Distributed and Resilient Planning-Control for Optimal LEO Satellite Constellation Coverage

Coverage services provided by LEO satellite constellations have served as the base platform for various space applications. However, the surge of space attacks such as physical and cyber attacks are greatly endangering the security of satellite constellations and the integrity of the coverage services. As repairs of satellites are challenging, a distributed protection mechanism is necessary to ensure the self-healing of the satellite constellation coverage from different attacks. To this end, this paper establishes a distributed framework to empower a resilient satellite constellation coverage design and control within a single orbit. Each satellite can make decisions individually to recover from adversarial and non-adversarial attacks and keep providing coverage service. We first provide the average coverage cost to measure the coverage performance. Then, we formulate the joint resilient coverage planning-control problem as a two-stage problem by decoupling the coverage planning and fuel-optimal control. A distributed algorithm is proposed to find the optimal coverage configuration. The multi-waypoint MPC methodology is adopted to steer satellites to the target configuration. Finally, we use a typical LEO satellite constellation as a case study to corroborate the results.