Observability of Light Curve Inversion for Shape and Feature Determination Exemplified by a Case Analysis

As the resident space object population continues to grow, Space Situational Awareness becomes most important for reducing the risk of collision among these objects. Obtaining object characteristic information, such as shape or reflectivity properties among other aspects, is essential for precise orbit propagation and object identification. Measurements of object brightness over time, or so-called light curve measurements, have a rich history of use for characterizing astronomical objects. If light curve measurements do not sufficiently capture the geometry of a system, the resulting shape and characteristic estimates from light curve inversion are not guaranteed to be accurate. Previous methods for increasing the likelihood of sufficient sampling involve acquisition of unfeasibly large amounts of light curve data, which binds valuable sensor resources to focus on one object for long periods of time. In this paper, observability is defined for the shape inversion problem from light curve measurements with a diffuse reflection model. This opens the horizon for efficient and effective object characterization on a routine basis within a sensor network, thus making dedicated, several night-long observations of one object for characterization obsolete. A realistic orbit and attitude motion are implemented to determine whether supplied light curve measurements of an Atlas V upper stage are sufficient for light curve inversion.