556 results about "Ground station" patented technology

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 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.

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 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 relates to a satellite-ground collaborative learning method and system and electronic equipment, and relates to the technical field of satellite remote sensing, and the method comprises the steps: compressing a basic model into a small model through a ground station, and enabling the small model to serve as a satellite in-orbit model; detecting the comprehensive distribution offset of the satellite during the in-orbit reasoning period, and when the comprehensive distribution offset is greater than a preset threshold value, sending related data to a ground station; calculating a weighted difference value between a prediction result of the on-orbit model and a prediction result of the basic model based on the related data, and triggering updating of the on-orbit model when the weighted difference value exceeds a preset threshold value; loRA fine tuning is carried out on the small model through the ground station so as to realize on-orbit model updating; and the steps are repeatedly executed until the updating frequency of the on-orbit model reaches the preset frequency, and the on-orbit model is aggregated into the basic model through the ground station to achieve model updating of the basic model. According to the scheme, the overall performance of the satellite on-orbit model facing the distributed external scene can be improved.

The invention relates to the technical field of wind energy development and utilization, in particular to a multi-source meteorological data dynamic fusion wind power plant simulation method, which comprises the following steps of: accessing satellite remote sensing, a ground observation station, numerical forecasting and wind power plant historical operation data, and outputting standardized meteorological data through format analysis, standardized processing and cleaning; a credibility score is calculated based on multi-dimensional indexes such as data integrity and time consistency, and abnormal data restoration or standby data source switching is achieved; in combination with wind power plant DEM topographic features and a self-adaptive sliding window, the weight of a data source is adjusted in real time through reinforcement learning, and a dynamic weight value is generated; an improved Windpowerlib framework adapts to fusion data, fan parameters are dynamically configured, and an initial simulation result is generated; and collecting real-time data of the wind power plant, and correcting model parameters by using Kalman filtering. The wind power plant simulation precision and timeliness can be improved, the data utilization rate and the model adaptability are enhanced, and the deviation between the simulation result and the actual working condition is reduced.

The invention relates to the technical field of satellite-ground laser communication, and discloses a banyan-shaped network communication method and system based on multi-beam multipath transmission and space diversity synthesis aperture reception. The method comprises the following steps: dividing a light beam into a plurality of beams at a satellite-based terminal through beam forming to point to a plurality of ground stations; multiple ground stations receive data in parallel and then gather the data to a data center for time-space synchronization; and the data center adopts a multi-branch neural network to intelligently fuse the synchronized data so as to reconstruct a signal. According to the invention, by constructing the satellite-to-ground collaborative architecture, signal interruption and data loss caused by atmospheric turbulence are effectively suppressed, the limitation of high-error-code communication is broken through, and remote, high-speed and high-reliability satellite-to-ground communication is realized.

The invention discloses a computing power scheduling method for multi-satellite collaborative application. The computing power scheduling method comprises the steps that 1, a ground station generates an undirected connection graph according to a satellite constellation topological structure and a resource state; step 2, the ground station receives a user instruction and carries out task computing power demand estimation; step 3, the ground station adopts a sliding window mode on the undirected connection graph to determine an execution area for executing the task; 4, calculating a central node of the execution area, and taking the central node as a source satellite for executing an information acquisition task; 5, executing an information acquisition task by the source satellite; step 6, completing task data distribution from the source satellite to other satellite nodes in the area by adopting a double-factor sorting scheduling strategy; 7, the satellite node returns a result to the source satellite after completing task processing; and step 8, the source satellite collects the result and sends the result to the ground station. The invention provides a strategy of multi-satellite cooperative processing and resource dynamic scheduling under the condition that the single-satellite capability is limited, and the processing time delay of on-satellite data is reduced.

