Observability analysis for cooperative navigation system in autonomous underwater vehicles

Wenbai Li, Mingyong Liu, Xiaokang Lei, Fei Xu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

Abstract

Precise navigation of autonomous underwater vehicles (AUV) is one of the most important challenges for marine applications. Current 2-dimensional (2D) navigation systems (algorithms) are effective to autonomous surface vehicles (ASV) operations, but still have some limitations for AUV navigation in 3D underwater environment. In this paper, a 3D range navigation algorithm is proposed that is potentially useful for small AUVs that have severe volume and power constraints. This algorithm enables an AUV to compute its trajectory in the presence of unknown currents and simultaneously estimate the currents by using range measurements from a single known location (beacon). The principal work here is the observability analysis of the proposed navigation system that characterizes observable AUV trajectories using novel approaches towards uniform observability of linear time varying systems. Then, implementation of the 3D range navigation algorithm as a discrete time extended Kalman filter is given based on the observability results and kinematic model of the system. Finally, a set of comparative simulation results verify the validity of the navigation algorithm and the system's observability related to trajectories.

Original languageEnglish
Title of host publicationProceedings - 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2010
Pages155-161
Number of pages7
DOIs
StatePublished - 2010
Externally publishedYes
Event2010 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2010 - Xiamen, China
Duration: 29 Oct 201031 Oct 2010

Publication series

NameProceedings - 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2010
Volume1

Conference

Conference2010 IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 2010
Country/TerritoryChina
CityXiamen
Period29/10/1031/10/10

Keywords

  • Autonomous underwater vehicle
  • Extended Kalman filter
  • Navigation system
  • Observability
  • Unknown currents

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