An Intelligent Approach to Dynamic Scheduling System of Earth Observation Satellites

2011 ◽  
Vol 186 ◽  
pp. 591-595
Author(s):  
Yao Feng ◽  
Ren Jie He ◽  
Ju Fang Li ◽  
Li Ning Xing
Keyword(s):  
Dynamic Scheduling ◽  
Satellite System ◽  
Earth Observation ◽  
Benchmark Problems ◽  
High Quality ◽  
Scheduling System ◽  
Earth Observation Satellite ◽  
Earth Observation Satellites ◽  
Intelligent Approach ◽  
Hierarchical Genetic Algorithm

With the increased number of earth observation satellites, the process of acquiring high quality solution schedule for multi-satellite, multi-orbit and multi-user is more difficult than before. The multi-objective hierarchical genetic algorithm with preference and dynamic heuristic algorithm are proposed to solve the dynamic scheduling problem of earth observation satellite system. The experimental results performed on some benchmark problems suggest that this proposed approach is effective to the dynamic scheduling system.

scholarly journals A Study of Distributed Earth Observation Satellites Mission Scheduling Method Based on Game-Negotiation Mechanism

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6660
Author(s):  
Lihao Liu ◽  
Zhenghong Dong ◽  
Haoxiang Su ◽  
Dingzhan Yu
Keyword(s):  
Dynamic Scheduling ◽  
Environmental Changes ◽  
Search Algorithm ◽  
Integrated Management ◽  
Scheduling Algorithm ◽  
Earth Observation ◽  
Scheduling Problems ◽  
Satellite Systems ◽  
Earth Observation Satellites ◽  
Negotiation Mechanism

While monolithic giant earth observation satellites still have obvious advantages in regularity and accuracy, distributed satellite systems are providing increased flexibility, enhanced robustness, and improved responsiveness to structural and environmental changes. Due to increased system size and more complex applications, traditional centralized methods have difficulty in integrated management and rapid response needs of distributed systems. Aiming to efficient missions scheduling in distributed earth observation satellite systems, this paper addresses the problem through a networked game model based on a game-negotiation mechanism. In this model, each satellite is viewed as a “rational” player who continuously updates its own “action” through cooperation with neighbors until a Nash Equilibria is reached. To handle static and dynamic scheduling problems while cooperating with a distributed mission scheduling algorithm, we present an adaptive particle swarm optimization algorithm and adaptive tabu-search algorithm, respectively. Experimental results show that the proposed method can flexibly handle situations of different scales in static scheduling, and the performance of the algorithm will not decrease significantly as the problem scale increases; dynamic scheduling can be well accomplished with high observation payoff while maintaining the stability of the initial plan, which demonstrates the advantages of the proposed methods.

scholarly journals Application of a Multi-Satellite Dynamic Mission Scheduling Model Based on Mission Priority in Emergency Response

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1430 ◽  
Author(s):  
Jintian Cui ◽  
Xin Zhang
Keyword(s):  
Dynamic Scheduling ◽  
Search Algorithm ◽  
Earth Observation ◽  
Impact Factors ◽  
Scheduling Problem ◽  
Model Based ◽  
Scheduling Model ◽  
Earth Observation Satellites ◽  
Scheduling Plan ◽  
Satellite Scheduling

Emergency observations are missions executed by Earth observation satellites to support urgent ground operations. Emergency observations become more important for meeting the requirements of highly dynamic and highly time-sensitive observation missions, such as disaster monitoring and early warning. Considering the complex scheduling problem of Earth observation satellites under emergency conditions, a multi-satellite dynamic mission scheduling model based on mission priority is proposed in this paper. A calculation model of mission priority is designed for emergency missions based on seven impact factors. In the satellite mission scheduling, the resource constraints of scheduling are analyzed in detail, and the optimization objective function is built to maximize the observation mission priority and mission revenues, and minimize the waiting time for missions that require urgency for execution time. Then, the hybrid genetic tabu search algorithm is used to obtain the initial satellite scheduling plan. In case of the dynamic arrival of new emergency missions before scheduling plan releases, a dynamic scheduling algorithm based on mission priority is proposed to solve the scheduling problem caused by newly arrived missions and to obtain the scheduling plan of newly arrived missions. A simulation experiment was conducted for different numbers of initial missions and newly arrived missions, and the scheduling results were evaluated with a model performance evaluation function. The results show that the execution probability of high-priority missions increased because the mission priority was taken into account in the model. In the case of more satellite resources, when new missions dynamically arrived, the satellite resources can be reasonably allocated to these missions based on the mission priority. Overall, this approach reduces the complexity of the dynamic adjustment and maintains the stability of the initial scheduling plan.

