We consider the problem of estimating the directions of arrival (DOA) of mu
ltiple sources in the presence of local scattering. This problem is encount
ered in wireless communications due to the presence of scatterers in the vi
cinity of the mobile or when the signals propagate through a random inhomog
eneous medium. Assuming a uniform linear array (ULA), we develop DOA estima
tion algorithms based on covariance matching applied to a reduced-size stat
istic obtained from the sample covariance matrix after redundancy averaging
. Next, a computationally efficient estimator based on AR modelling of the
coherence loss function is derived. A theoretical expression for the asympt
otic covariance matrix of this estimator is derived. Finally, the correspon
ding Cramer-Rao bounds (CRBs) are derived. Despite its simplicity, the AR-b
ased estimator is shown to possess performance that is nearly as good as th
at of the covariance matching method.