2D DOA estimation of coherent signals with a separated linear acoustic vector-sensor array

Abstract

In this paper, a two-dimensional (2D) DOA estimation algorithm of coherent signals with a separated linear acoustic vector-sensor (AVS) array consisting of two sparse AVS arrays is proposed. Firstly, the partitioned spatial smoothing (PSS) technique is used to construct a block covariance matrix, so as to decorrelate the coherency of signals. Then a signal subspace can be obtained by singular value decomposition (SVD) of the covariance matrix. Using the signal subspace, two extended signal subspaces are constructed to compensate aperture loss caused by PSS. The elevation angles can be estimated by estimation of signal parameter via rotational invariance techniques (ESPRIT) algorithm. At last, the estimated elevation angles can be used to estimate automatically paired azimuth angles. Compared with some other ESPRIT algorithms, the proposed algorithm shows higher estimation accuracy, which can be proved through the simulation results.