Direction-of-arrival and power spectral density estimation using a single directional microphone

Abstract

A method is proposed for estimating direction-ofarrival (DOA) and power spectral density (PSD) of stationary point source signals using a single, rotating, directional microphone. By considering different microphone orientations for different time frames, the DOA is estimated by locating the maxima in an estimated PSD vector obtained by solving a groupsparsity constrained optimization problem using a dictionary composed of the known microphone response sampled on an angular grid. The estimated DOAs are then used for obtaining an overdetermined least squares problem with a nonnegativity constraint for re-estimating the PSD of the point source signals.The DOA estimation performance is compared between cases of different frequency-dependent microphone directivity patterns, as well as with the MUSIC algorithm for 6-element uniform linear and circular microphone arrays. The proposed stationary point source PSD estimation using DOA information is compared with traditional single-channel methods for PSD estimation employing minimum statistics and MMSE-based approaches for a rotating microphone setup, one speech source and one stationary interfering point source.

Multi-Source Direction-of-Arrival Estimation using Group-Sparse Fitting of Steered Response Power Maps

“…. , φS,L , such that the source signals' DOAs can be estimated by averaging PSD values over frequency for each subvector φS,l and identifying their peak values over all L candidate directions considered [18]. For a total of J sources, the estimated DOAs θS 1 , .…”

“…Alternatively, in this paper, we propose a method for DOA estimation of multiple sources based on a group-sparse modeling framework. Group-sparse optimization has been previously used in DOA estimation of broadband sources with co-prime arrays [17], as well as with a single directional microphone [18]. Here, it is employed to model a broadband SRP map using direction-dependent power spectral densities (PSDs).…”

The Neural-SRP Method for Universal Robust Multi-source Tracking

“…Other functions more flexible than the peak-picking in (6) can be used for the case of multiple active sources, such as peak subtraction [18] or sparsity-based [19] techniques. Lower computational cost can be achieved through usage of volumetric SRP variations [20], [21].…”

Direction of arrival estimation using the rotating equatorial microphone

“…Given a GMM speech model, a characteristic difference could be observed in the acoustic transfer function as the reflection board was directed at a speech source. A more sophisticated approach was implemented in Tengan et al (2021) and Tengan et al (2023), where a directional microphone was sequentially oriented in multiple directions and DOA estimation was performed by locating the maxima in an estimated power spectral density (PSD) vector. This vector was obtained by solving a group-sparsity constrained optimization problem using a dictionary composed of the known DOA-dependent microphone responses.…”