Ensemble Kalman Filter with a Square Root Scheme (EnKF-SR) for Trajectory Estimation of AUV SEGOROGENI ITS

Herlambang, Teguh and Djatmiko, Eko Budi and Nurhadi, Hendro (2015) Ensemble Kalman Filter with a Square Root Scheme (EnKF-SR) for Trajectory Estimation of AUV SEGOROGENI ITS. International Review of Mechanical Engineering (I.RE.ME.), 9. pp. 553-560. ISSN 1970- 8734

[thumbnail of Jurnal Internasional (IREME).pdf]
Preview
Text
Jurnal Internasional (IREME).pdf - Published Version

Download (3MB) | Preview

Abstract

Results of a study on the development of navigation system and guidance for A UV are
presented in this paper. The study was carried to evaluate the behavior of A UV SEGOROGENI
ITS, designed with a characteristic length of 980 mm, cross-section diameter of i80 mm, for
operation in a 3.0 m water depth, at a maximum forward speed of 1.94 knots. The most common
problem in the development of AUVs is the limitation in the mathematical model and the
restriction on the degree of freedom in simulation. in this study a model of linear system was
implemented, derived from a non-linear system that is linearized utilizing the Jacobian matrix. The
linear system is then implemented as a platform to estimate the trajecto1y. in this respect the
estimation is carried out by adopting the method of Ensemble Kalman Filter Square Root (EnKFSR).
The EnKF-SR method basically is developedfrom EnKF at the stage of correction algorithm.
The implementation of EnKF-SR on the linear model comprises of three simulations, each of
which generates 100, 200 and 300 ensembles. The best simulation exhibited the error behveen the
real tracking and the simulation in translation mode was in the order of 0. 009 m/s, whereas in the
rotation mode was some 0. 00 I radls. These fact indicates the accuracy of higher than 9 5% has
been achieved. Copyright© 2015 Praise Worthy Prize S.r.l.

Item Type: Article
Uncontrolled Keywords: A UV, EnKF-SR, Linear System, Trajectoty Estimation
Subjects: V Naval Science > VM Naval architecture. Shipbuilding. Marine engineering > VM365 Remote submersibles. Autonomous vehicles.
Divisions: Faculty of Industrial Technology > Mechanical Engineering
Depositing User: Mr. Tondo Indra Nyata
Date Deposited: 09 Aug 2019 07:45
Last Modified: 27 Aug 2019 01:05
URI: http://repository.its.ac.id/id/eprint/70236

Actions (login required)

View Item View Item