TY - GEN
T1 - Mode Domain Spatial Active Noise Control Using Sparse Signal Representation
AU - Maeno, Yu
AU - Mitsufuji, Yuki
AU - Abhayapala, Thushara D.
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/9/10
Y1 - 2018/9/10
N2 - Active noise control (ANC) over a sizeable space requires a large number of reference and error microphones to satisfy the spatial Nyquist sampling criterion, which limits the feasibility of practical realization of such systems. This paper proposes a mode-domain feedforward ANC method to attenuate the noise field over a large space while reducing the number of microphones required. We adopt a sparse reference signal representation to precisely calculate the reference mode coefficients. The proposed system consists of circular reference and error microphone arrays, which capture the reference noise signal and residual error signal, respectively, and a circular loudspeaker array to drive the anti-noise signal. Experimental results indicate that above the spatial Nyquist frequency, our proposed method can perform well compared to a conventional methods. Moreover, the proposed method can even reduce the number of reference microphones while achieving better noise attenuation.
AB - Active noise control (ANC) over a sizeable space requires a large number of reference and error microphones to satisfy the spatial Nyquist sampling criterion, which limits the feasibility of practical realization of such systems. This paper proposes a mode-domain feedforward ANC method to attenuate the noise field over a large space while reducing the number of microphones required. We adopt a sparse reference signal representation to precisely calculate the reference mode coefficients. The proposed system consists of circular reference and error microphone arrays, which capture the reference noise signal and residual error signal, respectively, and a circular loudspeaker array to drive the anti-noise signal. Experimental results indicate that above the spatial Nyquist frequency, our proposed method can perform well compared to a conventional methods. Moreover, the proposed method can even reduce the number of reference microphones while achieving better noise attenuation.
KW - Active noise control
KW - Adaptive algorithm
KW - Compressive sensing
KW - Mode-domain signal processing
KW - Sparse signal representation
UR - http://www.scopus.com/inward/record.url?scp=85054249205&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2018.8461482
DO - 10.1109/ICASSP.2018.8461482
M3 - Conference contribution
SN - 9781538646588
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 211
EP - 215
BT - 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018
Y2 - 15 April 2018 through 20 April 2018
ER -