A Modified Denoise Approach for UCA DOA Estimation in Low SNR Case
When the Uniform Circular Array (UCA) is used to estimate the Direction-Of-Arrival (DOA) of the coherent sources, it is necessary to transform the UCA data to the interpolated Uniform Linear Array (ULA) data. Thus, the transformed array data can be applied to the spatial processing algorithm for the coherent sources such as the forward-backward smoothing algorithm. To select a more robust transformation matrix, a modified denoise approach for UCA estimation in low SNR case is proposed in this paper. First, a denoise method is investigated to maximize the SNR in the process of the interpolated transformation. The Pseudo Signal to Noise Ratio (PSNR) obtained from the eigen-values of the forward-backward smoothing virtual covariance matrix estimate is used as the parameter of this maximization problem.