A comparison of two approaches for adaptive sampling of environmental processes using autonomous underwater vehicles

Author

Cannell, Christopher J. ; Stilwell, Daniel J.

Author_Institution

Bradley Dept. of Electr. & Comput. Eng., Virginia Polytech. Inst. & State Univ., Blacksburg, VA

fYear

2005

fDate

17-23 Sept. 2005

Firstpage

1514

Abstract

Two classes of adaptive sampling of underwater processes are considered for autonomous underwater vehicle (AUV) applications. The first approach is based on estimating parameters of an assumed process model using either Kalman filter or least squares techniques. The second, nonparametric approach is based on information-theoretic concepts and incorporates a classification phase in lieu of a process model. Two applications of each method are evaluated for processes with closed boundaries. Specifically, we utilize a finite element simulation of neutral tracer injection advected by a turbulent flow field

Keywords

Kalman filters; finite element analysis; least squares approximations; oceanographic techniques; oceanography; sampling methods; seawater; underwater vehicles; Kalman filter; adaptive sampling; autonomous underwater vehicles; environmental processes; finite element simulation; information theory; least squares technique; neutral tracer injection; process model; turbulent flow field; Anthropometry; Application software; Finite element methods; Humans; Information theory; Least squares approximation; Parameter estimation; Sampling methods; Testing; Underwater vehicles;

fLanguage

English

Publisher

ieee

Conference_Titel

OCEANS, 2005. Proceedings of MTS/IEEE

Conference_Location

Washington, DC

Print_ISBN

0-933957-34-3

Type

conf

DOI

10.1109/OCEANS.2005.1639970

Filename

1639970