Global Coverage Constellation Design Exploration Using Evolutionary Algorithms

Whittecar, William R.; Ferringer, Matthew P.

doi:10.2514/6.2014-4159

Cited by 25 publications

(9 citation statements)

References 7 publications

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“…Parallel computing with multi-objective evolutionary computation (MOEC) gives decisionmakers a powerful tool to search the complex tradeoffs of resiliency and affordability with an efficiency and effectiveness not achievable with traditional methods. (Whittecar, 2014)…”

Section: Tradeoff Framework For Satellite Designmentioning

confidence: 99%

“…The results are ported into a visual analytics program to explore design tradeoffs and inform the next conception of the problem. (Whittecar, 2014) Figure 3. GRIPS Decision Support Process (Whittecar, 2014) However, when mission requirements are more flexible, and the designer is interested in understanding the nature of underlying tradeoffs, heuristic tools provide the ability to approximate the set of optimal solutions that exist within a vast and otherwise intractable space.…”

Section: Grips Analytic Enginementioning

confidence: 99%

“…(Whittecar, 2014) Figure 3. GRIPS Decision Support Process (Whittecar, 2014) However, when mission requirements are more flexible, and the designer is interested in understanding the nature of underlying tradeoffs, heuristic tools provide the ability to approximate the set of optimal solutions that exist within a vast and otherwise intractable space. Generating such results and providing visualization of tradeoffs lets the decision maker see how a small sacrifice in for example, coverage performance may lead to significant cost savings in the form of launching to a lower orbit.…”

Section: Grips Analytic Enginementioning

confidence: 99%

“…Additionally, bringing stakeholders into the iterative problem formulation process allows for discovery of new solutions that otherwise might not be considered. (Whittecar, 2014)…”

Section: Grips Analytic Enginementioning

confidence: 99%

See 3 more Smart Citations

Model Based Tradeoffs for Affordable Resilient Systems

Wheaton

Madni

2018

INCOSE International Symp

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Affordability and resilience are two non‐functional requirements that are increasingly needed in 21st century systems. Since these attributes act in tradeoff fashion, a tradespace definition and evaluation framework is needed. This paper presents a model‐based approach that builds on two core capabilities: a framework to define the space system environment, and an analytic tool to set up the tradespace within the framework for tradeoff analysis with what‐if assumptions about the future space system environment.

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Section: Tradeoff Framework For Satellite Designmentioning

confidence: 99%

Section: Grips Analytic Enginementioning

confidence: 99%

Section: Grips Analytic Enginementioning

confidence: 99%

“…Additionally, bringing stakeholders into the iterative problem formulation process allows for discovery of new solutions that otherwise might not be considered. (Whittecar, 2014)…”

Section: Grips Analytic Enginementioning

confidence: 99%

See 2 more Smart Citations

Model Based Tradeoffs for Affordable Resilient Systems

Wheaton

Madni

2018

INCOSE International Symp

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“…We can cite Ferringer, et al 12 and Whittecar, et. al 13 . For a regional coverage problem, which is our object of study, Genetic Algorithms have been mostly employed compared to other methods.…”

Section: Introductionmentioning

confidence: 98%

Optimization of small satellite constellation design for continuous mutual regional coverage with multi-objective genetic algorithm

Meziane-Tani¹,

Métris²,

Lion³

et al. 2016

IJCIS

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This paper describes the application of an evolutionary optimization method to design satellite constellation for continuous regional coverage without intersatellite links. This configuration, called mutual coverage, is related to some technical limitations that exist on small satellite technology. The coverage of the north Algerian seismological network is taken as an example of application. A Multi Objective Genetic Algorithm (MOGA) is used to make a trade-off between the improvement of the coverage rate, the minimization of the total number of satellites and the reduction of the satellites' altitude. First, some experiments have been performed to find the weight distribution of the fitness function that shows the most significant improvement of the average fitness function. Then, some optimized constellation designs are given for different ranges of altitude and it is shown that the size of the MOGA constellation design is significantly reduced compared to the traditional geometrical design.

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Architectural Decisions for Communications Satellite Constellations to Maintain Profitability While Serving Uncovered and Underserved Communities

Portillo

Dolan

Cameron

et al. 2022

Satell Commun Network

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The rise of the commercial space industry has resulted in the development of megaconstellations that promise to provide global broadband. These constellations capitalize on advancements in technology, improved modeling capabilities, and reductions in launch cost. One of the significant open questions is whether these constellations will significantly increase access for uncovered and underserved communities, in addition to serving existing markets. This paper analyzes which constellation characteristics provide the best global coverage at the lowest operational cost. First, we present the demand model that assesses the number of under-served and uncovered users in a given region. Then, we present a genetic algorithm used to identify potential constellations. Finally, we conclude by identifying which characteristics are the most promising for broadband constellations, as well as predictions of how the market will develop in the coming years. Our analysis has found that geostationary (GEO) and medium Earth orbit (MEO) satellite constellations have the highest likelihood of profitability. LEO networks are on average 27% more expensive, but if designed wisely, they can be competitive. Our work shows that there are diminishing returns with large constellations, and that it is more cost effective to have a small number of highly capable satellites, rather than many low complexity satellites. Key technologies like high frequency bands and miniaturization of components can lead to further cost reductions and increase the competitiveness of LEO constellations.

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Global Coverage Constellation Design Exploration Using Evolutionary Algorithms

Cited by 25 publications

References 7 publications

Model Based Tradeoffs for Affordable Resilient Systems

Model Based Tradeoffs for Affordable Resilient Systems

Optimization of small satellite constellation design for continuous mutual regional coverage with multi-objective genetic algorithm

Architectural Decisions for Communications Satellite Constellations to Maintain Profitability While Serving Uncovered and Underserved Communities

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