A simplified method for online acoustic feedback path modeling and neutralization in multichannel active noise control systems

  • Authors:

  • Muhammad Tahir Akhtar;Masahide Abe;Masayuki Kawamata;Wataru Mitsuhashi

  • Affiliations:

  • The Education and Research Center (ERC) for Frontier Science and Engineering, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu, 182-8585 Tokyo, Japan;Graduate School of Engineering, Tohoku University, 6-6-05, Aoba, Aramaki, Aoba-ku, Sendai 980-8579, Japan;Graduate School of Engineering, Tohoku University, 6-6-05, Aoba, Aramaki, Aoba-ku, Sendai 980-8579, Japan;Department of Information and Communication Engineering, The University of Electro-Communications, 1-5-1 Chofugaoka, Chofu, 182-8585 Tokyo, Japan

  • Venue:
  • Signal Processing
  • Year:
  • 2009

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Abstract

The presence of strong acoustic feedback degrades the performance of active noise control (ANC) systems, and in the worst case the ANC system may become unstable. In this paper, we investigate additive-random-noise-based methods for online feedback path modeling and neutralization (FBPMN) in multichannel ANC systems. In existing methods, separate filters are used for each acoustic feedback path: one for online feedback path modeling (FBPM), and another for feedback path neutralization (FBPN). Furthermore, the existing method works well for predictable noise sources but its performance degrades for unpredictable sources. This paper attempts to solve these problems in multichannel ANC systems. The proposed method is a modification and extension of previous work for online FBPMN in single-channel ANC systems. In the proposed method, we combine the two tasks of FBPM and FBPN in one online FBPMN filter, and hence, the computational complexity of the proposed method is lower than existing methods. Computer simulations are carried out to demonstrate the effectiveness of the proposed method. It is shown that the proposed method achieves better performance than existing methods for both predictable and unpredictable noise sources. Furthermore, this improved performance is achieved at somewhat reduced computational complexity.