  Sparse signal models are in the focus of recent developments in narrowband
DOA estimation. Applying these methods to localizing audio sources, however, is
challenging due to the wideband nature of the signals. The common approach of
processing all frequency bands separately and fusing the results is costly and
can introduce errors in the solution. We show how these problems can be
overcome by decomposing the wavefield of a circular microphone array and using
circular harmonic coefficients instead of time-frequency data for sparse DOA
estimation. As a result, we present the super-resolution localization method
WASCHL (Wideband Audio Sparse Circular Harmonics Localizer) that is inherently
frequency-coherent and highly efficient from a computational point of view.
