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access icon free Multiband-structured Kalman filter

  • Author(s): Feiran Yang 1  and  Jun Yang 1, 2
    • View affiliations
  • Source: Volume 12, Issue 6, August 2018, p. 722 – 728
    DOI:  10.1049/iet-spr.2017.0313 , Print ISSN 1751-9675, Online ISSN 1751-9683
© The Institution of Engineering and Technology
Received 24/06/2017, Accepted 22/02/2018, Revised 27/01/2018, Published 23/02/2018

The broadband Kalman filter (BKF) and general Kalman filter (GKF) have been proposed for the application of acoustic system identification. Here, the authors present a multiband-structured Kalman filter (MSKF) to speed up the convergence rate of BKF and GKF for highly correlated signal. A simplified version of MSKF (SMSKF) is also provided at the aim of reducing the complexity. It is shown that the BKF and GKF are the special cases of the proposed MSKF, and the SMSKF can be treated as the improved multiband-structured subband adaptive filter algorithm with a variable regularisation matrix. The low-complexity implementation of SMSKF, both in the fast filtering and matrix inversion operation, is discussed. Computer simulations confirm the performance advantage of the proposed algorithm.

Inspec keywords: matrix inversion; computational complexity; adaptive Kalman filters

Other keywords: BKF; multiband-structured subband adaptive filter algorithm; acoustic system identification; variable regularisation matrix; simplified multiband-structured Kalman filter; matrix inversion operation; GKF; general Kalman filter; broadband Kalman filter; SMSKF

Subjects: Algebra; Computational complexity; Signal processing theory; Filtering methods in signal processing; Algebra

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