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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 languageEnglish (US)
Pages (from-to)1-45
Number of pages45
JournalControl and Dynamic Systems: Advances in Theory and Application
StatePublished - Jan 1 1983
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Information Systems

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