The invention discloses a high-fidelity splicing method and system for an unmanned aerial vehicle image, and the method employs a dual-stage processing strategy, achieves precise positioning through coarse-fine two-stage alignment, calculates an overall transformation parameter through global estimation to complete coarse alignment, refines non-rigid offset through local correction, and achieves high-fidelity splicing of the unmanned aerial vehicle image. The feature weight is dynamically adjusted in combination with self-adaptive enhancement, and geometric smooth constraint is used for limiting regional displacement; smooth weights with continuous boundaries and the weight sum being 1 are generated based on the shape of the overlapping region, images are decomposed to different frequency layers for layer-by-layer fusion, and the system comprises an image acquisition unit, a dual-stage processing unit and an output display unit and can be deployed on the end side of an unmanned aerial vehicle or a ground station. The method is high in alignment precision, can process large parallax and non-rigid deformation, is traceless in fusion, is high in structural fidelity, and meets the real-time processing requirements of airborne or edge equipment.

A ground station of a UAS for an unmanned aerial vehicle (UAV) includes a landing pad assembly and a carousel assembly that allow for passive removal and replacement of a battery from and to a UAV. The UAS can include a battery replacement system that uses the mechanical movement of a landing pad of the ground station to control movement of a battery door of the landing pad assembly.

The invention relates to a ground precipitation intensity estimation method based on phased array radar echoes and geographic factors, which belongs to the field of radio, and comprises the following steps of: mapping and interpolating polar coordinate multivariable radar echoes and a three-dimensional wind field to a unified three-dimensional grid to form a consistent spatio-temporal data basis; then, various rainfall type areas are automatically divided based on local density clustering, a time lag field is constructed according to rainfall types, and adaptive time alignment of radar echoes and ground station observation is achieved; a three-dimensional wind field and a raindrop terminal end velocity are introduced to calculate rainfall falling drift, the position of a grid point matched with a ground station point space is corrected, and accurate space matching of radar echoes and ground station observation is completed; a terrain uplift index is constructed by combining a stratum wind direction, a DEM (Digital Elevation Model), a gradient, a slope direction and a slope position type, and a radar nonlinear precipitation potential vector and a terrain feature are jointly modeled through a physical constraint coupling model, so that quantitative estimation of the ground precipitation intensity is realized, and the reliability and applicability of ground precipitation estimation in a complex environment are improved.

The invention discloses an unmanned aerial vehicle cluster dynamic cross-domain key management method and system based on the Chinese remainder theorem (CRT), a key generation center generates system public and private keys and public parameters, and a ground station and an unmanned aerial vehicle perform hierarchical registration and verify respective keys; the unmanned aerial vehicles respectively generate signature messages and send the signature messages to a specified ground station for identity verification, and the ground station constructs a group key based on CRT and publishes the group key to the block chain; when a new unmanned aerial vehicle applies for joining, a signature message is sent to the ground station, and the ground station updates and publishes the group key; when the unmanned aerial vehicle applies for leaving, a leaving message is sent to the ground station, and the ground station updates and publishes the group key. According to the method, complex operations such as bilinear pairing operation and large integer modular exponentiation operation are avoided by optimizing the group key derivation process based on the CRT, and the calculation complexity is remarkably reduced. Meanwhile, efficient cross-domain authentication and batch verification are realized through Pedersen commitment and a zero-knowledge proof technology, and communication and calculation overhead is reduced.

The invention discloses a forest protection patrol and sprinkling fire extinguishing unmanned aerial vehicle system. The system comprises an integrated task unmanned aerial vehicle platform and a ground station remotely interacting with the integrated task unmanned aerial vehicle platform. The unmanned aerial vehicle platform is integrated with a task detection module and is used for acquiring and returning target data including a fire scene video, an image and accurate positioning information; the task execution module is used for storing and spraying fire extinguishing liquid; and the dual-mode communication unit comprises an airborne sight distance and satellite communication module and is used for establishing a bidirectional data transmission link with a ground station. The ground station comprises a ground communication unit which is provided with a corresponding sight distance and a satellite communication module; and the comprehensive processing and commanding unit is used for receiving and processing the target data, generating comprehensive fire scene situation information, generating a task control instruction based on the situation and returning the task control instruction to the unmanned aerial vehicle platform, so that the working state of the detection module and the precise spraying operation of the execution module are controlled in real time, and the integrated'searching and spraying 'function of patrol and fire extinguishing is realized.

