CBBA-based Decentralized Task Allocation Framework for Multiple Observation Satellites

In this study, we propose a decentralized task allocation algorithm for Earth observation missions utilizing a Low Earth Orbit (LEO) Synthetic Aperture Radar (SAR) satellite constellation. By employing the Consensus-Based Bundle Algorithm (CBBA), each satellite autonomously evaluates observation tasks based on priority, requested observation times, and imaging angles. Through iterative consensus and bundle adjustments, the proposed method ensures conflict-free task assignments without requiring centralized coordination. Simulation results demonstrate that the decentralized framework achieves high task coverage, maximizing task allocation per satellite and effectively meeting observation requests. The proposed approach provides enhanced scalability and flexibility, especially suitable for autonomous multi-satellite operations.