Data-aided Underwater Acoustic Ray Propagation Modeling

Acoustic propagation models are widely used in numerous oceanic and other underwater applications. Most conventional models are approximate solutions of the acoustic wave equation, and require accurate environmental knowledge to be available beforehand. Environmental parameters may not always be easily or accurately measurable. While data-driven techniques might allow us to model acoustic propagation without the need for extensive prior environmental knowledge, such techniques tend to be data-hungry and often infeasible in oceanic applications where data collection is difficult and expensive. We propose a data-aided ray physics based high frequency acoustic propagation modeling approach that enables us to train models with only a small amount of data. The proposed framework is not only data-efficient, but also offers flexibility to incorporate varying degrees of environmental knowledge, and generalizes well to permit extrapolation beyond the area where data was collected. We demonstrate the feasibility and applicability of our method through four numerical case studies, and one controlled experiment. We also benchmark our method's performance against classical data-driven techniques.Comment: Accepted version in IEEE Journal of Oceanic Engineerin

Underwater acoustic communications in warm shallow water channels

Ph.DDOCTOR OF PHILOSOPH

Cooperative bathymetry-based localization using low-cost autonomous underwater vehicles

We present a cooperative bathymetry-based localization approach for a team of low-cost autonomous underwater vehicles (AUVs), each equipped only with a single-beam altimeter, a depth sensor and an acoustic modem. The localization of the individual AUV is achieved via fully decentralized particle filtering, with the local filter’s measurement model driven by the AUV’s altimeter measurements and ranging information obtained through inter-vehicle communication. We perform empirical analysis on the factors that affect the filter performance. Simulation studies using randomly generated trajectories as well as trajectories executed by the AUVs during field experiments successfully demonstrate the feasibility of the technique. The proposed cooperative localization technique has the potential to prolong AUV mission time, and thus open the door for long-term autonomy underwater.Massachusetts Institute of Technology. Department of Mechanical EngineeringSingapore-MIT Alliance for Research and Technology (SMART) (Graduate Fellowship

Distributed Mobile Sensor Networks for Hazardous Applications

1Research Department for Underwater Acoustics and Marine Geophysics, Bundeswehr Technical Centre for Ships and Naval Weapons, Naval Technology and Research (WTD 71), Klausdorfer Weg 2, 24148 Kiel, Germany 2Navy Center for Applied Research in Artificial Intelligence, Naval Research Laboratory, 4555 Overlook Avenue S.W., Washington, DC 20375, USA 3Acoustic Research Laboratory, National University of Singapore, 21 Lower Kent Ridge Road, Singapore 119077 4 Systems Technology Department, NATO Undersea Research Centre (NURC), Viale S. Bartolomeo 400, 19126 La Spezia, Ital

Modeling and simulation of cell cycle in budding yeast

The molecular machinery of the cell cycle is known in detail for the budding yeast, Saccharomyces cerevisiae. In spite of its evolutionary distance from other complex organisms, the budding yeast cell cycle has many features which are similar to complex organisms. This allows budding yeast to be used as a model organism in cell cycle studies.Master of Science (Bioinformatics