground communication task under a weak network condition are realized.

The invention relates to a mineral reserve dynamic monitoring method and system based on satellite remote sensing and a block chain. The method comprises the following steps: acquiring original remote sensing data and metadata of a mining area, executing hash operation on the data by utilizing a satellite-borne trusted execution environment to generate integrity proof, and performing digital signature to construct a trusted data packet; transmitting the data packet to a ground station to verify the validity of the signature, extracting verified data, and submitting the verified data to a block chain for evidence storage; based on the on-chain evidence storage data, using a deep learning model to extract earth surface features and calculating reserves changes; and finally, a reserve change result is returned to the block chain, and dynamic supervision and early warning are realized through an intelligent contract, so that a technical system from data source credible guarantee, transmission process tampering prevention, reserve intelligent calculation to supervision automatic execution is constructed. The problems that in traditional mineral product monitoring, the authenticity of a data source is lack, the processing process is not traceable, and supervision response is lagged are solved, and the reliability, auditing performance and supervision timeliness of a mineral product reserve dynamic monitoring result are improved.

The invention relates to the technical field of ocean data processing and intelligent reconstruction, and particularly provides an ocean spatio-temporal data interpolation method based on remote sensing condition information diffusion. The method comprises the following steps: processing observation data of multiple sites on the ground and remote sensing data of L4 ocean to obtain an observation data set, a remote sensing data set and data sets with different missing rates; respectively carrying out standardization and distribution alignment processing on the observation data set and the remote sensing data set to obtain preprocessed data, and obtaining a trained model; according to the method, an interpolation framework based on a conditional diffusion mechanism is constructed, and interpolation reasoning is carried out for data sets with different missing rates through a trained model, so that the accuracy of interpolation of the missing values of observation data is improved, and the physical rationality and the overall continuity of an interpolation result are ensured.

The invention discloses a satellite antenna dynamic pointing calibration method and system based on satellite autonomous gradient optimization, relates to the technical field of satellite communication, and realizes closed-loop calibration without ground intervention by processing signal to noise ratio (SNR) data uploaded by a ground station on a satellite in real time and combining a multi-physical field coupling model of a temperature and stress sensor. And the pointing error in a dynamic environment is reduced from more than 2.0 degrees of a traditional scheme to less than 0.3 degrees.

The invention relates to the technical field of image data processing, and discloses an AI target change detection method fusing a time sequence remote sensing image, which comprises the following steps of: calculating a difference information entropy value of a remote sensing image on a satellite-borne edge calculation unit, and comparing the difference information entropy value with a trigger threshold value; only when the information entropy value is higher than the threshold value, the change area is extracted to form an incremental information packet to be transmitted to the ground; and after analyzing the incremental information packet, the ground station generates an instruction according to the identified environmental interference characteristics and regional stability, feeds back the instruction to the satellite-borne unit, and bidirectionally adjusts a trigger threshold value. According to the invention, an information screening decision is preposed to a data generation source, so that invalid transmission of massive invariable background data is avoided; therefore, the acquisition delay of the key change information is obviously reduced; the established satellite-ground closed-loop feedback mechanism enables the whole monitoring method to continuously optimize the judgment standard during use, and the applicability and reliability of the method are improved.

The invention discloses a multi-mode unmanned aerial vehicle system and method for detecting the thickness of a bridge concrete protection layer. The system comprises a multi-mode unmanned aerial vehicle platform, a contact type mechanical arm, an electromagnetic induction steel bar detection module, a wireless data transmission module, an area array laser radar module and a binocular camera module. The contact type mechanical arm is installed on the unmanned aerial vehicle platform and used for executing contact type nondestructive testing. The electromagnetic induction steel bar detection module is installed at the tail end of the contact type mechanical arm and used for making contact with the bridge surface and measuring the thickness of a steel bar protection layer. The wireless data transmission module is installed on the unmanned aerial vehicle platform and used for returning the video of the view angle of the unmanned aerial vehicle to the ground station operation platform in real time, and the ground station operation platform observes and controls the unmanned aerial vehicle according to the returned video; the area array laser radar module is installed below the contact type mechanical arm and used for carrying out pose estimation and obstacle avoidance during adsorption mode switching. The binocular camera module is arranged at the front end of the contact type mechanical arm and used for collecting images of a detected area and conducting unmanned aerial vehicle autonomous positioning.