The invention discloses a ground station antenna pointing error compensation method and related equipment. The method comprises the following steps: controlling an antenna driving shaft to sequentially rotate to a plurality of measuring points according to a preset angle step length in a preset angle range, and synchronously acquiring a command angle value output by an encoder and an actual angle value output by a gradienter at each measuring point; for each measurement point, an error value is calculated according to the relation that the error value is equal to the difference between the actual angle value and the command angle value, and an error sample set containing a plurality of data pairs is formed; and performing curve fitting processing on the error sample set to obtain a continuous and smooth error compensation function in the preset angle range, and performing ground station antenna pointing error compensation by using the error compensation function, the error compensation function being used for representing a mapping relationship between a command angle value and an error value. The problem that an existing ground station antenna pointing error compensation method is high in cost, complex in implementation or limited in compensation effect can be solved.

The invention provides a fishing-light complementary unmanned aerial vehicle target detection system fusing multi-modal data, and the system comprises an unmanned aerial vehicle flight platform which is used for bearing each unit to fly according to a preset route; the airborne multi-mode sensing unit is used for synchronously acquiring visible light images, thermal infrared images and multispectral image data in the fishing-light complementary park; the airborne edge calculation unit is used for operating the target detection model and carrying out real-time preprocessing and preliminary fusion analysis on the acquired multi-modal data; the ground station control center performs data interaction with the unmanned aerial vehicle flight platform through a wireless communication link; visible light, thermal infrared and multispectral sensors are synchronously integrated through the unmanned aerial vehicle platform, monitoring tasks such as photovoltaic panel fault diagnosis, water area safety monitoring, breeding activity and water quality environment analysis are integrated together by utilizing a deep learning fusion algorithm, and the defects that an existing scheme is single in function and split in management are overcome.

Provided in the embodiments of the present application are a store-and-forward-based satellite communication method, and a device, which are applied to the technical field of communications. The method is applied to a first satellite base station, wherein a satellite base station network comprises at least one satellite base station, the satellite base station network comprises the first satellite base station and a second satellite base station, the first satellite base station respectively establishes communication connections with the second satellite base station and a user equipment, the second satellite base station respectively establishes communication connections with the first satellite base station and a ground station, and the user equipment is in a non-store-and-forward mode. The method comprises: when the communication between a second satellite base station and a ground station is disconnected or the communication between a first satellite base station and the second satellite base station is disconnected, the first satellite base station generating a first mode switching instruction; and the first satellite base station sending the first mode switching instruction to a user equipment, wherein the first mode switching instruction is used for instructing the user equipment to switch the communication mode thereof from the current non-store-and-forward mode to a store-and-forward mode.

The invention discloses a wind power plant icing disaster sensing and early warning method and system. The method comprises the following steps: acquiring SCADA multi-source data of a satellite, a ground station and a wind power plant; performing data noise reduction and feature extraction; inputting the feature data into a physical mechanism model and a data-driven machine learning model in parallel, and fusing the outputs of the physical mechanism model and the data-driven machine learning model by adopting a dynamic weight distribution strategy to obtain an icing thickness predicted value; and early warning information is generated and prevention and control measures are triggered. The system comprises corresponding function modules. According to the method, through multi-source data fusion and mechanism-data driven dual-core model coupling, high-precision prediction and closed-loop prevention and control of the whole cycle from icing formation, growth to ablation are achieved, and the early warning timeliness and accuracy and the operation safety and economic benefits of the wind power plant are remarkably improved.

The invention discloses a method and device for achieving track control of a hydraulic mechanical arm, a target operation area is perceived through a depth camera, division of the operation area and marking of obstacles are completed in combination with an artificial intelligence algorithm, and tight coupling of environment modeling and task planning is achieved. According to the method, the plurality of candidate operation areas can be quickly generated and transmitted back to the ground station, an operator only needs to visually select or correct, the manual operation amount is greatly reduced, and the operation efficiency is remarkably improved. According to the embodiment of the invention, the track control precision and the working efficiency of the hydraulic mechanical arm are improved, the dependency degree of operation on artificial experience is reduced, the friendliness of man-machine interaction is enhanced, the safety and the reliability of the system can be ensured in a complex mining area scene, and the method has good application value and popularization prospect.

