Multi-Vehicle Decentralized Fusion and Tracking

In this paper, we introduce a decentralized fusion and tracking based on a distributed multi-source multitarget filtering and robust communication with the following features: (i) data reduction; (ii) a disruption tolerant dissemination procedure that takes advantage of storage and mobility; and (iii) efficient data set reconciliation algorithms. We developed and implemented complex high-fidelity marine application demonstration of this approach that encompasses all relevant environmental parameters. In the simulated example, multi-source information is fused by exploiting sensors from disparate Unmanned Underwater Vehicles (UUV) and Unmanned Surface Vehicle (USV) multi-sensor platforms. Communications among the platforms are continuously establishing and breaking depending on the time-changing geometry. We compare and evaluate the developed algorithms by assessing their performance against different scenarios.