Using Polarimetric Data from Space-Based Observers to Characterize High-Altitude Airborne Objects

Passively collected light curves are a fundamental byproduct of electro-optical sensing and are abundantly available for space objects. Previous work has demonstrated that considering the polarization of these light curves yields observable information regarding the material properties of the observed object. This paper applies the previously established multiple model adaptive estimation methods for space object characterization to characterize high-altitude atmospheric objects with light-curve measurements from orbital sensors. Alternative estimator weighting formulations are implemented, and it is shown that these alternative formulations demonstrate desirable behavior in situations with and without the truth present.