default Using Bayesian area search behaviours in autonomous underwater sensor networks for littoral surveillance

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Using Bayesian area search behaviours in autonomous underwater sensor networks for littoral surveillance. Munafò, Andrea; Braca, Paolo; Goldhahn, Ryan A.; Ferri, Gabriele; LePage, Kevin D. CMRE-FR-2015-020. December 2015.

IIn this report a multistatic network of AUVs is considered, where a collaborative multi-sensor tracker is coupled with Bayesian search behaviours to go beyond the individual sensor limitations. The Distributed Information FUSION (DIFFUSION) approach is developed based on a Bayes filter implemented in the form of a particle filter within the Random Finite Set (RFS) formulation. The output of the particle filter tracker, namely the target full posterior, is then used by an area search behaviour which is able to drive the AUVs to put the areas of high probability of detections in locations where the target is most likely located. A full validation of the approach is presented including post-processed data obtained during the Exercise Proud Manta 2012 sea trial, and real-time results from the Littoral Continuous Active Sonar 2015 experiment, the first sea trial where all the components presented were operating in the field.