  We present a detection problem where several spatially distributed sensors
observe Poisson signals emitted from a single source of unknown position. The
measurements at each sensor are modeled by independent inhomogeneous Poisson
processes. A method based on Bayesian change-point estimation is proposed to
identify the location of the source's coordinates. The asymptotic behavior of
the Bayesian estimator is studied. In particular the consistency and the
asymptotic efficiency of the estimator are shown. The limit distribution and
the convergence of the moments are also described. The similar statistical
model could be used in GPS localization problems.
