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Mass Estimation Through Fusion of Astrometric and Photometric Data Collection with Application to High Area-to-Mass Ratio Objects Matthew J Richardson This thesis work presents the formulation for a tool developed in MATLAB to determine the mass of a space object from the fusion of astrometric and photometric data. The application for such a tool is to better model the mass estimation method used for high area-to-mass ratio objects found in high altitude orbit regimes. Typically, the effect of solar radiation pressure is examined with angles observations to deduce area-to-mass ratio calculations for space objects since the area-to-mass ratio can greatly affect its orbital dynamics. On the other hand, photometric data is not sensitive to mass but is a function of the albedo-area and the rotational dynamics of the space object. Thus from these two data types it is possible to disentangle intrinsic properties using albedo-area and area-to-mass and ultimately determine the mass of a space object. Three case studies were performed for the different orbit regimes: geosynchronous, highly elliptic, and medium earth orbit. The position states were either initialized with a two line element set or with initial orbit determination methods to simulate data which was run through an unscented Kalman filter to estimate the translational and rotational states of the space object as well as the mass and albedo area. In the geosynchronous and highly elliptic cases the tool was able to accurately predict the mass value to within ±5kg of the true value based on a 95% confidence interval which will allow applications to understanding high area-to-mass objects with high certainty.

Mass Estimation through Fusion of Astrometric and Photometric Data Collection with Application to High Area-to-Mass Ratio Objects