Nonlinear Filtering Using an Adaptive Observer Approach

This correspondence describes a method for nonlinear filtering based on an adaptive observer, which guarantees the local stability of the linearised error system. Filter gain selection is by use of a fake algebraic Riccati equation. The design procedure attempts to produce a stable filter at the expense of optimality. This contrasts with the extended Kalman filter (EKF) which attempts to preserve optimality via its linearisation procedure, at the expense of optimality. A passivity approach is applied to deduce stability conditions for the filter error system. The performance is compared with an EKF for tracking frequency modulated signals. Correspondence to: Dr G. A. Einicke, CSIRO, Division of Exploration and Mining PO Box 883 Kenmore, QLD 4069, Australia [email protected] Ph +61 7 3327 4615, fax +61 7 3327 4455 Page 2 Einicke, White and Bitmead