  In this paper we use the MAP criterion to locate a region containing a
source. Sensors placed in a field of interest divide the latter into smaller
regions and take measurements that are transmitted over noisy wireless
channels. We propose implementations of our algorithm that consider complete
and limited communication among sensors and seek to choose the most likely
hypothesis. Each hypothesis corresponds to the event that a given region
contains the source. Corrupted measurements are used to calculate conditional
posteriors. We prove that the algorithms asymptotically find the correct region
almost surely as long as information is available from three or more sensors.
We also study the geometric properties of the model that make it possible in
some situations to detect the correct region with a unique sensor. Our
simulations confirm that the performance of algorithms with complete and
limited information ameliorates with decreasing noise.
