Adaptive Game-Based Strategy for Spacecraft Counter-Reconnaissance

This paper studies the problem of payload protection for a target spacecraft in counter-reconnaissance. The target spacecraft aims to avoid having its critical payloads captured within the imaging areas of reconnaissance spacecraft, while minimizing fuel consumption and service disruption, as well as preventing hazards such as collisions and direct solar illumination of sensors. In this complex confrontation between reconnaissance and counter-reconnaissance, the outcome is highly sensitive to both parties' strategies. Therefore we propose an adaptive non- zero-sum game-based strategy by leveraging information asymmetry, opponent strategy inference and imaging conditions. To further achieve online decision-making, we perform a situation-based real-time optimization of the value functions during strategy computation, significantly reducing the computational load without compromising global game performance. Simulation results validate that this strategy provides effective payload protection at a low cost, even when confronted with high-threat adversarial situations, and exhibits a certain level of robustness and adaptability to scenario uncertainties.