Publication:
Sonar localization of an autonomous underwater vehicle

Loading...
Thumbnail Image
Authors
Percin, Enis.
Subjects
AUV
Extended Kalman filter
Nonlinear systems
Potential function
ARX model
Advisors
Cristi, Roberto
Date of Issue
1993-12
Date
December 1993
Publisher
Monterey, California. Naval Postgraduate School
Language
en_US
Abstract
Two different algorithms to navigate an AUV within a charted environment are presented. They use sonar returns and a local map together with the dynamic model to estimate the vehicle's position and acceleration at all times. Kalman filtering techniques are used to compute the estimates. The main difficulty is the presence of uncharted obstacles, which are identified by the potential function algorithm. Results show that first algorithm works in an environment without obstacles. Results from the application of the potential function algorithm in a pool using Tritech ST725 high resolution sonar show the feasibility and robustness of the potential function approach to the navigation problem.
Type
Thesis
Description
Series/Report No
Department
Department of Electrical and Computer Engineering
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
Sponsors
Funder
Format
67 p.
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
Copyright is reserved by the copyright owner
Collections