A novel 2-D pair-matching algorithm using the special relation between the transition matrices and the autocorrelation matrix of the signals
Xi Nie, Liping Li · 2013
In this paper, a novel pair-matching algorithm is developed for two-dimensional (2-D) direction-of-arrival (DOA) estimation. In the proposed algorithm, firstly we take the singular value decomposition (SVD) of the cross-correlation matrix of two uniform linear arrays (ULAs). Next we extract the square root of the singular values. Lastly we multiply the left singular vectors and right singular vectors by the square root of the corresponding singular values respectively and obtain the new singular vectors which are called the modified singular vectors. After this processing, there exists a special relation between the transition matrices from the modified singular vectors to the steering vectors and the autocorrelation matrix of the signals. Exploiting this relation, the pair-matching procedure of the azimuth and elevation angles is carried out effectively. The simulation results are presented to validate the effectiveness of the proposed algorithm.