Joint Observation and Transmission Scheduling for Satellite Networks with Heterogeneous Missions

Low Earth Orbit (LEO) observation satellite systems play a critical role in a variety of applications, including environmental monitoring, urban planning, and national security. However, transmitting the data collected by numerous observation satellites to Earth remains a significant challenge. One promising approach to improve data transmission efficiency is to utilize LEO communication satellites as data relays. Existing researches in this area primarily focus on the inter-satellite communication scheduling, often neglecting the importance of satellite observation scheduling, which limits the potential performance gain. In this work, we investigate the joint optimization of observation and transmission scheduling in a satellite network with resource-constrained LEO satellites, taking into account the heterogeneity of observation missions and the dynamics of network topology. Specifically, we first introduce a Time-Expanded Graph (TEG) model to effectively represent dynamic network topology and satellite resource constraints. Based on this model, we formulate a network flow problem that incorporates both mission-specific characteristics and satellite energy costs. To reduce the solution complexity in large-scale networks, we propose a novel low-complexity Augmented Lagrangian-based Distributed Parallel Splitting (ALDPS) algorithm. Simulation results show that our proposed algorithm can improve the network utility by 8.3% to 28.1% compared to baseline methods.