PROJECT TITLE :

Distributed Information Fusion in Multistatic Sensor Networks for Underwater Surveillance

ABSTRACT:

Surveillance in antisubmarine warfare has historically been dispensed by means of submarines or frigates with towed arrays. These techniques are manpower intensive. Different approaches have recently been suggested using distributed stationary and mobile sensors, like autonomous underwater vehicles (AUVs). In distinction with the employment of customary assets, these little, low-power, and mobile devices have limited processing and wireless communication capabilities. However, when deployed during a spatially separated network, these sensors will form an intelligent network achieving high performance with important options of scalability, robustness, and reliability. The distributed information FUSION (DIFFUSION) strategy, in that the local info is shared among sensors, is one amongst the key aspects of this intelligent network. During this paper, we have a tendency to propose 2 DIFFUSION schemes, in which the data shared among sensors consists of: 1) contacts, generated by the local detection stage and a pair of) tracks, generated by the local tracking stage. In the primary DIFFUSION scheme, contacts are combined at each nodes using the optimal Bayesian tracking based mostly on the random finite set formulation. In the second DIFFUSION theme, tracks are combined using the track-to-track association/fusion procedure, then a sequential call primarily based on the association events is exploited. A full validation of the DIFFUSION schemes is conducted by the NATO Science and Technology Organization—Center for maritime analysis and experimentation during the ocean trials Exercise Proud Manta 2012–2013 using real data. Performance metrics of DIFFUSION and of native tracking/detection strategies are also evaluated in terms of time-on-target (ToT) and false alarm rate (FAR). We tend to demonstrate the good thing about using DIFFUSION against the local noncooperative ways. In explicit DIFFUSION improves the extent of TOT (FAR) with respect to the native tracking/detection strategies. In specific, the TOT - s increased over 90%–95% while the WAY is reduced of two order of magnitude. The matter of communication failures, data not offered from the collaborative AUV throughout sure periods of time, is additionally investigated. The robustness of DIFFUSION with respect to these communication failures is demonstrated, and the connected performance results are reported here. In specific, with 75% of communication failures the ToT is over ninety%–ninety five% with a comparatively little increase of the WAY with respect to the case of excellent communication.