The invention discloses an in-orbit pointing deviation correction method for a two-dimensional mechanical antenna oriented to a panel satellite spot beam. The method comprises the following steps: acquiring an azimuth angle, a pitch angle and telemetry information of an antenna pointing to a ground station in real time in an in-orbit manner; reversely calculating a gain difference value between the actual signal and the theoretical signal; judging whether the gain difference meets the pointing precision requirement or not, and if not, inversely calculating the deviation angle of the actual pointing vector and the theoretical pointing vector and the actual pointing vector; a Gauss-Newton method is adopted to solve an optimal theoretical pointing vector; resolving an installation matrix pointed by the matching theory and adjusting an antenna installation matrix; and repeating the steps to form a closed loop until the gain difference meets the precision requirement. According to the method, three-dimensional installation matrix correction is adopted to replace traditional zero correction, closed-loop feedback and nonlinear optimization are combined, multi-source error high-precision compensation is achieved, the engineering feasibility is high, the in-orbit multi-satellite batch correction requirement of the panel satellite is met, and the communication system reliability and the data transmission rate are remarkably improved.

The invention discloses a method for aggregating ocean buoy data, which comprises the following steps of: establishing a space-time correlation model according to the spatial distribution density of buoy clusters and the dynamic characteristics of an ocean environment, and adaptively dividing buoy groups with a data compression cooperative relationship; performing a data-related compression operation within the buoy group; constructing a transmission priority dynamic sorting engine, and calculating a dynamic weight coefficient; performing hierarchical packaging processing on the differential coding data, distributing enhanced forward error correction coding resources for high-priority data, and reserving redundant transmission time slots; the method comprises the following steps: receiving a hierarchical data packet through a low-orbit satellite and executing on-satellite preprocessing, reconstructing an original data stream by using a distributed decoder, and meanwhile, fusing multi-dimensional space-time related data to generate an aggregated data product; and finally, the aggregated data product is transmitted to a ground data center through a satellite downlink. According to the invention, uplink data volume is reduced, disaster monitoring timeliness is improved, ground station processing load is reduced, and system environment adaptability is enhanced.

Systems and methods for autonomous space-mission coordination integrate ground-based prediction with on-orbit execution. A processing system in a ground station may ingest multi-source environmental data, produce near-term nowcasts through an prediction model, rank pending spacecraft tasks against current resource telemetry, select a high-value task subset, convert the subset into time-tagged command packets, and transmit the packets through a communications link. A processing system aboard each spacecraft may receive the packets, merge them into a persistent schedule, and at each time tag slews attitude, activate an imaging or radar sensor with specified parameters, capture data, and store the data in non-volatile memory. The spacecraft may generate quality metrics for the captured data and return the metrics to the ground station.

A georegistration (a.k.a. georectification) of an image captured by a camera in an aerial vehicle, such as a satellite, is based on identifying multiple features using descriptor sets, and sending to a ground station only the descriptors of the identified features and the associated locations in the captured image, without sending of the captured image itself, thus requiring a low communication bandwidth. Using a database of geosynchronized reference images, the ground station uses the received descriptors sets and the associated image locations to localize the features on a selected geosynchronized reference image from the database, and forms a mapping function that map any locations in the captured image to geographical coordinates on Earth. The mapping may be used to geosynchronize an additional feature identified in the aerial vehicle, or to geo synchronize a region that may be cropped from the captured image and sent to the ground station.

The invention relates to a multi-mode interactive indoor unmanned aerial vehicle target detection and tracking method and system. The system comprises a target detection and tracking module, a laser radar inertial odometer module, a video display and interaction module and a flight control module. The method comprises the steps that an unmanned aerial vehicle end receives and processes RGB images, laser radar point cloud and IMU data; and optimizing a YOLOv8 target detection model and an OSTrack target tracking model through a TensorRT inference engine. By fusing LiDAR and IMU data, accurate state estimation and map construction are provided. And the ground station end displays a video stream and generates a control command through the video display and interaction module. And calculating a flight speed and a yaw angle rate by estimating an error between the target image position and the current position of the unmanned aerial vehicle, and generating a flight control instruction. The problems that an indoor unmanned aerial vehicle system often faces low target detection precision, poor tracking stability and difficult user interaction experience are solved, and the method and the system are more efficient, more accurate and higher in interactivity.

