State estimation under non-Gaussian Lévy noise: A modified Kalman filtering method
Volume 105 / 2015
Banach Center Publications 105 (2015), 239-246
MSC: Primary 93E11; Secondary 60G35.
DOI: 10.4064/bc105-0-14
Abstract
The Kalman filter is extensively used for state estimation for linear systems under Gaussian noise. When non-Gaussian Lévy noise is present, the conventional Kalman filter may fail to be effective due to the fact that the non-Gaussian Lévy noise may have infinite variance. A modified Kalman filter for linear systems with non-Gaussian Lévy noise is devised. It works effectively with reasonable computational cost. Simulation results are presented to illustrate this non-Gaussian filtering method.
