BIMSA >
Seminar on Control Theory and Nonlinear Filtering
Maximum Correntropy Ensemble Kalman Filter
Maximum Correntropy Ensemble Kalman Filter
Organizer
Speaker
Yangtianze Tao
Time
Tuesday, January 10, 2023 9:30 PM - 10:00 PM
Venue
Online
Abstract
In this presentation, a robust ensemble Kalman filter (EnKF) called MC-EnKF is proposed for nonlinear state-space model to deal with filtering problems with non-Gaussian observation noises. Our MC-EnKF is derived based on maximum correntropy criterion (MCC) cost function with some technical approximations. Moreover, we propose an effective adaptive strategy for kernel bandwidth selection.
Besides, the relations between the common EnKF and MC-EnKF are given, i.e., MC-EnKF will converge to the common EnKF when the kernel bandwidth tends to infinity. This justification provides a complementary understanding of the kernel bandwidth selection for MC-EnKF. In experiments, non-Gaussian observation noises significantly reduce the performance of the common EnKF for both linear and nonlinear systems, whereas our proposed MC-EnKF with a suitable kernel bandwidth maintains its good performance at only a marginal increase in computing cost, demonstrating its robustness and efficiency to non-Gaussian observation noises.