There is provided a technique for achieving inter-satellite optical communication for a satellite having a limited calculation capability. One aspect of the present disclosure relates to an earth station, including: a data acquisition unit that acquires a predicted orbit data sequence indicative of a predictive ephemeris of a satellite for a predetermined period, and a communication unit that transmits the acquired predicted orbit data sequence to a relay satellite, wherein the data acquisition unit acquires a first data sequence that is the predicted orbit data sequence having a first data amount and a second data sequence that is the predicted orbit data sequence having a second data amount smaller than the first data amount, and the communication unit transmits the first data sequence or the second data sequence as orbit information of a satellite to a relay satellite, the first data sequence or the second data sequence selected in accordance with predetermined selection criteria.

The invention relates to the technical field of satellite communication transmission optimization, and discloses a multi-band collaborative satellite communication remote data transmission system. According to the system, terminal historical data are processed through waveform decomposition, steady-state and transient characteristics are extracted, and a terminal-level dynamic transmission characteristic spectrum is constructed in combination with real-time parameters. And carrying out feature level comparison on the feature spectrum and ground station measured data, fusing time delay, frequency offset and coding distortion differences to generate a difference fusion spectrum, mapping the difference fusion spectrum to a satellite network topology, and identifying an abnormal propagation path and a corresponding physical region. And then activating multi-frequency-band cooperative monitoring, and completing accurate positioning and self-adaptive response of an abnormal region by adjusting satellite node parameters and applying controllable disturbance. According to the scheme, terminal-level behavior characteristics and network topology mapping are utilized, accurate diagnosis from signal tracing to a space path is achieved, and the accuracy of satellite network transmission anomaly management and the autonomous response capability of a system are improved.

The invention provides a multi-mode unmanned aerial vehicle countering method and system based on ground-air cooperation, relates to the technical field of unmanned aerial vehicle countering, and solves the problems that an existing unmanned aerial vehicle countering technology is low in cooperation efficiency, weak in environmental adaptability and insufficient in real-time response capability. In the method, a ground station uses a radar to scan a target unmanned aerial vehicle in a monitoring airspace, calculates basic parameters of the target unmanned aerial vehicle, constructs a threat degree evaluation model, obtains the threat degree of the target unmanned aerial vehicle, and uses a greedy algorithm to carry out target distribution between a countering unmanned aerial vehicle and the target unmanned aerial vehicle to form a distribution scheme; the distribution scheme is uploaded to the countering unmanned aerial vehicle, and a target unmanned aerial vehicle distributed to the countering unmanned aerial vehicle in a monitoring airspace is recognized through a built-in lightweight visual recognition algorithm; a target unmanned aerial vehicle is continuously tracked through a built-in visual tracking algorithm, and a corresponding countering means is dynamically selected based on recognition and tracking states. According to the invention, the countering response speed of the unmanned aerial vehicle and the stability of target tracking in a complex environment are smoothly improved.

The application discloses a kind of support to drag and drop sorting waypoint list management interaction system, belong to ground station waypoint management field.Belong to ground station waypoint management field.It includes waypoint list display module, drag and drop sorting interaction module, waypoint management operation module, associated function adaptation module;Waypoint list display module presents the key parameters such as waypoint height, flight speed with entry form;Drag and drop sorting interaction module supports user to drag and drop waypoint entry adjustment order, real-time feedback state and synchronously flight execution logic;Waypoint management operation module provides waypoint deletion, save, read and upload function;Associated function adaptation module realizes linkage with template editor, relative coordinate editor and flight control module.This system operation is intuitive, data synchronization is efficient, and function integration is strong, effectively solve the problem that traditional waypoint management operation is complicated, data linkage is insufficient, improve the convenience and accuracy of flight mission planning.

At a satellite, in each of a plurality of time periods, a method of communicating with first and second ground stations, to exchange a first downlink message and a first uplink message with the first ground station and a second downlink message and a second uplink message with the second ground station, wherein the first and second downlink messages and the first and second uplink messages are time-stamped messages, and determining one or more orbit parameters indicative of an orbit of the satellite based on known positions of respective first and second ground stations relating to one or more of the plurality of time periods and based on first timing information relating to times of reception and transmission of respective first uplink and downlink messages and second timing information relating to times of reception and transmission of respective second uplink and downlink messages in the one or more time periods.

