1 research outputs found
Inferring Room Geometries
Determining the geometry of an acoustic enclosure using microphone arrays
has become an active area of research. Knowledge gained about the acoustic
environment, such as the location of reflectors, can be advantageous for
applications such as sound source localization, dereverberation and adaptive
echo cancellation by assisting in tracking environment changes and helping
the initialization of such algorithms.
A methodology to blindly infer the geometry of an acoustic enclosure by estimating
the location of reflective surfaces based on acoustic measurements
using an arbitrary array geometry is developed and analyzed. The starting
point of this work considers a geometric constraint, valid both in two
and three-dimensions, that converts time-of-arrival and time-difference-pf-arrival information into elliptical constraints about the location of reflectors.
Multiple constraints are combined to yield the line or plane parameters of
the reflectors by minimizing a specific cost function in the least-squares
sense. An iterative constrained least-squares estimator, along with a closed-form estimator, that performs optimally in a noise-free scenario, solve the
associated common tangent estimation problem that arises from the geometric
constraint. Additionally, a Hough transform based data fusion and
estimation technique, that considers acquisitions from multiple source positions,
refines the reflector localization even in adverse conditions.
An extension to the geometric inference framework, that includes the estimation
of the actual speed of sound to improve the accuracy under temperature
variations, is presented that also reduces the required prior information
needed such that only relative microphone positions in the array are
required for the localization of acoustic reflectors. Simulated and real-world
experiments demonstrate the feasibility of the proposed method.Open Acces