Unambiguous speech DOA estimation under spatial aliasing conditions

With the bandwidth of speech signals extending over several octaves, the spatial Nyquist criterion constrains the microphone array design. Violating this criterion by increasing microphone spacing in order to achieve high resolution introduces ambiguity in identifying the source directions due to the aliasing components. In this work, we investigate the effect of spatial aliasing on the direction-of-arrival (DOA) spectrum due to wideband sources. Noting that the extent of aliasing is frequency dependent, we propose a multi-stage scheme for speech DOA estimation following a subband decomposition. To observe the advantage of this scheme, we verify it with the steered minimum variance distortionless response (STMV) and approximate kernel density estimators. The performance is evaluated with simulations and recorded room impulse responses.