15 results about "Satellite scheduling" patented technology

The invention relates to the technical field of space network communication and satellite intelligent management, in particular to an LEO satellite network intelligent routing system and method based on intention recognition. Comprising a natural language instruction input module, a text preprocessing module, a BERT semantic modeling module for RoPE position coding enhancement, a bidirectional LSTM context enhancement module, an intention recognition module, an entity recognition module, a structured result generation module and an interface interaction module. According to the method, a path request instruction in a natural language form is mapped into a structured scheduling parameter, the problems that a parameter configuration process in a traditional satellite scheduling system depends on manpower, the response timeliness is poor and the analysis capability is weak are solved, meanwhile, rotation position coding is introduced to improve the sequence structure sensing capability, and local context features are captured in combination with BiLSTM, so that the real-time performance of the satellite scheduling system is improved. Through intention recognition and entity recognition dual-task joint modeling, high-precision output of a structured request analysis result is realized, and key support is provided for satellite network intelligent scheduling.

The invention discloses a relay satellite scheduling method considering antenna resource heterogeneity and task diversity, and the method specifically comprises the following steps: 1, discretizing a scheduling period into equal-length time slots, and constructing a time slot set S; constructing a visibility mask and a service window mask for any task t and antenna a; 2, generating an initial feasible scheduling scheme by adopting a conflict perception initialization strategy; and step 3, performing iterative improvement on the initial scheme generated in the CAI stage by adopting a constraint local re-optimization strategy, thereby improving the task completion rate and the target function value. According to the invention, the overall task completion rate and the bandwidth utilization efficiency of the relay system can be improved.

The present application relates to the technical field of satellite scheduling, in particular to a multi-modal multi-objective satellite task scheduling method based on a ring topology, comprising the following steps: S1: taking the minimization of task request failure rate and ground station load imbalance rate as the optimization target, constructing a multi-modal multi-objective optimization scheduling model of satellite task scheduling, and determining the problem target space; S2: determining a task available time window set according to user task request, a ground station set, a satellite-ground visible time window set and a problem constraint set, and constructing a problem decision space; S3: adopting a knowledge evolutionary algorithm iterative optimization to explore and maintain more equivalent Pareto optimal solution sets, and obtaining a high-quality scheduling scheme set, wherein the knowledge evolutionary algorithm is based on a ring topology structure decision population updating strategy. The present application can realize multi-modal multi-objective optimization of the problem, so that a group of satellite task scheduling schemes considering multiple optimization targets and differentiated from each other can be obtained after a single run.

The invention relates to the technical field of satellite scheduling, in particular to a multi-modal multi-target satellite task scheduling method based on ring topology, which comprises the following steps: S1, by taking a minimum task request failure rate and a ground station load imbalance rate as optimization targets, constructing a satellite task scheduling multi-modal multi-target optimization scheduling model, and determining a problem target space; s2, determining a task available time window set according to the user task request, the ground station set, the satellite-ground visible time window set and the problem constraint set, and constructing a problem decision space; and S3, iterative optimization is carried out by adopting a knowledge evolutionary algorithm, more equivalent Pareto optimal solution sets are explored and maintained, a high-quality scheduling scheme set is obtained, and the knowledge evolutionary algorithm decides a population updating strategy based on a ring topology structure. According to the invention, multi-modal multi-objective optimization of the problem can be realized, so that a group of mutually differentiated satellite task scheduling schemes considering a plurality of optimization objectives can be obtained after single operation.

This paper presents a resource scheduling optimization method for mega-constellations, focusing on satellite resource allocation in this field. It addresses the challenge of existing satellite resource scheduling methods in achieving global optimization while balancing time and energy consumption, aiming to improve the execution efficiency and reduce energy consumption of multi-satellite collaborative tasks. By simulating and processing real satellite scheduling tasks, satellite and task data are obtained. A reinforcement learning-guided genetic algorithm is used to optimize task sequences. These optimized sequences are then used for satellite resource allocation, and the time and energy consumption of each task sequence are calculated and normalized to obtain a comprehensive index. This method yields the task execution sequence with the minimum combined time and energy consumption index, thus providing the optimal scheduling scheme to meet the satellite scheduling requirements of mega-constellations.

