• Journal of Astronomy and Space Sciences
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• v.20 no.3
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• pp.227-238
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• 2003

Spacecraft mission planning functions including event prediction, mission scheduling, command planning, and ground track display have been developed for the KOMPSAT-2 mission operations. Integrated event prediction functions including satellite orbital events, user requested imaging events, and satellite operational events have been implemented. Mission scheduling functions have been realized to detect the mission conflicts considering the user specified constraints and resources, A conflict free mission scheduling result is mapped into the spacecraft command sequences in the command planning functions. The command sequences are directly linked to the spacecraft operations using eXtensible Markup Language(XML) for command transmission. Ground track display shows the satellite ground trace and mission activities on a digitized world map with zoom capability.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.26 no.2
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• pp.54-60
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• 2018

This paper contains the multi-mission scheduling optimization of UAV within a given operating time. Mission scheduling optimization problem is one of combinatorial optimization, and it has been shown to be NP-hard(non-deterministic polynomial-time hardness). In this problem, as the size of the problem increases, the computation time increases dramatically. So, we applied the genetic algorithm to this problem. For the application, we set the mission scenario, objective function, and constraints, and then, performed simulation with MATLAB. After 1000 case simulation, we evaluate the optimality and computing time in comparison with global optimum from MILP(Mixed Integer Linear Programming).

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.12
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• pp.1163-1170
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• 2008

A mission scheduling optimization algorithm according to the purpose of satellite operations is developed using genetic algorithm. Satellite mission scheduling is making a timetable of missions which are slated to be performed. It is essential to make an optimized timetable considering related conditions and parameters for effective mission performance. Thus, as important criterions and parameters related to scheduling vary with the purpose of satellite operation, those factors should be fully considered and reflected when the satellite mission scheduling algorithm is developed. The developed algorithm in this study is implemented and verified through a comprehensive simulation study. As a result, it is shown that the algorithm can be applied into various type of the satellite mission operations.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.56-63
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• 2016

We consider a satellite mission scheduling problem, which is a promising problem in recent satellite industry. This problem has various considerations such as customer importance, due date, limited capacity of energy and memory, distance of the location of each mission, etc. Also we consider the objective of each satellite such as general purpose satellite, strategic mission and commercial satellite. And this problem can be modelled as a general knapsack problem, which is famous NP-hard problem, if the objective is defined as to maximize the total mission score performed. To solve this kind of problem, heuristic algorithm such as taboo and genetic algorithm are applied and their performance are acceptable in some extent. To propose more efficient algorithm than previous research, we applied a particle swarm optimization algorithm, which is the most promising method in optimization problem recently in this research. Owing to limitation of current study in obtaining real information and several assumptions, we generated 200 satellite missions with required information for each mission. Based on generated information, we compared the results by our approach algorithm with those of CPLEX. This comparison shows that our proposed approach give us almost accurate results as just less than 3% error rate, and computation time is just a little to be applied to real problem. Also this algorithm has enough scalability by innate characteristic of PSO. We also applied it to mission scheduling problem of various class of satellite. The results are quite reasonable enough to conclude that our proposed algorithm may work in satellite mission scheduling problem.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.1
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• pp.48-57
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• 2010

A comparison of two kinds of scheduling optimization algorithms is presented in this paper. As satellite control and operation techniques have been developed, satellite missions became more complicated and overall quantity of missions also increased. These changes require more specific consideration and a huge amount of computation for the satellite mission scheduling. Therefore, it is a good strategy to make a scheduling optimization algorithm for the efficient satellite mission scheduling operation. In this paper, two kinds of scheduling optimization algorithms are designed with tabu-search algorithm and genetic algorithm respectively. These algorithms are applied for the same mission scenario and the results of each algorithm are compared and analyzed.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.6
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• pp.572-578
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• 2010

In this paper, the final fitness results of the satellite mission scheduling algorithm, which is designed by using the genetic algorithm, are simulated and compared with respect to the control constants. Heuristic algorithms, including the genetic algorithm, are good to find global optima, however, we have to find the optimal control constants before its application to a problem, because the algorithm is strongly effected by the control constants. In this research, the satellite mission scheduling algorithm is simulated with different crossover probability and mutation probability, which is major control constant of the genetic algorithm.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.30 no.1
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• pp.139-146
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• 2002

This paper describes the devlopment and implementation for the KOMPSAT-1 scheduling & automatic command plan generator(KSCG). Some problems in mission planning and command planning had occurred using the mission & command planning s/w in MAPS(Missin Analysis and Planning Subsystem) during the LEOP(Launch & Early Orbit Phase) & early normal mission phase due to lots of manual input process and non-automatic process. Therefore, the more mission operations for KOMPSAT-1. In order to prevent the development of new one(KSCG) which should reduce the manual process and generate automatically the command plan has been needed. As a result, the mission operations of KOMPSAT-1 has greatly became stable and more effient.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.1
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• pp.89-100
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• 2016

Given the unpredictability of the space environment, satellite communications are manually performed by exchanging telecommands and telemetry. Ground support for orbiting satellites is given only during limited periods of ground antenna visibility, which can result in conflicts when multiple satellites are present. This problem can be regarded as a scheduling problem of allocating antenna support (task) to limited visibility (resource). To mitigate unforeseen errors and costs associated with manual scheduling and mission planning, we propose a novel method based on a genetic algorithm to solve the ground support problem of multiple satellites and antennae with visibility conflicts. Numerous scheduling parameters, including user priority, emergency, profit, contact interval, support time, remaining resource, are considered to provide maximum benefit to users and real applications. The modeling and formulae are developed in accordance with the characteristics of satellite communication. To validate the proposed algorithm, 20 satellites and 3 ground antennae in the Korean peninsula are assumed and modeled using the satellite tool kit (STK). The proposed algorithm is applied to two operation modes: (i) telemetry, tracking, and command and (ii) payload. The results of the present study show near-optimal scheduling in both operation modes and demonstrate the applicability of the proposed algorithm to actual mission control systems.

• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.2
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• pp.177-188
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• 2024

The strategic UAV for theater level ISR(Intelligence, Surveillance and Reconnaissance) mission typically has numerous ground targets over area of responsibility(AOR) or area of operation(AO). It is necessary to automatically incorporate these multitude of ground targets into mission planning process in order to collect ISR images before actual flight mission. In addition, weather information such as wind direction and/or velocity may have significant impacts on the qualities of collected sensor images, especially in SAR(Synthetic Aperture Radar) images. Thus weather factors in the operation altitude should also be considered in the mission planning stage. In this study, we propose a novel mission planning scheme based on target scheduling and deviation correction method incorporating weather factors.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.6
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• pp.237-244
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• 2013

We propose Energy-constrained Multiprocessor Real-Time Scheduling algorithms for (m,k)-firm deadline constrained tasks (EMRTS-MK). Rather than simply saving as much energy as possible, we consider energy as hard constraint under which the system remains functional and delivers an acceptable performance at least during the prescribed mission time. We evaluate EMRTS-MKs in several experiments, which quantitatively show that they achieve the scheduling objectives.