Hybrid Sensing for Near-Earth Space Domain Awareness: Leveraging Space-Based Assets for Augmenting Optical Ground Observations

Abstract Because of recent advancements in space technologies, easier and more economical access to space, and an increase in commercial interests, the near-Earth space environment has witnessed an exploding number of objects being put into orbit. In particular, the low Earth orbit (LEO) region is at an increased risk of orbital collisions from large satellite constellation projects. Thus, monitoring LEO objects for space domain awareness and space traffic management has become increasingly imperative. In this paper, we use the concept of limited-CDF (cumulative distribution function) surface and mutual information for designing sensor tasking algorithms focusing on regular observation of known catalog LEO objects (follow-up). Observations are carried out using simulated ground-based optical telescope(s). The simulations are representative of realistic observation processes. We investigate how data from passive space-based sensors can be used to improve the follow-up performance of the telescope(s). A sensor-tasking framework is developed in which we conduct a comparative study to assess how different types of satellite constellation patterns such as Walker-Delta and Walker-Star affect the overall sensor tasking performance. Through several case studies, we (1) analyze the appropriate characteristics of the parameters to be optimized and their impact on the evolution of orbital state uncertainties, (2) compare different traditional and non-traditional algorithms for sensor tasking problem, (3) investigate the effect of measurements from different constellation configurations of passive space-based sensor, and (4) identify a suitable coordinate system for the limited-CDF surface construction.