Real-time collaborative tracking for underwater networked systems

• Authors: Diba Mirza;Curt Schurgers;Ryan Kastner
• Venue: Proceedings of the Seventh ACM International Conference on Underwater Networks and Systems
• Year: 2012

Localization is a crucial requirement for mobile underwater systems. Real-time position information is needed for control and navigation of underwater vehicles, in early warning systems and for certain routing protocols. Past research has shown that the localization accuracy of networked underwater systems can be significantly improved using collaborative tracking techniques. More specifically the Maximum Likelihood (ML) position estimates of a mobile collective can be computed from measurements of relative positions and motion, albeit centrally and non-real time. While for a number of underwater applications non-real-time position estimates may suffice, in this paper we focus on the design of a collaborative tracking solution that operates in real-time, yet is scalable and energy-efficient. Using the ML solution as a baseline, we identify key factors that fundamentally limit the performance of real-time (centralized and distributed) solutions, quantifying their effects via simulations. In the remaining solution space, we propose a low overhead scheme for real-time and distributed tracking. The specific challenges that we address include determining what information should be shared between vehicles, how this information must be encoded to minimize the communication overhead and when should vehicles communicate with each other to achieve the best performance with the minimum energy consumption. Our proposed technique can strategically trade off localization accuracy and energy consumption, achieving more than 50% reduction in the communication overhead compared to any fixed scheme.