Marine Vehicle Sensor Network Architecture and Protocol Designs for Ocean Observation

The micro-scale and meso-scale ocean dynamic processes which are nonlinear and have large variability, have a significant impact on the fisheries, natural resources, and marine climatology. A rapid, refined and sophisticated observation system is therefore needed in marine scientific research. The maneuverability and controllability of mobile sensor platforms make them a preferred choice to establish ocean observing networks, compared to the static sensor observing platform. In this study, marine vehicles are utilized as the nodes of mobile sensor networks for coverage sampling of a regional ocean area and ocean feature tracking. A synoptic analysis about marine vehicle dynamic control, multi vehicles mission assignment and path planning methods, and ocean feature tracking and observing techniques is given. Combined with the observation plan in the South China Sea, we provide an overview of the mobile sensor networks established with marine vehicles, and the corresponding simulation results.

[1]  Eric Blayo,et al.  A reduced-order strategy for 4D-Var data assimilation , 2005, 0709.2825.

[2]  Naomi Ehrich Leonard,et al.  Preparing to predict: The Second Autonomous Ocean Sampling Network (AOSN-II) experiment in the Monterey Bay , 2009 .

[3]  Gaurav S. Sukhatme,et al.  Planning and Implementing Trajectories for Autonomous Underwater Vehicles to Track Evolving Ocean Processes Based on Predictions from a Regional Ocean Model , 2010, Int. J. Robotics Res..

[4]  Alberto Alvarez,et al.  Combining networks of drifting profiling floats and gliders for adaptive sampling of the Ocean , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[5]  Peter M. Atkinson,et al.  Evaluating the utility of the ensemble transform Kalman filter for adaptive sampling when updating a hydrodynamic model , 2009 .

[6]  David M. Fratantoni,et al.  Introduction to the Autonomous Ocean Sampling Network (AOSN-II) program , 2009 .

[7]  D. Fratantoni,et al.  A thin layer of phytoplankton observed in the Philippine Sea with a synthetic moored array of autonomous gliders , 2009 .

[8]  Dario Pompili,et al.  Overview of networking protocols for underwater wireless communications , 2009, IEEE Communications Magazine.

[9]  David M. Fratantoni,et al.  UNDERWATER GLIDERS FOR OCEAN RESEARCH , 2004 .

[10]  Naomi Ehrich Leonard,et al.  Nonlinear gliding stability and control for vehicles with hydrodynamic forcing , 2008, Autom..

[11]  Naomi Ehrich Leonard,et al.  Routing strategies for underwater gliders , 2009 .

[12]  David M. Fratantoni,et al.  Multi-AUV Control and Adaptive Sampling in Monterey Bay , 2006, IEEE Journal of Oceanic Engineering.

[13]  A. Pascual,et al.  Coastal and mesoscale dynamics characterization using altimetry and gliders: A case study in the Balearic Sea , 2010 .

[14]  Lisamarie Windham-Myers,et al.  Experimental removal of wetland emergent vegetation leads to decreased methylmercury production in surface sediment , 2009 .

[15]  Naomi Ehrich Leonard,et al.  Cooperative Filters and Control for Cooperative Exploration , 2010, IEEE Transactions on Automatic Control.

[16]  Andrea L. Bertozzi,et al.  Environmental boundary tracking and estimation using multiple autonomous vehicles , 2007, 2007 46th IEEE Conference on Decision and Control.

[17]  Nicholas M. Patrikalakis,et al.  Multi-vehicle oceanographic feature exploration , 2009 .

[18]  Pierre F. J. Lermusiaux,et al.  Adaptive modeling, adaptive data assimilation and adaptive sampling , 2007 .

[19]  Naomi Ehrich Leonard,et al.  Collective Motion, Sensor Networks, and Ocean Sampling , 2007, Proceedings of the IEEE.

[20]  Pierre Testor,et al.  Impact of data assimilation of glider observations in the Ionian Sea (Eastern Mediterranean) , 2010 .

[21]  Takeshi Sakanoi,et al.  Small and meso-scale properties of a substorm onset auroral arc , 2010 .

[22]  Fumin Zhang,et al.  Steady three dimensional gliding motion of an underwater glider , 2011, 2011 IEEE International Conference on Robotics and Automation.

[23]  Ecmwf Newsletter,et al.  EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS , 2004 .

[24]  Sonia Martínez,et al.  Monitoring Environmental Boundaries With a Robotic Sensor Network , 2006, IEEE Transactions on Control Systems Technology.

[25]  N.M. Patrikalakis,et al.  Path Planning of Autonomous Underwater Vehicles for Adaptive Sampling Using Mixed Integer Linear Programming , 2008, IEEE Journal of Oceanic Engineering.

[26]  N. Pinardi,et al.  An oceanographic three-dimensional variational data assimilation scheme , 2008 .

[27]  Pierre F. J. Lermusiaux,et al.  Nonlinear optimization of autonomous undersea vehicle sampling strategies for oceanographic data-assimilation , 2007, J. Field Robotics.

[28]  Pradeep Bhatta,et al.  Nonlinear Stability and Control of Gliding Vehicles , 2006 .