Experimental evaluation of leaky LMS algorithms for active noise reduction in communication headsets

• Published in: The Journal of the Acoustical Society of America 2000-11, Vol.108 (5_Supplement), p.2483-2484
• Main Authors: Cartes, David A., Ray, Laura R., Collier, Robert D.
• Format: Article
• Language: English
• ISSN: 0001-4966; 1520-8524
• DOI: 10.1121/1.4743166

An adaptive leaky LMS algorithm has been developed to optimize stability and performance of active noise cancellation systems. The research addresses performance issues related to insufficient excitation, nonstationary noise fields, and signal-to-noise ratio. The algorithm is based on a Lyapunov tuning approach in which three candidate algorithms, each of which is a function of the instantaneous measured reference input, measurement noise variance, and filter length, provide varying degrees of trade-off between stability and performance. Each algorithm is evaluated experimentally for reduction of low-frequency noise in communication headsets and compared with that of traditional LMS algorithms. Acoustic measurements are made in a specially designed acoustic test cell which is based on the original work of Shaw, Brammer and co-workers and which provides a highly controlled and uniform acoustic environment. The stability and performance of the ANR system, including prototype communication headsets, are investigated for a variety of noise sources ranging from stationary white noise to highly nonstationary measured F-16 aircraft noise over a 20-dB dynamic range. Results demonstrate significant improvements in stability of Lyapunov-tuned LMS algorithms over traditional leaky or nonleaky normalized algorithms while providing noise reduction performance equivalent to that of the NLMS algorithm for idealized noise fields.