Image collection optimization in the design and operation of lightweight, low areal-density space telescopes

Abstract

Demand for space imagery has increased dramatically over the past several decades. Scientific and government agencies rely on Earth-observing space assets for a variety of functions, including mapping, agriculture, and intelligence. In recent years, online interactive mapping services have created a large demand for high-resolution commercial satellite imagery. The satellite systems launched to meet the demand for imagery have two major objectives: 1) efficient global Earth coverage and 2) responsiveness to real-time events. Depending on the specific application, mission architects may particularly value one objective. Commercial satellites need to fulfill tasking requests from customers and are primarily focused on global accessibility and efficient imaging. Engineers may design military or environmental warning satellites, on the other hand, to focus on quickly responding to events in unpredictable locations. This thesis investigates two elements in support of the design of Earth observing satellite systems. The first part is a study of a responsive satellite constellation architecture. The focus within the Responsive Space community has primarily been on small, lightweight, disposable satellite systems. Industry and academia have done less work to consider architectures that meet the responsiveness objective while still providing global coverage with sustainable orbits. This thesis analyzes an architecture that supports objectives of efficient coverage of the globe and also responsiveness to arising targets. The space community has also demonstrated significant interest in lightweight space telescopes. These systems offer launch cost savings and, in the case of segmented aperture optics, can be stowed and deployed on orbit.

(cont.) The reduction in mass comes, however, at the price of structural flexibility, which affects the satellite's ability to efficiently image targets. The second part of this thesis explores how satellite dynamic properties affect the ability to provide efficient imaging. Satellite scheduling optimization formulations, including graph search, integer programming, and dynamic programming, enable evaluation of imaging efficiency. Integration of imaging performance metrics into a trade-space analysis tool allows for more informed decisions early in the satellite design process.