Estimation of Spacecraft Attitude Motion and Vibrational Modes Using Simultaneous Dual-Latitude Ground-Based Data

Cutting-edge Space Situational Awareness (SSA) research calls for improved methods for rapidly characterizing resident space objects. In this thesis, this will take the form of speeding up convergence of spacecraft attitude estimates, and of a non-model-based approach to the detection of vibrational modes. Because attitude observability from photometric data is angle-based, dual-site simultaneous photometric observations of a resident space object are predicted to improve the convergence speed and steady-state error of spacecraft attitude state estimation from ground-based sensor data. Additionally, it is predicted that by adding polarimetric data to the measurements, the speed of convergence and steady-state error will be reduced further. This thesis models satellite motion and measurements from ground-based sensors for dual-latitude simultaneous light curve simulation, then develops a data fusion process to combine photometric, astrometric, and polarimetric data from both sites in order to more quickly estimate the attitude of an RSO. The Fractional Fourier Transform shows promise as a non-model-based approach to the detection of input vibrational frequencies from the degree of linear polarization. The main results are that dual-site observation geometry is conducive to slight improvements of attitude filter performance, and the addition of polarimetric data to the measurements yields much improved performance over both the single-site and dual-site cases