Open AccessMultiband‐structured Kalman filter
Author(s) -
Yang Feiran,
Yang Jun
Publication year - 2018
Publication title -
iet signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.384
H-Index - 42
eISSN - 1751-9683
pISSN - 1751-9675
DOI - 10.1049/iet-spr.2017.0313
Subject(s) - kalman filter , computer science , invariant extended kalman filter , fast kalman filter , inversion (geology) , adaptive filter , recursive least squares filter , alpha beta filter , extended kalman filter , rate of convergence , algorithm , control theory (sociology) , filter (signal processing) , moving horizon estimation , telecommunications , artificial intelligence , computer vision , paleontology , channel (broadcasting) , control (management) , structural basin , biology
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.