Bayesian Estimation For Tracking Of Spiraling Reentry Vehicles

Download or read book Bayesian Estimation For Tracking Of Spiraling Reentry Vehicles written by Juan Esteban Tapiero Bernal and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis presents a development of a physics-based dynamics model of a spiraling atmospheric reentry vehicle. An analysis of the trajectory characteristics, using elements from differential geometry lead to a relationship of the state of the vehicle to the spiraling of motion. The Bayesian estimation framework for nonlinear systems is introduced showing the theoretical basis of the estimation techniques. Two estimation algorithms, extended Kalman filter and particle filter are presented, their mathematical formulation and implementation characteristics. Different trajectories that can be represented by the model are introduced and analyzed, showing the spiraling behavior that can be described by the model. The extended Kalman filter and particle filter are compared in the ability to estimate the states and spiraling characteristics, with successful results for both techniques inside one standard deviation. In general superior performance was shown by the particle filter, which estimated the torsion with an error 10 orders of magnitude smaller.