MIT Department of Ocean Engineering
Acoustics Group

REAL-TIME, ADAPTIVE ENVIRONMENTAL ASSESSMENT

using

AUTONOMOUS OCEANOGRAPHIC SAMPLING NETWORKS

Principal Investigators

Prof. Henrik Schmidt , Dept. Ocean Engineering, MIT
Prof. A.B. Baggeroer , Dept. Ocean Engineering,MIT
Dr. James Bellingham, MIT Sea Grant , Head of AUV Laboratory

Staff

Dr. John Leonard, MIT Sea Grant AUV Laboratory
Dr. Brad Moran, MIT Sea Grant AUV Laboratory

Students

Max Deffenbaugh
Pierre Elisseef

Collaborating Institutions

Woods Hole Oceanographic Institution
Institute of Ocean Sciences, Sidney, BC, Canada.

Objectives

High resolution, 3-d mapping of oceanographic phenomenae for:

Verification of hypotheses and mathematical/numerical models.
Environmental monitoring
Environmental mapping
Tactical Oceanography
Mine Countermeasures

Background

The verification of oceanographic hypotheses involves measurement of spatial and temporal gradients, requiring high spatial and temporal resolution. Traditional oceanographic measurement approaches are limited in terms of coverage and resolution:

Towed sensors: Coverage limited by ship mobility. Resolution limited by navigation. Temporal and spatial samplings are not uncoupled
Lagrangean Floats: Passively follow flow field. Temporal and spatial sampling are not uncoupled.
Satelite imagery: Provides only surface measurements. Excellent coverage in surface plane, but resolution in general insufficient for gradient measurements.
Acoustic tomography: Provides excellent coverage in vertical slices. Resolution dependent on number of acoustic paths through region, insufficient for gradient estimates.
Autonomous Underwater Vehicles (AUV): High resolution in space and time. Excellent synoptic coverage, but time and space gradient measurements are coupled, i.e. do not provide ``snap shots'' of oceanographic parameters.

Solution

Hybrid Adaptive Sampling Network Concept:

Tomography: provides mapping coverage, and high-resolution navigation for AUV-s.
AUV network: provides rapid response and direct, high-resolution measurements of oceanographic parameters

Integrated AUV navigation and acoustic tomography

Adaptively improves tomography resolution by having mobile tomography sources.
Improves tomography coverage by adaptive mobility of sources.
Higher resolution of sensor navigation by simultaneously estimating oceanography.
Tomography provides coverage in terms of spatial ``snap shots'' of oceanographic parameters.

Local Area Network (LAN) Architecture.

Integration with acoustic communication network technology provides standard Internet architecture for sampling network, including AUV-s.
AUV sampling strategies optimizing resolution may be designed.

Flexible Deployment

Network ultimately deployable from airplanes or ships anywhere in the world.
Deep/shallow water.
Standard NFS (Network Filing System) protocol for data telemetry to and from remote control center.
Flexible communication requirements (Satelite, WLAN (Wireless Local Area Network), Fiber optics).

Benefits

Rapid deployment in oceanographic active areas
Deployment flexibility.
Shallow/deep water.
Improves resolution of oceanographic measurements by orders of magnitude.
Optimal sampling strategies by focusing on high gradient regions.
Low cost. Autonomous/remotely operated once deployed. No ships needed once deployed.

Deployment Schedule

May 1995: Bermuda. Deep water AUV test
June 1995: Juan de Fuca. Deep water, rapid response.
Fall 1995: Buzzard's Bay. Navigation-communication network test.
April 1996: Buzzard's Bay. Test deployment of Haro Strait AOSN
June 1996: Haro Strait, BC Real-time mapping of frontal dynamics.
Summer 1996: Bermuda. Deep water, communication-navigation, rapid response.
Winter 1997: Labrador Sea. Deep water. Rapid response to satellite detected convective overturning. Real-time, remote data collection and control.