Aerospace Engineering Commons^™

Information-Based Methods And Models For Particle Flow Filtering, Kari Catherine Ward

Doctoral Dissertations

"Recursive estimation methodologies, such as Kalman and Bayesian filters, typically require models of some kind to perform the estimation. This filtering process seeks to improve knowledge surrounding some quantities of interest, or states, over time by incorporation of imperfect observations. The models required pertain to the state dynamics, sensors from which measurements are obtained, and probabilistic models of the underlying stochastic processes. In addition to any number of necessary models, real-world application of a filter is normally accompanied by at least one, if not several, techniques to promote better performance. These methods vary in purpose from expanding the kinds of …