Abstract
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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1-45 |
| Number of pages | 45 |
| Journal | Control and Dynamic Systems: Advances in Theory and Application |
| Volume | 20 |
| State | Published - 1983 |
| Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Information Systems