Moving long baseline positioning algorithm with uncertain sound speed

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

This paper presents a Moving long baseline (MLBL) positioning algorithm for the underwater target considering the uncertain underwater sound speed. First, the positioning and the sound speed models are established. To tackle the uncertain sound speed, a Uncertain least squares (ULS) positioning algorithm is applied to estimate the target position and the sound speed. Then it is essentially shown that four mobile buoys are necessarily (at least) required to locate the target. Further, it is found that under a singularity scenario in which the ranges between the target and each of the mobile buoys are equal, there is no solution to the positioning according to the classical geometrical equations. In order to solve this singularity problem, an ULS-based Unscented Kalman filter (UKF) algorithm is proposed to obtain the estimated solution. Simulation results illustrate the effectiveness of proposed methods.

Original languageEnglish
Pages (from-to)3995-4002
Number of pages8
JournalJournal of Mechanical Science and Technology
Volume29
Issue number9
DOIs
StatePublished - 22 Sep 2015

Keywords

  • Mobile buoy
  • Moving long baseline
  • Sound speed
  • Unscented Kalman filter

Fingerprint

Dive into the research topics of 'Moving long baseline positioning algorithm with uncertain sound speed'. Together they form a unique fingerprint.

Cite this