  This paper addresses the problem of localizing an unknown number of targets,
all having the same radar signature, by a distributed MIMO radar consisting of
single antenna transmitters and receivers that cannot determine directions of
departure and arrival. Furthermore, we consider the presence of multipath
propagation, and the possible (correlated) blocking of the direct paths (going
from the transmitter and reflecting off a target to the receiver). In its most
general form, this problem can be cast as a Bayesian estimation problem where
every multipath component is accounted for. However, when the environment map
is unknown, this problem is ill-posed and hence, a tractable approximation is
derived where only direct paths are accounted for. In particular, we take into
account the correlated blocking by scatterers in the environment which appears
as a prior term in the Bayesian estimation framework. A sub-optimal
polynomial-time algorithm to solve the Bayesian multi-target localization
problem with correlated blocking is proposed and its performance is evaluated
using simulations. We found that when correlated blocking is severe, assuming
the blocking events to be independent and having constant probability (as was
done in previous papers) resulted in poor detection performance, with false
alarms more likely to occur than detections.
