A robust and computationally efficient method for tonal active noise control using a simplified secondary path model

We present a computationally efficient method for sinusoidal noise cancellation based on the FXLMS algorithm. It features subsampling in order to increase convergence speed and decrease computational requirements, and most importantly, does not require extra noise added to the filter output for secondary path identification. In addition, it is robust to secondary path variations and in low SNR scenarios, which are frequently found in practical active noise control systems, features fast tracking and can be directly generalized to multichannel systems. We illustrate its operation with simulations.

[1]  Dayong Zhou,et al.  A New Active Noise Control Algorithm That Requires No Secondary Path Identification Based on the SPR Property , 2007, IEEE Transactions on Signal Processing.

[2]  Masayuki Kawamata,et al.  A new variable step size LMS algorithm-based method for improved online secondary path modeling in active noise control systems , 2006, IEEE Transactions on Audio, Speech, and Language Processing.

[3]  Hiromitsu Ohmori,et al.  Direct fully adaptive active noise control algorithms without identification of secondary path dynamics , 2002, Proceedings of the International Conference on Control Applications.

[4]  Sen M. Kuo,et al.  Active Noise Control Systems: Algorithms and DSP Implementations , 1996 .

[5]  Barry G. Quinn,et al.  A fast efficient technique for the estimation of frequency , 1991 .

[6]  Hideaki Sakai,et al.  Analysis of the filtered-X LMS algorithm and a related new algorithm for active control of multitonal noise , 2006, IEEE Transactions on Audio, Speech, and Language Processing.

[7]  Ming Zhang,et al.  A robust online secondary path modeling method with auxiliary noise power scheduling strategy and norm constraint manipulation , 2003, IEEE Trans. Speech Audio Process..

[8]  Sen M. Kuo,et al.  A secondary path modeling technique for active noise control systems , 1997, IEEE Trans. Speech Audio Process..

[9]  B. Widrow,et al.  Adaptive noise cancelling: Principles and applications , 1975 .

[10]  Rui Seara,et al.  Mean weight behavior of the Filtered-X LMS algorithm , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

[11]  Yoshinobu Kajikawa,et al.  Active noise control without a secondary path model by using a frequency-domain simultaneous perturbation method with variable perturbation , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

[12]  Ali H. Sayed,et al.  Fundamentals Of Adaptive Filtering , 2003 .

[13]  José Carlos M. Bermudez,et al.  Mean weight behavior of the filtered-X LMS algorithm , 2000, IEEE Trans. Signal Process..