Enhanced PUMA for Direction-of-Arrival Estimation and Its Performance Analysis

Direction-of-arrival (DOA) estimation is a problem of significance in many applications. In practice, due to the occurrence of coherent signals and/or when the number of available snapshots is small, it is a challenge to find DOAs accurately. This problem is revisited here through a new enhanced principal-singular-vector utilization for modal analysis (EPUMA) DOA estimation approach, which improves the threshold performance by first generating
$(P+K)$
DOA candidates for
$K$
sources where
$P\geq K$
, and then judiciously selecting
$K$
of them. The asymptotic variance of EPUMA is theoretically derived, and numerical results are provided to validate the asymptotic analysis and illustrate the practical merits of EPUMA.