LU Caixia, YANG Feiran, YANG Jun. An Adaptive Time-Domain Kalman Filtering Approach to Acoustic Feedback Cancellation for Hearing Aids[J]. Chinese Journal of Electronics, 2020, 29(1): 139-146. doi: 10.1049/cje.2019.11.003
Citation: LU Caixia, YANG Feiran, YANG Jun. An Adaptive Time-Domain Kalman Filtering Approach to Acoustic Feedback Cancellation for Hearing Aids[J]. Chinese Journal of Electronics, 2020, 29(1): 139-146. doi: 10.1049/cje.2019.11.003

An Adaptive Time-Domain Kalman Filtering Approach to Acoustic Feedback Cancellation for Hearing Aids

doi: 10.1049/cje.2019.11.003
Funds:  This work is supported by the National Natural Science Foundation of China (No.61501449, No.11674348), Youth Innovation Promotion Association of Chinese Academy of Sciences (No.2018027), IACAS Young Elite Researcher Project (No.QNYC201812), the Strategic Priority Research Program of Chinese Academy of Sciences (No.XDC02020400), and the National Key R&D Program of China (No.2017YFC0804900).
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  • Corresponding author: YANG Jun (corresponding author) received the B. E. and M. E. degrees from Harbin Engineering University, Harbin, China, and the Ph.D. degree in acoustics from Nanjing University, Nanjing, China, in 1990, 1993, and 1996, respectively. From 1996 to 1998, he was a Postdoctoral Fellow at the Institute of Acoustics, Chinese Academy of Sciences (IACAS), Beijing, China. From October 1998 to April 1999, he was with Hong Kong Polytechnic University as a Visiting Scholar. From Jan. 1997 to May 1999, he was with IACAS as an Associate Professor. He joined the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, as a Research Fellow, a Teaching Fellow, Assistant Professor, and Associate Professor in 1999, 2001, 2003, and 2005, respectively. Since Nov. 2003, he has been a Professor at IACAS. Currently, he is the Director of the Key Laboratory of Noise and Vibration Research, Institute of Acoustics, Chinese Academy of Sciences. His main areas of research interests include communication acoustics, 3-D audio systems, acoustic signal processing, sound field control, and nonlinear acoustics. He serves as the Editor-in-Chief of Sound and Vibration. He is a Fellow of the International Institute of Acoustics and Vibration (IIAV). (Email:jyang@mail.ioa.ac.cn)
  • Received Date: 2018-09-03
  • Rev Recd Date: 2019-04-13
  • Publish Date: 2020-01-10
  • The adaptive filtering approach has been widely used for acoustic feedback control in the hearing aids due to its excellent performance. The commonly used adaptive filtering algorithms employ a fixed step-size, which has to compromise between the initial convergence and the steady-state misalignment. Many variable stepsize adaptive algorithms have been proposed to handle this problem. In this paper, we propose a broadband Kalman filter to resolve this problem. The acoustic feedback path is modelled by a first-order Markov model, and the observation equation is constructed using more past data vector. A major issue in the hearing aids is the computational complexity. We thus present a simplified version to reduce the complexity, which bridges between the exact Kalman filter and the affine projection algorithm. The estimation of the process and measurement noise variance is discussed in detail. A two-feedbackpath model is adopted to improve the algorithm's lack of re-convergence. Simulation results confirm the proposed algorithm clearly outperforms the other variable step-size adaptive filtering approaches.
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