ABSTRACT
The acoustic imaging problem consists of mapping the directions and intensities of sound sources using a microphone array. These maps are used, e.g., to design airplanes, cars, and trains that are quieter and more aerodynamically efficient, and also to analyze structures such as concert halls and turbines. In this chapter we describe ways to accelerate the computation of acoustic images, in particular the Kronecker array transform (KAT). We start by giving a short description of the problem of acoustic imaging, and the main state-of-the-art methods for solving it, from the standard beamforming method, through more accurate solutions such as DAMAS and covariance-fitting. We proceed by describing the KAT and how it can be applied to accelerate these methods, or to make possible the application of even more powerful methods, such as recent sparse estimation techniques, which without the KAT would be too computer intensive to be used in acoustic imaging.
