Single Stage DOA-Frequency Representation of the Array Data with Source Reconstruction Capability

TL;DR

This paper introduces a novel single-stage DOA-frequency representation framework for array data that enables source reconstruction and improves wideband DOA estimation, especially in low SNR conditions.

Contribution

The paper proposes a reversible DOA-frequency domain representation using a new G dictionary, facilitating source reconstruction and wideband DOA estimation with improved accuracy.

Findings

Sparse solvers outperform noncoherent methods in multitone scenarios.

The proposed method outperforms existing wideband DOA estimators at low SNR.

Source recovery is significantly improved over traditional beamforming techniques.

Abstract

In this paper, a new signal processing framework is proposed, in which the array time samples are represented in DOA-frequency domain through a single stage problem. It is shown that concatenated array data is well represented in a $\mathbf{G}$ dictionary atoms space, where $\mathbf{G}$ columns correspond to pixels in the DOA-frequency image. We present two approaches for the $\mathbf{G}$ formation and compare the benefits and disadvantages of them. A mutual coherence guaranteed $\mathbf{G}$ manipulation technique is also proposed. Furthermore, unlike most of the existing methods, the proposed problem is reversible into the time domain, therefore, source recovery from the resulted DOA-frequency image is possible. The proposed representation in DOA-frequency domain can be simply transformed into a group sparse problem, in the case of non-multitone sources in a given bandwidth. Therefore, it can also be utilized as an effective wideband DOA estimator. In the simulation part, two scenarios of multitone sources with unknown frequency and DOA locations and non-multitone wideband sources with assumed frequency region are examined. In multitone scenario, sparse solvers yield more accurate DOA-frequency representation compared to some noncoherent approaches. At the latter scenario, the proposed method with group sparse solver outperforms some existing wideband DOA estimators in low SNR regime. In addition, sources' recovery simultaneous with DOA estimation shows significant improvement compared to the conventional delay and sum beamformer and without prerequisites required in sophisticated wideband beamformers.