Naval Postgraduate School
Robustifying the Kalman filter
robustifyingkalm00gave.pdf (1.072Mb)Abstract
Kalman filters are tracking and prediction algorithms based on Gaussian measurement errors and structural models. The Kalman filter performance may degrade if the measurement errors come from a thicker-tailed-than Gaussian distribution. In this report non-linear procedures are described which are based on Kalman-type models, but work with student-t measurement errors. Keywords: Kalman filter; Student-t measurement errors; Iterative reweighting procedure; Nonlinear filter; Biweight; Robust estimation
NPS Report Number
NPS55-87-014Related items
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