Target localization in acoustic sensor networks using factor graphs

We consider the problem of localizing targets which act as acoustic sources over a region covered by a sensor network in which each node is equipped with an acoustic intensity sensor. The a posteriori distribution of each target location is constructed through a message passing algorithm on the factor graph representation of the joint posterior which is based on the loopy sum product algorithm. After constructing the posteriors, it is possible to compute the MAP or MMSE estimation expressions of the target locations under these distributions. This approach is the application of an information architecture for distributed inference proposed before. Therefore it is naturally amenable to a distributed implementation and depending on functions which can be easily generated, it has the advantage of compliance with the requirements of sensor networks.