The advantages of the bias-separated filter implementation as compared with Kalman filtering are pointed out. A method of derivation of the bias-separated filter structure, based on the theory of linear observers, is presented. Some alternative derivations are also described. The extension from a constant to a time-varying bias, to nonlinear systems, and to noise on bias is discussed. Problems of fixed interval smoothing and failure detection and estimation are considered. Additional applications to trajectory estimation, added-inertial navigation, calibration, satellite-attitude estimation, and process control are illustrated. Some areas requiring further investigation are pointed out.
|Number of pages
|Control and Dynamic Systems: Advances in Theory and Application
|Published - 1983
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Information Systems