Scott Moura

Probe Sets for Nonlinear Kalman Filtering: Multi-Center Gains and Covariance Recalibration

Kalman filters (KFs) choose the gain as the product of the state--measurement cross-covariance and the inverse of the innovation covariance. In nonlinear systems, the predictive distribution generally changes shape, and these covariances require approximation. Conventional nonlinear KFs approximate them around a single...