The invention discloses a method and a system for measuring gravitational potential by a satellite-air-ground optical clock time-frequency comparison system. According to the method for measuring the gravitational potential, an optical clock superior to 110-18 orders of magnitude serves as the basis, a free space time-frequency comparison link based on an optical frequency comb serves as a bridge, the optical clocks among the satellite, the air and the ground are connected, high-precision time-frequency transmission is carried out, a gravity frequency shift signal is accurately extracted through time-frequency comparison of a remote clock, and the gravitational potential is measured. And then the gravity potential difference of the position where the remote clock is located is obtained by using a gravity frequency shift equation, and the gravity potential difference between air and ground or between any ground stations is determined.

The embodiment of the invention provides a measurement and control link multiple access method and device based on a high-dimensional discrete space, electronic equipment and a storage medium. The method comprises the following steps: constructing the high-dimensional discrete space based on an initial orthogonal vector coordinate system; the high-dimensional discrete space comprises space resources of at least one of a time domain, a frequency domain and a code domain; in a high-dimensional discrete space, constructing a non-stipulated coordinate system matched with the control scene requirement by taking the initial stipulated coordinate system as a reference; constructing a dual mapping relation matrix according to a non-stipulated coordinate system of the initial stipulated coordinate system, and updating the dual mapping relation matrix based on the measured data; and accessing at least one satellite or spacecraft to the ground station based on the updated dual mapping relation matrix and the constellation measurement and control link, thereby realizing effective expansion of the measurement and control link multiple access technology, and improving the measurement and control link multiple access efficiency based on the available discrete space of the multi-dimensional joint variable.

The invention relates to the technical field of satellite communication, and provides a high-orbit and low-orbit fused satellite antenna tracking method and system. The method comprises the following steps: constructing a global satellite database and carrying out time-space coordinate unified coding; predicting visible time according to the satellite coordinates, and identifying a visible time window overlapping region and a corresponding tracking satellite pair; based on the types of the satellite pairs in the overlapping time, tracking path optimization under space-time unified coordinates is carried out, and optimization control parameters are output; switching points and scanning tracks are spliced according to the control parameters, and antenna tracking control parameters are obtained and used for adjusting an antenna. According to the invention, the technical problem that the stability of a satellite communication link is reduced due to switching delay and signal interruption risks when a traditional ground station system dynamically tracks high and low orbit satellites is solved, seamless switching and continuous high-gain tracking of the satellite communication link are realized through cooperative tracking and real-time optimization operation of the multi-orbit satellites, and the stability of the satellite communication link is improved. And the link stability and the resource utilization rate of satellite communication are improved.

The invention provides a radar rainfall real-time estimation system based on double-method fusion and ground verification, belongs to the technical field of meteorological radar rainfall estimation, and adopts double-method fusion of a physical model estimation module and a driving model estimation module to cooperate with a causal inference fusion engine to improve the precision and adaptability of rainfall estimation and improve the rainfall estimation accuracy. The physical model module adaptively selects a Z-R, ZDR-R or KDP-R relation according to the quality of radar-based data and rainfall scenes, drives the model module to capture space-time nonlinear evolution characteristics of rainfall echoes and predicts short-time rainfall dynamics, and the causal inference engine identifies differentiated characteristics of two estimation fields, inferes hail, vertical airflow and other physical hybrid factors, and performs real-time prediction on the hail, the vertical airflow and other physical hybrid factors. A comprehensive rainfall estimation field is generated, a continuous error correction field converted from ground station observation data is corrected through a space-time error atlas network, and finally rainfall estimation information is generated for real-time rainfall estimation, so that the adaptability to a complex weather field and the precision of the estimation field are improved.

