Space Signatures for Rapid Unambiguous Identification of Satellites

The research objective of this proposal is to demonstrate a semi-automated association process based upon photometric and astrometric data collected by deep space sensors for UnCorrelated Tracks (UCTs) found in and near the Geosynchronous Earth Orbit (GEO) regime. We will derive a method for parameterizing photometric data such that it can be fused with astrometric (kinematic) parameters, some of which are already used in the current manual process. The fusion process will provide a framework for assigning probabilistic associations in a semi-automated way. The Phase I technical objectives are focused upon how to process photometric information to assist in decreasing the association uncertainty. The key technical issue is how well the photometric features can discriminate between different objects, as our hypothesis rests on the addition of photometric information to astrometric data. During Phase I, we will focus on demonstrating what information can be added by photometric features. Statistical tests will be performed to analyze how quickly the association process can converge to the correct solution using both photometric and astrometric data.