  In localization applications, the line-of-sight between anchors and targets
may be blocked by obstacles in the environment. A target that is invisible
(i.e., without line-of-sight) to a sufficient number of anchors cannot be
unambiguously localized and is, therefore, said to be in a blind spot. In this
paper, we analyze the blind spot probability of a typical target by using
stochastic geometry to model the randomness in the obstacle and anchor
locations. In doing so, we handle correlated anchor blocking induced by the
obstacles, unlike previous works that assume independent anchor blocking. We
first characterize the regime over which the independent blocking assumption
underestimates the blind spot probability of the typical target, which in turn,
is characterized as a function of the distribution of the visible area,
surrounding the target location. Since this distribution is difficult to
characterize exactly, we formulate the nearest two-obstacle approximation,
which is equivalent to considering correlated blocking for only the nearest two
obstacles from the target and assuming independent blocking for the remaining
obstacles. Based on this, we derive an approximate expression for the blind
spot probability, which helps determine the anchor deployment intensity needed
for the blind spot probability of a typical target to be at most a threshold,
$\mu$.
