Publication | Closed Access
Evolutionary approaches to dynamic earth observation satellites mission planning under uncertainty
14
Citations
15
References
2019
Year
Earth ObservationEngineeringDynamic Resource AllocationRequest PriorityOperations ResearchOrbit DeterminationEvolution StrategyData ScienceUncertainty QuantificationPower Consumption ConstraintsSystems EngineeringCombinatorial OptimizationQuantitative ManagementEvolutionary ApproachesSatellite NetworkGeostationary OrbitMission PlanningComputer ScienceEvolutionary ProgrammingAerospace EngineeringSpace Mission DesignCloud ComputingRemote SensingTrajectory Optimization
Mission planning for Earth Observation Satellite operators typically implies dynamically altering how requests from different customers are prioritised in order to meet expected deadlines. A request corresponds to a given area of interest to capture on Earth. This exercise is challenging for different reasons. First, satellites are limited by maneuvers and power consumption constraints resulting in a limited surface that can be covered at each orbit. Consequently, many requests are in competition with each other and so all of them cannot be treated at each orbit. When a request priority is boosted, it may incidentally penalise surrounding requests. Second, there are several uncertain factors such as weather (in particular cloud cover) and future incoming requests that can impact the completion progress of the requests. With order books of increasing size and the planned operations of a growing number of satellites in a close future, there is a clear need for a decision support method.
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