The application discloses a kind of forest fire monitoring methods based on low-orbit satellite, comprising: obtaining data by multiple sensors, and generating fusion dataset by denoising and smoothing processing.Utilize convolutional neural network to combine multi-scale analysis to enhance fire point features, form feature set.Multiple satellite cooperative observation data are matched with feature set, and enhanced dataset of high frequency observation is generated by time series alignment.Adopt deep learning and transfer learning optimization model, extract key area features, share multiple satellite data through distributed computing, obtain coverage enhanced dataset.Based on timeliness evaluation model, dynamically adjust multiple satellite scheduling strategy, output scheduling result.Through reinforcement learning optimization algorithm robustness, combined with complex weather condition simulation, obtain robustness enhanced model, and utilize multi-source data verification technology to verify data fusion precision, output final monitoring result.The application significantly improves the accuracy, timeliness and coverage integrity of fire point detection.

The invention relates to a hopping beam scheduling method and a satellite constellation system. The method comprises the following steps: acquiring service cell information corresponding to a satellite, and performing feature extraction on the service cell information to obtain a service cell feature vector; receiving feature vectors of adjacent cells sent by other satellites adjacent to the satellite in the satellite constellation system, and fusing the feature vectors of the adjacent cells to obtain fused feature vectors of the adjacent cells; and based on the serving cell feature vector and the adjacent cell fusion feature vector, determining the number of hopping beams and cell identifiers of the satellite in each hopping beam time slot, and pointing the hopping beams matched with the number of the hopping beams to cells corresponding to the cell identifiers at the ending moment of the corresponding hopping beam time slot. By adopting the method, the effectiveness of each satellite scheduling hopping beam can be ensured, and the overall throughput of a satellite constellation system is improved.

This application discloses a regional target decomposition method for collaborative scheduling of satellite resources in heterogeneous remote sensing constellations, relating to the field of satellite remote sensing technology. The method includes: determining multiple stripes of satellite observation target areas in a heterogeneous remote sensing constellation; constructing triplet decision variables for each strip: strip start-point encoding, strip selection binary variable, and length normalization coefficient; constructing strip combination schemes based on the triplet decision variables; constructing a regional target decomposition model with the objective function of minimizing total satellite usage cost, combined with coverage constraints and strip-related constraints; solving the regional target decomposition model to obtain the optimal strip combination scheme; and obtaining the triplet decision variables for each strip based on the optimal strip combination scheme. This application provides reasonable input for subsequent single-satellite scheduling, helps generate better scheduling schemes, maximizes the fulfillment of mission requirements, fully utilizes the observation capabilities of heterogeneous remote sensing constellations, and ensures their efficient collaborative operation.

The invention relates to a GIS (Geographic Information System)-based agile satellite area target observation meta-task generation method, which comprises the following steps of: inputting sub-satellite point shp data of a satellite, filtering invisible points, and intersecting with shp data of an area to be observed to obtain an available satellite; generating preliminary visible windows according to continuous time grouping, and combining the windows according to satellite maneuvering time constraint; calculating the maximum visual distance of the satellite and generating a maximum visual area; extracting region boundary point data, and calculating a side swing angle range; dividing a to-be-observed area into grid center points, and generating a roll angle data set and candidate strips; and finally, optimizing and selecting an optimal strip and a side-sway angle through a task planning algorithm. According to the method, shp data is used as input, a geographic information system (GIS) technology is adopted to process a complex spatial relationship between a satellite visual range and a to-be-observed area, the spatial calculation efficiency and precision are remarkably improved, the solution space of a combined optimization problem is converted from infinity to finite, problem solving becomes possible, and the method is suitable for large-scale popularization and application. And a foundation is laid for satellite scheduling and planning scheme formulation.

The invention provides a rapid satellite visibility forecasting method based on a numerical orbit predictor. The method comprises the steps that on the basis of current orbit parameters of a satellite, a satellite orbit is forecasted with a first preset step length, and a first orbit forecasting point sequence is obtained; carrying out interpolation processing to obtain a preliminarily estimated continuous orbit; extracting a time period of which the elevation angle is greater than or equal to a preset elevation angle threshold as at least one preliminary visible time interval; carrying out integration according to a second preset step length to generate a corresponding second orbit forecast point sequence; respectively calculating the elevation angle of the satellite relative to the specified ground target based on each point in the second orbit forecast point sequence to obtain discrete elevation angle data; performing polynomial fitting on the elevation data to obtain an elevation interpolation polynomial; and subtracting the preset elevation angle threshold value to obtain a target elevation angle threshold value function, solving a zero crossing point of the target elevation angle threshold value function, and determining a starting moment of the satellite in the final visible time interval and an ending moment when the satellite leaves the visible state.

