• DocumentCode
    1211057
  • Title

    Sequential tuning of microwave filters using adaptive models and parameter extraction

  • Author

    Pepe, Giuseppe ; Görtz, Franz-Josef ; Chaloupka, Heinz

  • Author_Institution
    Tesat-Spacecom GmbH & Co. KG, Backnang, Germany
  • Volume
    53
  • Issue
    1
  • fYear
    2005
  • Firstpage
    22
  • Lastpage
    31
  • Abstract
    This paper describes a sequential procedure for computer-aided tuning and diagnosis of multiple-coupled resonator filters. The method is based on a sequential parameter estimation and a systematic tuning procedure and employs three different filter models. A detuned model represents the initial status of the filter after a well-defined detuning procedure. The target filter is described by an ideal model, whereas the actual state of the filter at each tuning step is represented by a coarse adaptive model. The goal of the procedure is the convergence of the coarse model to the ideal model and will be obtained by systematically centering resonant frequencies and coupling coefficients. Practical examples comprising low- and high-degree filters confirm the effectiveness of the proposed approach in both tuning and fault diagnosis.
  • Keywords
    adaptive filters; circuit analysis computing; circuit tuning; fault diagnosis; microwave filters; parameter estimation; resonator filters; adaptive models; computer aided diagnosis; computer aided tuning; convergence; coupling coefficients; fault diagnosis; microwave filters; multiple coupled resonator filters; parameter extraction; resonant frequencies; sequential parameter estimation; sequential tuning; Adaptive filters; Circuit faults; Fault diagnosis; Frequency response; Manufacturing; Microwave filters; Parameter estimation; Parameter extraction; Resonator filters; Tuning;
  • fLanguage
    English
  • Journal_Title
    Microwave Theory and Techniques, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9480
  • Type

    jour

  • DOI
    10.1109/TMTT.2004.839342
  • Filename
    1381672