The concept of spatial active noise control is to use a number of
loudspeakers to generate anti-noise sound waves, which would
cancel the undesired acoustic noise over a spatial region. The
acoustic noise hazards that exist in a variety of situations
provide many potential applications for spatial ANC. However,
using existing ANC techniques, it is difficult to achieve
satisfying noise reduction for a spatial area, especially using a
practical hardware setup. Therefore, this thesis explores
various aspects of spatial ANC, and seeks to develop algorithms
and techniques to promote the performance and feasibility of
spatial ANC in real-life applications.
We use the spherical harmonic analysis technique as the basis for
our research in this work. This technique provides an accurate
representation of the spatial noise field, and enables in-depth
analysis of the characteristics of the noise field. Incorporating
this technique into the design of spatial ANC systems, we
developed a series of algorithms and methods that optimizes the
spatial ANC systems, towards both improving noise reduction
performance and reducing system complexity.
Several contributions of this work are: (i) design of compact
planar microphone array structures capable of recording 3D
spatial sound fields, so that the noise field can be monitored
with minimum physical intrusion to the quiet zone, (ii)
derivation of a Direct-to-Reverberant Energy Ratio (DRR)
estimation algorithm which can be used for evaluating reverberant
characteristics of a noisy environment, (iii) propose a few
methods to estimate and optimize spatial noise reduction of an
ANC system, including a new metric for measuring spatial noise
energy level, and (iv) design of an adaptive spatial ANC
algorithm incorporating the spherical harmonic analysis
technique. The combination of these contributions enables the
design of compact, high performing spatial ANC systems for
various applications
