Abstract:

Computationally efficient methods for super-resolution direction of arrival (DOA) estimation aim to reduce the complexity of conventional techniques, to economize on the costs of systems and to enhance the robustness of DOA estimators against array geometries and other environmental restrictions, which has been an important topic in the field. According to the theory and elements of the multiple signal classification (MUSIC) algorithm and the primary derivations from MUSIC, state-of-the art efficient super-resolution DOA estimators are classified into five different types. These five types of approaches reduce the complexity by realvalued computation, beamspace transformation, fast subspace estimation, rapid spectral search, and no spectral search, respectively. With such a classification, comprehensive overviews of each kind of efficient methods are given and numerical comparisons among these estimators are also conducted to illustrate their advantages. Future development trends of efficient algorithms for super-resolution DOA estimates are finally predicted with basic requirements of realworld applications.