A low complexity 2D-DOA estimation algorithm using signal decomposition

This study proposes an Estimation of Signal Parameter via Rotational Invariance Techniques (ESPRIT) based algorithm for estimating the two-dimensional-direction-of-arrivals (2D-DOA) of signals impinging on a uniform rectangular array (URA). The basic idea of the proposed algorithm is to decompose the URA receive signal into several groups subject to the associated spatial signatures. Two rounds of one-dimensional ESPRIT (1D-ESPRIT) algorithms are conducted to estimate the spatial signature for the signal decomposition. The first round 1D-ESPRIT is applied on columns of the URA whereas the other round 1D-ESPRIT is on the rows of the URA. In between, a grouping technique is developed to generate signal groups each containing signals with distinct spatial signatures. The grouping technique is performed by using a minimum variance distortionless response (MVDR) based spatial filter. Computer simulations show that, in addition to having significantly reduced computational complexity, the proposed algorithm possesses better estimation accuracy as compared to the conventional 2D-ESPRIT algorithm.