Eric Gorman, Quantum Space; Collin Deans, Quantum Space; Mohamed Nassif, Quantum Space; Elizabeth Frank, Quantum Space
Keywords: QuantumNet: A Scalable Cislunar Space Domain Awareness Constellation, cislunar, SDA, constellation, optimization, pareto, sensor, model
Abstract:
The expected uptick in missions to the Moon over the next decade will drive demand for data related to tracking, monitoring, and coordinating the behavior of actors in cislunar space. Given the vastness of Cislunar space, no single spacecraft can provide the coverage required. Here we present a subset of the capabilities of a tool developed for architecting a cislunar space domain awareness (SDA) constellation called QuantumNet, enabling optimization across sensor capability, orbit design, and asset distribution in cislunar space. An optical sensor throughput model was developed in MATLAB using first-principles physics that simulates photons reflecting from a resident space object (RSO) with specified physical geometry at a given range and solar phase angle, and reports signal-to-noise ratio (SNR) across the detector. This model is then solved for the maximum range at which a threshold SNR value could be achieved as a function of solar phase angle, resulting in an instantaneous field of regard over all possible viewing angles for a given sensor configuration. By simulating the geometric placement of these sensor configurations in cislunar space using satellite position states generated in Ansys Government Initiatives (AGI) Systems Tool Kit (STK) over one lunar period, a general constellation coverage model is constructed that allows volume coverage metrics to be optimized as a function of visible sensor configuration, satellite orbit selection, and number of satellites within each orbit. The constellation coverage model is embedded within Ansys ModelCenter, and a genetic algorithm is employed to optimize designs across multiple observation metrics. Feasible designs, as well as Pareto-optimal designs, are shown for two possible target coverage volumes.
Date of Conference: September 19-22, 2023
Track: Cislunar SDA