The invention relates to a satellite laser autonomous calibration method based on multi-star sensor dynamic collaboration, multi-star sensors comprise a plurality of platform cabin star sensors and a plurality of laser self star sensors, and the platform cabin star sensors and the laser self star sensors are arranged on a satellite side plate. The satellite laser autonomous calibration method comprises the following steps: determining an installation matrix of a multi-star sensor and a satellite body system, and completing installation matrix parameter binding; by taking the platform cabin star sensor as an attitude calibration reference, correcting the mounting matrixes of the other platform cabin star sensors and the laser star sensor so as to complete in-orbit autonomous calibration; and calculating the residual error of the platform cabin star sensor and the laser star sensor, when the error quaternion residual error is lower than a set threshold value, ending the autonomous calibration process, and broadcasting the quaternion measured by the multiple star sensors. According to the installation layout of the satellite laser and the star sensor, the calibration process is simplified, a ground station does not need to participate, and the satellite can autonomously complete the calibration process in orbit.

The invention discloses an AI-driven satellite ground station multi-module cooperative intelligent management and control method, and relates to the technical field of satellite communication and ground station management and control. The method comprises the following steps: carrying out global situation-resource portrait fusion, arranging multi-source nodes, carrying out 10ns-level TSN + PTP synchronization, generating a five-dimensional situation tensor containing dimensions such as space coordinates, and mapping computing power and bandwidth resources to form a dynamic coupling hypergraph; link-task double-axis hierarchical scheduling: based on the link health degree and the task importance, completing resource dynamic binding and matching in a millisecond level through three-level channels; a quantum-classical hybrid encryption assembly line is used for differentiated encryption according to a grading result to guarantee data security; carrying out dual-channel self-evolution prediction, constructing a network to predict link quality and task requirements, and compressing the link quality and task requirements into a lightweight model to pass back and schedule; closed-loop execution and toughness self-healing are carried out, an instruction is generated and issued, an execution effect is returned to update a model, and redundancy is degraded and minute-level recovery is carried out when a fault occurs; the resource utilization rate, the task completion rate and the system toughness are improved.

The invention relates to the technical field of low-orbit satellite communication, in particular to an orbit optimization method and system for dynamically and autonomously tracking a low-orbit satellite based on a ground station, and the method comprises the steps: collecting TLE orbit element data, constructing an SGP4 orbit prediction model, and obtaining a prediction result; low-earth-orbit satellite orbits with different inclination angles are determined through STK software modeling based on a ground station, and corresponding standard results are obtained; comparing the prediction result with a standard result to obtain an error result; dynamically optimizing the Bstar parameter based on an error result by adopting a genetic algorithm, and determining an optimal Bstar parameter; adjusting the SGP4 orbit prediction model based on the optimal Bstar parameter, and obtaining an optimization result through the adjusted SGP4 orbit prediction model; according to the method, optimization is carried out based on an existing SGP4 model, optimal Bstar parameters are dynamically searched through a genetic algorithm, accumulative errors caused by the fact that TLE data are not updated in time are compensated, stable tracking of a ground station is guaranteed, and the precision of medium and long term orbit forecasting is improved.

The invention discloses a satellite-ground integrated cooperative efficient alignment method based on a large-view-field optical load, relates to the technical field of spacecraft systems, and solves the problems that in the prior art, precision is low, response is slow, the requirements of remote sensing satellite high-speed data transmission for pointing precision and link availability are met, and satellite data transmission efficiency is improved. Comprising the following steps that S1, when a satellite enters a data transmission mode, a laser ground station opens beacon light, and a satellite center computer executes an alignment program; s2, satellite alignment is completed, and a data transmission link between the satellite and the laser ground station is established; and S3, the satellite carries out a data transmission test, and when the data transmission test is completed, the satellite and laser ground station data transmission link is quitted, and the operation is ended.

The invention provides a fusion method of ground station monitoring and satellite remote sensing inversion PM2.5 data, and relates to the technical field of PM2.5 pollution prevention and control. Ground station data and satellite remote sensing data are subjected to time matching and space matching and then are fused by using a universal Kriging method to obtain a high-precision and large-area coverage PM2.5 product. The PM2.5 data spatial correlation is considered, so that the fusion result is closer to reality, the calculation complexity is reduced, and meanwhile, the reliability of the fusion result can be judged by giving an error after data fusion. According to the method, the limitations of insufficient spatial consideration and high calculation complexity of a traditional method are made up, and the PM2.5 product can be used for pollution process analysis, climate change and other researches.

