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Errors-In-Variables Filtering in Behavioural and State-Space Contexts

In: Total Least Squares and Errors-in-Variables Modeling

Author

Listed:
  • Roberto Guidorzi

    (Università di Bologna, Dipartimento di Elettronica, Informatica e Sistemistica)

  • Roberto Diversi

    (Università di Bologna, Dipartimento di Elettronica, Informatica e Sistemistica)

  • Umberto Soverini

    (Università di Bologna, Dipartimento di Elettronica, Informatica e Sistemistica)

Abstract

This paper considers the problem of filtering data sequences generated by errors-in-variables processes where all measured signals, differently from the classical Kalman filtering context, are affected by additive noise. The design of optimal (minimal variance) filters leading to estimates of the process inputs and outputs is first carried out in a behavioural context. The state-space context where EIV filtering can be performed relying on modified Kalman filtering techniques is then considered and a Monte Carlo simulation is finally proposed.

Suggested Citation

  • Roberto Guidorzi & Roberto Diversi & Umberto Soverini, 2002. "Errors-In-Variables Filtering in Behavioural and State-Space Contexts," Springer Books, in: Sabine Van Huffel & Philippe Lemmerling (ed.), Total Least Squares and Errors-in-Variables Modeling, pages 281-291, Springer.
    • Handle: RePEc:spr:sprchp:978-94-017-3552-0_25
    DOI: 10.1007/978-94-017-3552-0_25
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