Efficient 2-D DOA estimation for coherent sources with a sparse acoustic vector-sensor array

This paper proposes a computationally efficient two-dimensional (2-D) direction-of-arrival (DOA) estimation algorithm based extended-aperture for acoustic coherent signals impinging on a sparse acoustic vector-sensor array. The coherency of incident signals is decorrelated through matrix averaging and the signal/noise subspaces are reconstructed through a linear operation of a matrix formed from the cross-correlations between some sensor data, where the effect of additive noise is eliminated. Consequently, DOAs can be estimated without performing eigen-decomposition (into signal/noise subspaces), and there is no need to evaluate all correlations of the array data. The derived estimates are automatically matched by translating eigenvalues into real-valued ones, furthermore, the proposed method can achieve the unambiguous direction estimates with enhanced accuracy by setting the vector sensors to space much farther apart than a half-wavelength, and it is also suitable for the case of spatially nonuniform noise, which may be more realistic scenario for the sparsely placed sensors. The performance of the proposed method is demonstrated through numerical examples.