Multiple agile Earth observation satellites, oversubscribed targets scheduling using complex networks theory

The Earth observation satellites (EOSs) scheduling is of great importance to achieve efficient observation missions. The agile EOSs (AEOS) with stronger attitude maneuvering capacity can greatly improve observation efficiency while increasing scheduling complexity. The multiple AEOSs, oversubscribed targets scheduling problem with multiple observations are addressed, and the potential observation missions are modeled as nodes in the complex networks. To solve the problem, an improved feedback structured heuristic is designed by defining the node and target importance factors. On the basis of a real world Chinese AEOS constellation, simulation experiments are conducted to validate the heuristic efficiency in comparison with a constructive algorithm and a structured genetic algorithm

Task Scheduling of Multiple Agile Satellites with Transition Time and Stereo Imaging Constraints

This paper proposes a framework for scheduling the observation and download tasks of multiple agile satellites with practical considerations such as attitude transition time, onboard data capacity, and stereoscopic image acquisition. A mixed integer linear programming (MILP) formulation for optimal scheduling that can address these practical considerations is introduced. A heuristic algorithm to obtain a near-optimal solution of the formulated MILP based on the time windows pruning procedure is proposed. A comprehensive case study demonstrating the validity of the proposed formulation and heuristic is presented