Adaptable Data Download Schedules for Agile Earth-Observing Satellites

Maillard, Adrien; Verfaillie, Gérard; Pralet, Cédric; Jaubert, Jean; Sebbag, I.; Fontanari, Frédéric; L'Hermitte, Julien

doi:10.2514/1.i010383

Cited by 9 publications

(4 citation statements)

References 10 publications

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“…The problem is solved with an iterative repair search based algorithm in which the improvement mechanism is based on swaps and a new heuristic based on the maximum flexibility is introduced. The latest trend in space mission planning and scheduling includes a similar method that involves randomness in producing the initial solutions which are then also improved, called Squeaky Wheel Optimization (SWO) [14] [7] [15] [16]. In this method, the improvements are choices of changes in the order by which the tasks are considered for scheduling.…”

Section: Relevant Workmentioning

confidence: 99%

Ant-Based Automated Mission Planning for Data Relay Space Missions

Ntagiou¹,

Armellín²,

Iacopino

et al. 2019

Journal of Aerospace Information Systems

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The Earth Observation (EO) market is rapidly growing due to technology miniaturization, cheaper launch opportunities and wider spectrum of EO applications. Along with an exponential growth of the ground based users that can access Low Earth Orbit (LEO) spacecraft data, this growing community represents an important demand for Data Relay missions. LEO spacecraft have short visibility windows to the Ground Stations (GS) which limit their throughput. Data Relay missions are comprised of spacecraft at higher altitude orbits (Geostationary Orbits) acting as relays of data among LEO spacecraft and GS. Those missions are then able to offer more frequent data downlink opportunities to the LEO spacecraft thus increasing the volume of the data reaching the ground and improving the responsiveness between users' requests and downlink operations. Ground based Mission Planning Systems (MPS) are commonly managing such complex missions, representing a large operational cost. In this paper, we propose the application of a Swarm Intelligence algorithm to the design of an automated MPS for Data Relay missions. Automated MPS have the potential of saving operational costs while leaving the high level decisions to human operators. This paper represents the first time that an Ant Colony Optimization (ACO) algorithm is applied to this type of scheduling problem. This family of algorithms is generally found to offer good level of efficiency and scalability. In this work, we compare our approach against an algorithm popular in literature, called Squeaky Wheel Optimization (SWO) and show how our ACO algorithm outperforms it.

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Section: Relevant Workmentioning

confidence: 99%

Ant-Based Automated Mission Planning for Data Relay Space Missions

Ntagiou¹,

Armellín²,

Iacopino

et al. 2019

Journal of Aerospace Information Systems

View full text Add to dashboard Cite

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“…In other studies on Earth observing satellites, the ground system computes an energy activation threshold for each observation with the objective to guarantee that all high-priority observations are always fulfilled (Maillard et al 2015). Flexible download plans were also considered in these studies to manage uncertain memory consumptions (Maillard et al 2016), but memory is not a bottleneck in our case. Last, in works on the NASA Mars 2020 rovers, each activity planned offers a set of ranked alternatives called switch groups, with for each alternative an energy activation threshold computed on the ground (Agrawal et al 2021).…”

Section: Introductionmentioning

confidence: 99%

Building Resource-Dependent Conditional Plans for an Earth Monitoring Satellite

Pralet¹,

Doose²,

Anxionnat³

et al. 2022

ICAPS

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This paper introduces a conditional planning and execution system for an Earth monitoring satellite. This system builds plans containing optional acquisitions that are activated or not at execution time depending on the amount of energy actually available. One originality is that the energy activation thresholds computed on the ground take into account the capacity of the satellite to use an heliocentric pointing or switch off the payload when acquisitions are canceled. Another originality is that the conditional planner proposed uses several energy propagation models, from conservative models containing margins on power production to optimistic models that allow opportunistic acquisitions to be planned.

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“…There are several ongoing projects to design the next generation of Earth observation satellite constellations that will replace the currently operating satellites [4][5][6]. The next-generation satellites will improve the efficacy of the entire satellite system in terms of system operability, observation quality, capacity, and a delay between a user request and the arrival of observation data.…”

Section: Introductionmentioning

confidence: 99%

Optimization-Based Scheduling Method for Agile Earth-Observing Satellite Constellation

Cho

Kim

Choi

et al. 2018

Journal of Aerospace Information Systems

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This Paper proposes a two-step binary linear programming formulation for task scheduling of a constellation of low-Earth-orbit satellites and demonstrates its applicability and scalability to obtain high-quality solutions using a standard mixed-integer linear programming solver. In this instance, the goal of satellite constellation task scheduling is to allocate each task for the satellites and to determine the task starting times in order to maximize the overall mission performance metric. The scheduling problem is formulated to find the solution by first finding a set of candidate communication time intervals for each satellite/ground-station pair as one of the key constraints and time tabling the observation task to acquire the user-requested data, with the incorporation of key constraints for satellite constellation operation. Numerical experiments are designed for investigating the trends, sensitivity, and characteristics of scheduling outputs based on multiple representative instances. The performance of the scheduling solutions by the proposed two-step binary linear programming method exhibits significant improvement of up to 35% in the number of assignments and the sum of profits over the general greedy algorithm.

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Adaptable Data Download Schedules for Agile Earth-Observing Satellites

Cited by 9 publications

References 10 publications

Ant-Based Automated Mission Planning for Data Relay Space Missions

Ant-Based Automated Mission Planning for Data Relay Space Missions

Building Resource-Dependent Conditional Plans for an Earth Monitoring Satellite

Optimization-Based Scheduling Method for Agile Earth-Observing Satellite Constellation

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