Transform domain adaptive filter in active noise control

Abstract

The main shortcoming of the filtered-X LMS algorithm, which is widely used in a variety of active noise control (ANC) systems, is that its convergence behavior highly depends on the power spectrum or autocorrelation of the filtered reference signal. The more correlated the filtered reference signal is, the slower convergence speed the adaptive filter can achieve. The purpose of this paper is to introduce the transform domain adaptive filter (TDAF) into ANC to solve this problem. For the strongly correlated broadband signal, TDAF can achieve much faster convergence speed than LMS with relative low computational cost. A practical filtered-X DCT-LMS algorithm for ANC is also typically presented in this paper. Our experimental results with an ANC headset system prove the advantage of TDAF in ANC.