Low Complexity DOA Estimation for Massive UCA with Single Snapshot

In this paper, a low complexity direction of arrival (DOA) estimation method for massive uniform circular array (UCA) with single snapshot is proposed. Firstly, the coarse DOAs are estimated by finding the peaks from the circular convolution between a fixed coefficient vector and the received data vector. Thereafter, in order to refine coarse DOA estimates, we reconstruct the direction matrix based on the coarse DOA estimations and take the first order Taylor expansion with DOA estimation offsets into account. Finally, the refined estimations are obtained by compensating the offsets, which are obtained via least squares (LS) without any complex searches. In addition, the refinement can be iteratively implemented to enhance the estimation results. Compared to the offset search method, the proposed method achieves a better estimation performance while requiring lower complexity. Numerical simulations are presented to demonstrate the effectiveness of the proposed method.