Reduced-Complexity Super-Resolution DOA Estimation with Unknown Number of Sources

Abstract

When the number of sources is inaccurately estimated, it is well-known that the conventional subspace-based super-resolution direction-of-arrival (DOA) estimation techniques provide inconsistent spatial spectrum, and hence the DOA estimates. In this work, we present a novel technique which provides resolution capability comparable with that of the super-resolution techniques. While the working principle of the proposed technique is similar to that of the minimum-norm algorithm, the algorithm is insensitive to the estimated model-order. Simulation studies show that the proposed technique is advantageous over the use of subspace-based techniques with the number of sources estimated by well-known model order estimation techniques.