Joint DOA and multi-pitch estimation via block sparse dictionary learning

In this paper, we introduce a novel sparse method for joint estimation of the direction of arrivals (DOAs) and pitches of a set of multi-pitch signals impinging on a sensor array. Extending on earlier approaches, we formulate a novel dictionary learning framework from which an estimate is formed without making assumptions on the model orders. The proposed method alternatively uses a block sparse approach to estimate the pitches, using an alternating direction method of multipliers framework, and alternatively a nonlinear least squares approach to estimate the DOAs. The preferable performance of the proposed algorithm, as compared to earlier methods, is shown using numerical examples.