An approach to robust Kalman filtering

Abstract

We consider the problem of robustifying the Kalman filter. First, we review some known approaches to the problem. Then we establish the equivalence between the Kalman filter and a particular least squares regression problem. We suggest that the regression problem be solved robustly. Some well known approaches for doing this are discussed. Finally, the possibility of gleaning more information from past data is discussed.