A satellite receives, from a ground station, multiple first commands out-or-order for replicating a conflict-free replicated dataset at the satellite. An authority to access the conflict-free replicated dataset is retrievable from a block of a blockchain. The multiple first commands are reordered based on an ordering specified by a causal tree received from the ground station. A global state of the conflict-free replicated dataset is replicated locally at the satellite based on the multiple first commands reordered in accordance with the causal tree. From the ground station, multiple second commands are received for performing operations on the conflict-free replicated dataset. The operations are performed on the conflict-free replicated dataset, using the multiple second commands, based on the authority retrieved from the blockchain.

The invention provides a meteorological element field microstructure intelligent generation and reconstruction method and device, and relates to the field of model training, the method can obtain reanalysis data and historical forecast data of global meteorological elements, and construct a training sample set based on the reanalysis data and the historical forecast data; taking sparse meteorological element fields of a plurality of different height layers in a continuous time period as model input, combining ground station observation data and topographic data related to meteorological evolution as constraint conditions, and training the initial diffusion generation model by using the training sample set to obtain a final diffusion generation model after training is completed; the constraint condition is used for guiding the final diffusion generation model to generate a three-dimensional meteorological element field conforming to observation consistency and terrain adaptability; modeling the three-dimensional high-resolution meteorological element field through the final diffusion generation model to obtain a reconstructed three-dimensional meteorological element field microstructure; the high resolution is higher than the specified resolution.

The invention discloses an unmanned aerial vehicle power transmission line patrol method, which comprises the steps of S1, intelligent route planning, constructing a power transmission corridor digital twin model based on three-dimensional laser point cloud data, S2, autonomous flight control, adopting an STM32F4 series MCU as a bottom layer controller, and running a real-time operation system, S3, multi-modal data acquisition, adopting a multi-modal sensor matrix and a cooperative acquisition mechanism, and carrying out multi-modal data acquisition. S4, real-time transmission processing is carried out, and adaptive code rate control is adopted; and S5, intelligent analysis and decision making are carried out, and a deep learning module is adopted. According to the unmanned aerial vehicle power transmission line patrol method, key defects such as insulator damage and wire strand breakage in a power transmission line are recognized and analyzed in real time, image processing and target detection are directly completed at an equipment end through edge computing capability, and only high-definition images with suspected defects are screened and returned to a ground station or a data center; the transmission data volume and the communication load are greatly reduced, the mechanism effectively realizes the real-time preliminary screening of the line defects, and the inspection efficiency and the response speed are improved.

The invention discloses a signal encryption method and device based on quantum key distribution, and relates to the technical field of satellite navigation, and the method comprises the steps: building a quantum key distribution system based on a plurality of interconnected quantum key servers, and enabling a user communication terminal to be connected with a nearby quantum key server; the communication relay unit performs basis vector comparison on the quantum state data of the satellite and the ground station through a key distribution protocol to generate a quantum key; the key distribution unit dynamically updates the quantum key and distributes the quantum key to the user communication terminal; the user communication terminal encrypts the satellite navigation data by using the quantum key to obtain an encrypted data packet, and sends the encrypted data packet to the receiving end through the communication relay unit; and the receiving end decrypts the encrypted data packet based on the quantum key to obtain the satellite navigation data. According to the method, the generation rate of the quantum key can be improved, the anti-interference performance of the quantum key distribution system in a complex environment is enhanced, and the stability and reliability of the quantum key distribution system are ensured.

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

The invention provides a frequency division joint communication method and device based on overlapped multiple beams, and relates to the technical field of satellite communication. Comprising the steps that frequency selection frames forwarded by a communication ground station through satellites are received, the frequency selection frames are all-one sequences after spectrum spreading, and the frequency selection frames of different beams are distinguished through different uplink frequency points; and capturing a frequency selection frame sent by the communication ground station in a frequency selection state, and determining all overlapped beams where the communication terminal is located according to a capturing result. And framing a signal to be transmitted to generate a service frame, and synchronously sending the service frame on the frequency points corresponding to all the determined overlapped beams through multi-beam joint modulation. A multi-beam joint transmission signal is transparently forwarded to a communication ground station through a satellite, so that after the communication ground station separates each beam signal and completes de-spreading operation to obtain symbol-level information, the signals are coherently combined through a cross entropy estimation algorithm, and effective data information is extracted. Multi-beam joint communication is realized, the power spectrum density of the transmitted signal is reduced, and the signal concealment is improved.