A Robust Algorithm for DOA Estimation of Coherent Sources with UCA

Abstract

Direction of arrival (DOA) estimation of coherent sources with a uniform circular array (UCA) is an intractable problem. The method-of-direction-estimation (MODE) algorithm has strong superiority in handling coherent sources compared with the classical MUSIC, and ESPRIT algorithms. However, MODE is sensitive to source numbers and does not work well in the UCA scenario. In order to improve the performance of MODE, a robust DOA estimation method named UCA-PUMA (principal-eigenvector-utilization-for-modal-analysis) is proposed. The complicated non-Vandermonde structured steering vector of UCA is transformed into a virtual Vandermonde structured steering vector in mode space. The proposed method gives a closed-form solution compared with the original UCA-MODE algorithm. The performance of the UCA-PUMA method is evaluated by simulations. Simulation results demonstrate that the UCA-PUMA is more robust to source numbers than the UCA-MODE, and coherent sources can be handled without spatial smoothing. In addition, the UCA-PUMA fully takes advantage of the UCA, which is able to discriminate sources coming from a 360o azimuthal field of view.