The application discloses an intelligent scheduling method for agile satellite joint observation and data transmission, and relates to the technical field of satellite scheduling. Firstly, an agile satellite joint scheduling model under multiple constraint conditions is constructed based on satellite two-line orbit data and task coordinates. Then, a multiple knapsack algorithm is used to pre-allocate all tasks, and a candidate task set is generated for each satellite. Next, the single-satellite scheduling process is modeled as a Markov decision process, a state space including global physical states and structured task features is designed, and the action space is compressed into three high-level actions of observation, charging and transmission. Finally, hierarchical structure reinforcement learning is used for training, and action feasibility screening is performed through pre-computation. The high-level decision network adopts a dual deep Q network structure update strategy, and outputs an optimal scheduling scheme. The intelligent scheduling method can improve the task completion rate and resource utilization efficiency by combining the multiple knapsack algorithm and hierarchical structure reinforcement learning.

The application provides a layered multi-orbit multi-task satellite scheduling method, system, storage medium and electronic equipment, and relates to the technical field of satellite scheduling.The application provides a layered multi-orbit multi-task satellite scheduling method for large-scale satellite task scheduling problems, firstly, a task priority analysis index is provided for the priority of task allocation, so that the rationality of task arrangement is preliminarily ensured;then, a heuristic strategy different from the past is provided in the multi-orbit and multi-task matching stage, and an optimal orbit allocation tool model of multi-task in multi-orbit is innovatively developed, which can provide a high-quality task orbit allocation scheme in a relatively short time, and the optimal precision of the task orbit matching result is improved;finally, a single-orbit task scheduling function based on the time dependence of task value is provided for the single-orbit task scheduling, which is consistent with the profit change of the actual satellite task scheduling, and reflects the time dynamics of the model scheduling.

The invention discloses an agile earth satellite scheduling method based on multi-target neural strategy optimization, and the method comprises the steps: constructing a target model corresponding to a multi-target agile earth observation satellite scheduling problem, and enabling the target model to maximize the total observation income of a scheduling plan and maximize the average image quality of the scheduling plan as two optimization targets; a multi-target optimization strategy based on decomposition is adopted, a multi-target agile earth observation satellite scheduling problem is decomposed into a plurality of single-target optimization sub-problems, and each sub-problem corresponds to an optimization direction vector; constructing a scheduling sequence based on a Markov decision process, solving each single-target optimization sub-problem by using a neural network model of an encoder-decoder structure, and generating a scheduling sequence corresponding to each sub-problem; and combining the solutions of all single-target optimization sub-problems, and generating a Pareto frontier of the multi-target agile earth observation satellite scheduling problem through non-dominated sorting as a final satellite scheduling scheme.

The invention discloses an on-satellite interference avoidance method and device based on layered dynamic collaboration. According to the method, an interference avoidance task is divided into interference avoidance in a multi-core processor and interference avoidance among the multi-core processors. For interference avoidance among the multi-core processors, interference avoidance is carried out by a high-level scheduling controller according to the user density of adjacent space resource division units among the multi-core processors; for interference avoidance in the multi-core processor, the scheduling advance of each thread is set in a media access control layer in the multi-core processor at a bottom layer, so that different moments of adjacent threads on an assembly line correspond to the same scheduling moment, resource allocation is carried out at the same moment, a subsequent thread senses a scheduling result of a preorder thread, and resource allocation is carried out at the same moment. Therefore, interference avoidance is carried out. According to the method, the calculation complexity of a single decision point is reduced, the real-time requirement of on-satellite scheduling is met, and the scheduling flexibility and the interference response speed are remarkably improved.

The application discloses a scheduling method for LEO satellites, a medium and equipment, and relates to the technical field of satellite scheduling.The method comprises the following steps: a LEO satellite cooperative observation region of interest coverage system is constructed; the region of interest is divided according to the orbits and shooting fields of view of the LEO satellites in the system; and under the premise of minimum full coverage of image acquisition to the RoI, the satellite is distributed with a shooting task according to the division, with the minimum satellite camera rotation energy consumption as the target.The application not only reduces the rotation energy consumption of the camera, but also guarantees the size of the image, so that the overall energy consumption of the satellite camera is minimized, and the minimum RoI full coverage is realized.The application has excellent performance and good robustness.