Probe Sets for Nonlinear Kalman Filtering: Multi-Center Gains and Covariance Recalibration
The paper introduces probe sets to improve gain selection and covariance recalibration in nonlinear Kalman filters. Instead of using a single point, it uses small collections of states where the filter repeats its local approximation to select a better gain. This probing substantially reduces covariance inconsistency and rare large-error trajectories while preserving typical accuracy.