Integrated scheduling of observation and download tasks for heterogeneous satellites with memory capacity

Abstract

In this paper, a method is proposed for allocating observation and download tasks for various types of satellites using Mixed-Integer Linear Programming (MILP). The problem includes additional constraints considering memory capacity in addition to the basic scheduling constraints, aiming to maximize the download of observation images and minimize cross-visit times while facilitating collaboration among heterogeneous satellites. To achieve this, the paper defines heterogeneity and presents various constraints and objective functions in mathematical expressions for the transformation into a MILP-based optimization problem. In this process, key and auxiliary variables for scheduling, as well as operational efficiency metrics like the generalized Cross-coverage Gap, are introduced. To effectively handle increasing computation times with the growing scale of the problem, limits on optimization variables using the optimality gap are also proposed. Simulation results for various scenarios are presented to validate the effectiveness and problem-solving capabilities of the proposed approach.