A robust adaptive blind multichannel identification algorithm for acoustic applications

We propose a robust adaptive blind multichannel identification algorithm in the frequency domain. It utilizes the fast Fourier transform (FFT) to reduce computational complexity when the channel impulse response (IR) is long. Moreover, the Newton-LMS algorithm is obtained in the frequency domain with small computational load to improve the convergence speed. The advantage of the proposed method is its robustness to input noise, especially when the channel IR is long, e.g., the room acoustic IR with a length up to hundreds or thousands taps. The conventional methods cannot obtain an estimate with acceptable accuracy and low computational load. The situation becomes worse when the input signal-to-noise ratio (SNR) is low. Simulation results show that the proposed method is suitable for estimating long multichannel IRs in practical environments.