Optimal design of the satellite constellation arrangement reconfiguration process

Fakoor, Mahdi; Bakhtiari, Majid; Mahshid, Soleymani

doi:10.1016/j.asr.2016.04.031

Cited by 26 publications

(9 citation statements)

References 13 publications

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“…Because the positions r1 s and r1 t and the transformation time t 2 are known, the transfer orbit and its required velocity changes can be obtained by employing the Lambert theorem. 37–39…”

Section: Lambert Targetingmentioning

confidence: 99%

“…Because the positions r s 1 and r t 1 and the transformation time t 2 are known, the transfer orbit and its required velocity changes can be obtained by employing the Lambert theorem. [37][38][39] Mathematical formulations to compute the position of an object after the time t (for example computing the position r s 1 after the time t 1 from the position r s 0 or the position r t 1 after the time t 1 þ t 2 from the position r t 0 ) are proposed in Section 'State vector of an object after time Át'. Also, the transfer orbit and its required velocity changes can be obtained using the formulas in Section 'Lambert targeting formulation'.…”

Section: Lambert Targetingmentioning

confidence: 99%

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The effects of parking orbit elements on designing of on-orbit servicing missions

Bakhtiari

Daneshjou

Mohammadi-Dehabadi

2017

Proceedings of the Institution of Mechanical Engineers, Part G:

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Nowadays on-orbit servicing operations such as satellite refuelling, debris removal and visual inspection are considered as the most important issues in the space missions. Mission planning has a key role on the designation of such missions and it is strongly dependent on the required fuel. In this study, a new approach is proposed for the designing of the on-orbit operations with considering the parking orbit elements and location of the servicing satellites. The proposed method improves the previous mission planning process of the multiple servicing satellites in the terms of the reduction in the mission fuel consumption. Furthermore, a special rendezvous maneuver is considered for meeting the servicing satellites and the targets. Also, the transfer orbits are obtained through Lambert targeting. The optimisation of the problem is carried out by particle swarm optimisation algorithm and Taguchi technique is employed for the robust design of the control parameters of the optimisation algorithm. The results reveal that the proposed approach is an efficient way in the reduction of the fuel consumption in the on-orbit servicing missions rather than the conventional methods.

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Section: Lambert Targetingmentioning

confidence: 99%

Section: Lambert Targetingmentioning

confidence: 99%

The effects of parking orbit elements on designing of on-orbit servicing missions

Bakhtiari

Daneshjou

Mohammadi-Dehabadi

2017

Proceedings of the Institution of Mechanical Engineers, Part G:

Self Cite

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“…Constellation reconfiguration, defined as "a deliberate change of the relative arrangements of satellites in a constellation by addition or subtraction of satellites and orbital maneuvering in order to achieve desired changes in coverage or capacity " [1], has a wide range of applications in system recovery after satellite failure [2,3], constellation staged deployment [1], rapid emergency response [4], and so on. To positively respond to future uncertainties and rapidly recover or enhance system overall performance, constellation reconfiguration has profound significance in both civilian and military aspects.…”

Section: Introductionmentioning

confidence: 99%

“…Weck et al proposed a generic framework for reconfiguration problems using an auction algorithm to determine the optimal allocation efficiently and reliably and applied the framework to the optimal design of low-orbit communications constellations [1]. Soleymani et al proposed a particle swarm/genetic hybrid algorithm based on Lambert's theory to determine the optimal reconfiguration with two constraints: the total reconfiguration cost and the final pattern [2]. To achieve collision avoidance and to minimize the total fuel consumption during constellation reconfiguration, Fakoor et al proposed a hybrid invasive weed optimization/particle swarm optimization (IWO/PSO) method to perform satellite assignment and design the orbits in the same step [3].…”

Section: Introductionmentioning

confidence: 99%

Optimal reconfiguration of constellation using adaptive innovation driven multiobjective evolutionary algorithm

Lee

Huang

et al. 2021

J. of Syst. Eng. Electron.

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Constellation reconfiguration is a critical issue to recover from the satellite failure, maintain the regular operation, and enhance the overall performance. The constellation reconfiguration problem faces the difficulties of high dimensionality of design variables and extremely large decision space due to the great and continuously growing constellation size. To solve such real-world problems that can be hardly solved by traditional algorithms, the evolutionary operators should be promoted with available domain knowledge to guide the algorithm to explore the promising regions of the trade space. An adaptive innovationdriven multi-objective evolutionary algorithm (MOEA-AI) employing automated innovation (AI) and adaptive operator selection (AOS) is proposed to extract and apply domain knowledge. The available knowledge is extracted from the final or intermediate solution sets and integrated into an operator by the automated innovation mechanism. To prevent the overuse of knowledgedependent operators, AOS provides top-level management between the knowledge-dependent operators and conventional evolutionary operators. It evaluates and selects operators according to their actual performance, which helps to identify useful operators from the candidate set. The efficacy of the MOEA-AI framework is demonstrated by the simulation of emergency missions. It was verified that the proposed algorithm can discover a non-dominant solution set with better quality, more homogeneous distribution, and better adaptation to practical situations.

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“…The optimization is implemented with known initial constellations and target sites in their work. Fakoor et al [13,14] used the hybrid Invasive Weed Optimization/Particle Swarm Optimization algorithm to deal with the constellation reconfiguration. Optimal assignment of the satellites and optimal orbital transfer were combined in one step to simplify the reconfiguration process.…”

Section: Introductionmentioning

confidence: 99%

Reconfigurable Satellite Constellation Design for Disaster Monitoring Using Physical Programming

Yang

et al. 2020

International Journal of Aerospace Engineering

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Data collection by satellites during and after a natural disaster is of great significance. In this work, a reconfigurable satellite constellation is designed for disaster monitoring, and satellites in the constellation are made to fly directly overhead of the disaster site through orbital transfer. By analyzing the space geometry relations between satellite orbit and an arbitrary disaster site, a mathematical model for orbital transfer and overhead monitoring is established. Due to the unpredictability of disasters, target sites evenly spaced on the Earth are considered as all possible disaster scenarios, and the optimal reconfigurable constellation is designed with the intention to minimize total velocity increment, maximum and mean reconfiguration time, and standard deviation of reconfiguration times for all target sites. To deal with this multiobjective optimization, a physical programming method together with a genetic algorithm is employed. Numerical results are obtained through the optimization, and different observation modes of the reconfigurable constellation are analyzed by a specific case. Superiority of our design is demonstrated by comparing with the existing literature, and excellent observation performance of the reconfigurable constellation is demonstrated.

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Optimal design of the satellite constellation arrangement reconfiguration process

Cited by 26 publications

References 13 publications

The effects of parking orbit elements on designing of on-orbit servicing missions

The effects of parking orbit elements on designing of on-orbit servicing missions

Optimal reconfiguration of constellation using adaptive innovation driven multiobjective evolutionary algorithm

Reconfigurable Satellite Constellation Design for Disaster Monitoring Using Physical Programming

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