12,697 research outputs found
Applying autonomy to distributed satellite systems: Trends, challenges, and future prospects
While monolithic satellite missions still pose significant advantages in terms of accuracy and
operations, novel distributed architectures are promising improved flexibility, responsiveness,
and adaptability to structural and functional changes. Large satellite swarms, opportunistic satellite
networks or heterogeneous constellations hybridizing small-spacecraft nodes with highperformance
satellites are becoming feasible and advantageous alternatives requiring the adoption
of new operation paradigms that enhance their autonomy. While autonomy is a notion that
is gaining acceptance in monolithic satellite missions, it can also be deemed an integral characteristic
in Distributed Satellite Systems (DSS). In this context, this paper focuses on the motivations
for system-level autonomy in DSS and justifies its need as an enabler of system qualities. Autonomy
is also presented as a necessary feature to bring new distributed Earth observation functions
(which require coordination and collaboration mechanisms) and to allow for novel structural
functions (e.g., opportunistic coalitions, exchange of resources, or in-orbit data services). Mission
Planning and Scheduling (MPS) frameworks are then presented as a key component to implement
autonomous operations in satellite missions. An exhaustive knowledge classification explores the
design aspects of MPS for DSS, and conceptually groups them into: components and organizational
paradigms; problem modeling and representation; optimization techniques and metaheuristics;
execution and runtime characteristics and the notions of tasks, resources, and constraints.
This paper concludes by proposing future strands of work devoted to study the trade-offs of
autonomy in large-scale, highly dynamic and heterogeneous networks through frameworks that
consider some of the limitations of small spacecraft technologies.Postprint (author's final draft
Genetic algorithms for satellite scheduling problems
Recently there has been a growing interest in mission operations scheduling problem. The problem, in a variety of formulations, arises in management of satellite/space missions requiring efficient allocation of user requests to make possible the communication between operations teams and spacecraft systems. Not only large space agencies, such as ESA (European Space Agency) and NASA, but also smaller research institutions and universities can establish nowadays their satellite mission, and thus need intelligent systems to automate the allocation of ground station services to space missions. In this paper, we present some relevant formulations of the satellite scheduling viewed as a family of problems and identify various forms of optimization objectives. The main complexities, due highly constrained nature, windows accessibility and visibility, multi-objectives and conflicting objectives are examined. Then, we discuss the resolution of the problem through different heuristic methods. In particular, we focus on the version of ground station scheduling, for which we present computational results obtained with Genetic Algorithms using the STK simulation toolkit.Peer ReviewedPostprint (published version
Optimization of intersatellite routing for real-time data download
The objective of this study is to develop a strategy to maximise the available bandwidth to Earth of a satellite constellation through inter-satellite links. Optimal signal routing is achieved by mimicking the way in which ant colonies locate food sources, where the 'ants' are explorative data packets aiming to find a near-optimal route to Earth. Demonstrating the method on a case-study of a space weather monitoring constellation; we show the real-time downloadable rate to Earth
The observation of Extensive Air Showers from an Earth-Orbiting Satellite
In this paper we review the main issues that are relevant for the detection
of Extensive Air Showers (EAS) from space. EAS are produced by the interaction
of Ultra-High Energy Cosmic Particles (UHECP) with the atmosphere and can be
observed from an orbiting telescope by detecting air fluorescence UV light. We
define the requirements and provide the main formulas and plots needed to
design and optimize a suitable telescope. We finally estimate its expected
performances in ideal conditions.Comment: 24 pages, 10 figures; submitted to Astroparticle Physics 27 pages, 14
figures; major revision; added new figures and sections; typos fixed. arXiv
admin note: substantial text overlap with arXiv:0810.571
A Practical Method to Estimate Information Content in the Context of 4D-Var Data Assimilation. II: Application to Global Ozone Assimilation
Data assimilation obtains improved estimates of the state of a physical system by combining imperfect
model results with sparse and noisy observations of reality. Not all observations used in data assimilation
are equally valuable. The ability to characterize the usefulness of different data points is important
for analyzing the effectiveness of the assimilation system, for data pruning, and for the design of future
sensor systems.
In the companion paper (Sandu et al., 2012) we derive an ensemble-based computational procedure
to estimate the information content of various observations in the context of 4D-Var. Here we apply
this methodology to quantify the signal and degrees of freedom for signal information metrics of satellite observations used in a global chemical data assimilation problem with the GEOS-Chem chemical
transport model. The assimilation of a subset of data points characterized by the highest information
content yields an analysis comparable in quality with the one obtained using the entire data set
Automated telescope scheduling
With the ever increasing level of automation of astronomical telescopes the benefits and feasibility of automated planning and scheduling are becoming more apparent. Improved efficiency and increased overall telescope utilization are the most obvious goals. Automated scheduling at some level has been done for several satellite observatories, but the requirements on these systems were much less stringent than on modern ground or satellite observatories. The scheduling problem is particularly acute for Hubble Space Telescope: virtually all observations must be planned in excruciating detail weeks to months in advance. Space Telescope Science Institute has recently made significant progress on the scheduling problem by exploiting state-of-the-art artificial intelligence software technology. What is especially interesting is that this effort has already yielded software that is well suited to scheduling groundbased telescopes, including the problem of optimizing the coordinated scheduling of more than one telescope
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