  The problem of direction-of-arrival (DOA) estimation in the presence of
nonuniform sensor noise is considered and a novel algorithm is developed. The
algorithm consists of three phases. First, the diagonal nonuniform sensor noise
covariance matrix is estimated using an iterative procedure that requires only
few iterations to obtain an accurate estimate. The asymptotic variance of one
iteration is derived for the proposed noise covariance estimator. Second, a
forward-only rooting-based DOA estimator as well as its forward-backward
averaging extension are developed for DOA estimation. The DOA estimators take
advantage of using second-order statistics of signal subspace perturbation in
constructing a weight matrix of a properly designed generalized least squares
minimization problem. Despite the fact that these DOA estimators are iterative,
only a few iterations are sufficient to reach accurate results. The asymptotic
performance of these DOA estimators is also investigated. Third, a newly
designed DOA selection strategy with reasonable computational cost is developed
to select L actual sources out of 2L candidates generated at the second phase.
Numerical simulations are conducted in order to establish the considerable
superiority of the proposed algorithm compared to the the existing
state-of-the-art methods in challenging scenarios in both cases of uniform and
nonuniform sensor noise.
