A two-dimensional direction finding estimation with L-shape uniform linear arrays
Han Huilian, Pinjiao Zhao · 2013
In order to decrease two-dimensional DOA computational complexity, a 2-D direction finding method is proposed with L-shape uniform linear arrays when the additive white Gaussian noises exist. A cross-correlation matrix of received signals is first constructed. Afterwards, signal subspace can be acquired by performing eigen-value decomposition of the matrix. The signal subspace is divided into two sub-arrays. Then, a new matrix is reconstructed with the two sub-arrays is mentioned above and eigen-value decomposition theory is applied to it. This approach enables 2D direction-of-arrival (DOA) and needs low computation. In the proposed method, parameters can match automatically without spectral peak searching. Simulation results demonstrate effectiveness and efficiency of the proposed method.