An approach based on multiobjective genetic algorithms to schedule observations in planetary remote sensing missions

Abstract

Data acquisition in planetary remote sensing missions is influenced by complex environmental resource-and instrument-specific constraints. This impedes to perform observations at any given time during the mission and with any of the instruments composing the scientific payload. This article presents an approach to automatic scheduling of acquisition operations of a remote sensing instrument composing the scientific payload of a mission. The methodology first subdivides the long available observation time intervals into shorter segments and then performs a selection of them, producing an acquisition schedule, optimized with respect to scientific requirements, instrument characteristics, and mission constraints. The scheduling problem is modeled as a multiobjective optimization problem and solved by using Genetic Algorithms (GAs). GAs are able to efficiently explore the solution space by considering different competing objective functions, reaching high-quality solutions. These solutions represent different optimized tradeoffs among the considered instrument-specific quality metrics. The approach is demonstrated on the operations of Radar for Icy Moons Exploration (RIME), a radar sounder onboard Jupiter Icy Moons Explorer. The obtained results show a high potential of the proposed methodology.