A Lower Bound for Controlled Lagrangian Particle Tracking Error
Author(s)
Szwaykowska, Klementyna
Advisor(s)
Editor(s)
Collections
Supplementary to:
Permanent Link
Abstract
Autonomous underwater vehicles are flexible mobile
platforms for ocean sampling and surveillance missions.
However, navigation of these vehicles in unstructured, highly
variable ocean environments poses a significant challenge.
Model-based prediction of vehicle position may be used to
improve navigation capability, but prediction error exists due
to limited resolution and accuracy of flow values obtained
from ocean models that calculate flow velocity at discrete grid
points. We present a theoretical lower bound on the steady-state
error in position prediction for underwater vehicles using
ocean model flow data and show that it is determined by the
gridsize used by the ocean models. Our conclusions are justified
by simulation and data collected during an ocean experiment.
Sponsor
Date
2010-12
Extent
Resource Type
Text
Resource Subtype
Proceedings