  Distributed systems serve as a key technological infrastructure for
monitoring diverse systems across space and time. Examples of their widespread
applications include: precision agriculture, surveillance, ecosystem and
physical infrastructure monitoring, animal behavior and tracking, disaster
response and recovery to name a few. Such systems comprise of a large number of
sensor devices at fixed locations, wherein each individual sensor obtains
measurements that are subsequently fused and processed at a central processing
node. A key problem for such systems is to detect targets and identify their
locations, for which a large body of literature has been developed focusing
primarily on employing parametric models for signal attenuation from target to
device. In this paper, we adopt a nonparametric approach that only assumes that
the signal is nonincreasing as function of the distance between the sensor and
the target. We propose a simple tuning parameter free estimator for the target
location, namely, the simple score estimator (SSCE). We show that the SSCE is
$\sqrt{n}$ consistent and has a Gaussian limit distribution which can be used
to construct asymptotic confidence regions for the location of the target. We
study the performance of the SSCE through extensive simulations, and finally
demonstrate an application to target detection in a video surveillance data
set.
