Optimization of Flower Constellation Applied to Cislunar Environment Observations

The growing number of space objects and the consequent increasing threat of collisions, requires a continuous surveillance and monitoring of the space environment around Earth with ground and space-based sensors. Lunar missions have also gained a renewed interest from the scientific community; therefore, it is essential to start tracking and monitoring the cislunar environment as well in order to guarantee its safety and reliability. The aim of this paper is to optimize the design of a satellite constellation in Low-Earth Orbit to maximize the coverage of a desired portion of the sky and the available observations provided by optical devices mounted onboard satellites. This is carried out by considering the Lattice Flower Constellations (LFCs) theory. By employing this theory, the relative distribution of the satellites belonging to the constellation is fixed and its number of symmetries is maximized. Furthermore, the LFC theory requires a minimum number of parameters (represented by the number of orbital planes, the number of satellites per orbital plane, and the configuration number) to describe the constellation. In this paper, an optimization approach based on the metaheuristic algorithm Particle Swarm Optimization (PSO) is pursued to maximize the coverage of the desired portion of the sky. The proposed methodology is applied to two cases: global coverage of the Celestial Sphere and partial coverage of the sky, with particular regard to the cislunar environment. The effective and continuous coverage of the desired Celestial Sphere area allows the detection and tracking of space objects or the monitoring and surveillance of a precise portion of the sky.