The processing and use of data from Earth observation satellites

1984 ◽  
Vol 312 (1519) ◽  
pp. 109-114
Keyword(s):  
Remote Sensing ◽  
Earth Observation ◽  
Advanced Technology ◽  
System Designer ◽  
Satellite Systems ◽  
Use Of Data ◽  
Observation Systems ◽  
Earth Observation Satellite ◽  
Institutional Aspects ◽  
Earth Observation Satellites

Most systems reliant on advanced technology present a familiar dilemma: the system designer does not know what the customer wants, while the customer does not understand the technology well enough to know what is possible. Although Earth observation satellite systems ought ideally to be designed for all customer needs, this is impossible for several reasons. Not least of these is the difficulty of identifying at the outset all, or even most, of the possible customers. This circumstance makes the creation of Earth observation systems somewhat speculative and imposes particular constraints on the subsystems for processing and use of the data. This paper discusses the technical and institutional aspects of processing and dissemination of data from remote-sensing satellites for the benefit of the user.

scholarly journals Genetic Programming Method for Satellite System Topology and Parameter Optimization

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Jinhui Li ◽  
Yunfeng Dong ◽  
Ming Xu ◽  
Hongjue Li
Keyword(s):  
Genetic Programming ◽  
System Design ◽  
Evaluation System ◽  
Satellite System ◽  
Earth Observation ◽  
Tree Structure ◽  
Programming Method ◽  
Earth Observation Satellite ◽  
Physical Fields ◽  
System Topology

In this paper, a genetic programming method for satellite system design is proposed to simultaneously optimize the topology and parameters of a satellite system. Firstly, the representation of satellite system design is defined according to the tree structure. The genetic programming method is designed based on that representation. Secondly, according to the tree structure of different satellite schemes, different multiscale satellite models are established, in which various physical fields couple together. Then, an evaluation system is also proposed to test the performances of different satellite schemes. Finally, the application to the design of an earth observation satellite demonstrates the effectiveness of the proposed method.

scholarly journals Imaging-Duration Embedded Dynamic Scheduling of Earth Observation Satellites for Emergent Events

2015 ◽  
Vol 2015 ◽  
pp. 1-31 ◽  
Author(s):  
Xiaonan Niu ◽  
Hong Tang ◽  
Lixin Wu ◽  
Run Deng ◽  
Xuejun Zhai
Keyword(s):  
Dynamic Scheduling ◽  
Earth Observation ◽  
Dynamic Adjustment ◽  
Task Execution ◽  
Nsga Ii ◽  
Satellite Imaging ◽  
Imaging Time ◽  
Earth Observation Satellites ◽  
Satellite Scheduling ◽  
Two Stages

We present novel two-stage dynamic scheduling of earth observation satellites to provide emergency response by making full use of the duration of the imaging task execution. In the first stage, the multiobjective genetic algorithm NSGA-II is used to produce an optimal satellite imaging schedule schema, which is robust to dynamic adjustment as possible emergent events occur in the future. In the second stage, when certain emergent events do occur, a dynamic adjusting heuristic algorithm (CTM-DAHA) is applied to arrange new tasks into the robust imaging schedule. Different from the existing dynamic scheduling methods, the imaging duration is embedded in the two stages to make full use of current satellite resources. In the stage of robust satellite scheduling, total task execution time is used as a robust indicator to obtain a satellite schedule with less imaging time. In other words, more imaging time is preserved for future emergent events. In the stage of dynamic adjustment, a compact task merging strategy is applied to combine both of existing tasks and emergency tasks into a composite task with least imaging time. Simulated experiments indicate that the proposed method can produce a more robust and effective satellite imaging schedule.

scholarly journals An Efficient Local Search Heuristic for Earth Observation Satellite Integrated Scheduling

2020 ◽  
Vol 10 (16) ◽  
pp. 5616 ◽  
Author(s):  
Yuning Chen ◽  
Ji Lu ◽  
Renjie He ◽  
Junwei Ou
Keyword(s):  
Local Search ◽  
Programming Model ◽  
Image Data ◽  
Earth Observation ◽  
Search Heuristic ◽  
Algorithm Efficiency ◽  
Integrated Scheduling ◽  
Local Search Heuristic ◽  
Earth Observation Satellite ◽  
Earth Observation Satellites

Earth observation satellites (EOSs) are taking a large number of pictures with increasing resolution which produce massive image data. Satellite data transmission becomes the bottleneck part in the process of EOS resource management. In this paper, we study the earth observation satellite integrated scheduling problem (EOSIS) where the imaging activities and download activities are considered integratively. We propose an integer linear programming model to formulate the problem. Due to the NP-hardness of the problem, we propose an efficient local search heuristic (ELSH) to solve problems of large size. ELSH uses a dedicated local search method to guarantee algorithm performance and efficient constraint handling mechanisms to guarantee algorithm efficiency. Numerical experimental results show that the algorithm demonstrates excellent performance on a set of benchmark instances. The ELSH achieves optimal results for all small-size instances (with 50 targets, two satellites, and three ground stations), and is very robust for large instances with up to 2000 targets. Moreover, the proposed ELSH easily dominates the state-of-the-art algorithm.

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