The invention discloses a ground station multipath load intelligent power distribution system and a power distribution method. The system comprises a power supply module, a Hall voltage sensor, a single-chip microcomputer, an AD acquisition module, an input / output relay, a Hall current sensor and a master control module. Data receiving, transmitting, analyzing, storing and updating of input voltage and load current are achieved through the input measurement and control module and the load measurement and control module. Through acquisition and judgment of the main control module, the functions of input / load multichannel on-off execution, fault reporting of open phase, overvoltage, undervoltage and the like are realized, and an intelligent power distribution strategy is generated. By using the design method provided by the invention, the design cost can be effectively reduced; the load can be automatically distributed to a three-phase power supply; the method can achieve the quick and simultaneous power-on and power-off of multiple loads in a short time, can record a load curve, updates a power distribution strategy in time, and can adapt to various power distribution scenes.

A multi-vendor ground station integrated control system according to an example embodiment includes an integrated interface unit configured to provide a ground station integrated interface through which multi-vendor equipment and parts are compatible to operate an artificial satellite, a first processor configured to operably couple to the integrated interface unit and separate dependencies between subsystems when interacting with the subsystems, and a second processor configured to operably couple to vendor equipment having different forms of the ground stations, collect motions generated from the ground stations, and control equipment of the ground stations.

Systems, methods, and software for operating an unmanned aerial vehicle (UAV). A method includes capturing a video stream using one or more camera sensors of the UAV. The method includes transmitting data representative of the video stream to a ground station communicably coupled to the UAV. The method includes determining one or more performance characteristics of a communications link between the UAV and the ground station. The method includes adjusting a resolution of the video stream according to the one or more performance characteristics of the communication link. Embodiments of the present technology provide continuity of video quality for viewing by UAV users at ground stations responsive to variations in video data transmission capacity during flight operations with minimal, or no, detrimental impact on user experience.

The invention discloses a biomedicine standardized cubesat platform and a working method, and relates to the technical field of space.The biomedicine standardized cubesat platform adopts a 3U cubesat framework, the top layer of the 3U cubesat framework is provided with a satellite bus module, the middle layer of the 3U cubesat framework is provided with an energy and environmental control life support module, and the bottom layer of the 3U cubesat framework is provided with a biological experiment module; the satellite bus module is in bidirectional communication with the energy and environment control life support module and the biological experiment module through data interfaces. The satellite bus module further communicates with a ground station; the energy and environment control and life support module supplies energy to the satellite bus module and the biological experiment module through electrical interfaces, and provides oxygen supply, water supply and environment regulation and control support for the biological experiment module through a fluid transmission channel. Through a standardized and modularized cubesat structure, the functions of biological sample culture, environment regulation and control, real-time monitoring, data return and the like are integrated, and a low-cost and quick-response technical support is provided for space life science experiments.

In a system where multiple satellites autonomously take turns acting as servers, the servers will be rotated according to instructions from a ground station. [Solution] The server, which is a satellite 200 that has obtained server rights, receives a priority notification when a ground station 300 transmits the priority notification. If the server receives the priority notification, it selects the satellite 200 specified in the priority notification as the server for the next time interval. If the server does not receive the priority notification, it selects one of the multiple satellites as the server for the next time interval based on the status information of the server and the status information of each client.

The invention discloses a reinforcement learning-based low-altitude wide-area security risk high-precision identification method, which comprises the following steps of: forming an unmanned aerial vehicle communication network by an unmanned aerial vehicle, a base station and a ground station, transmitting data acquired when the unmanned aerial vehicle executes a task in a specified airspace to the base station through the unmanned aerial vehicle communication network, and transferring the data to the ground station by the base station; and the ground station collects and detects the received data sent by the unmanned aerial vehicle so as to identify whether an abnormal event occurs. The accuracy and efficiency of risk identification and target identification are improved.