A Novel Method for DOA Estimation Based on Generalized-Prior Distribution
Shu Zhang, Yumei Li, Juncai Song · 2010
This paper presents a method of sparse signal decomposition that is based on generalized Cauchy-prior distribution and generalized t-prior distribution instead of the Laplace-prior and Cauchy-prior distribution. These generalized distributions have strong characteristic of super-Gaussian. It takes full advantage of the sparse property of spatial spectrum to estimate the direction of arrival (DOA) of narrowband sources impinging on an uniform circular array. It has a number of advantages over other source localization techniques, including increased resolution, and improved robustness to noise, to a limited number of snapshots and to correlation of the sources. Moreover, there is no spectral peak searching, so it reduces the system complexity.