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An Integrated Navigation and Localization System

  • School of Information Science and Engineering, Harbin Institute of Technology Weihai
  • The Guangxi Key Laboratory of Automatic Detecting Technology and Instruments

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

Abstract

Navigation and localization technique is a critical part of an autonomous underwater vehicle (AUV). It provides critical position information, and determines the efficiency and accuracy of underwater tasks. To improve the accuracy and reliability of the navigation and localization system, we proposed an integrated navigation and localization system with a federated Kalman filter. In this system, we first utilize an improved Kalman filter-based SINS/DVL combined localization method to improve the tracking ability and position accuracy of the inertial navigation. Then we explore an ultra-short baseline (USBL) base phase difference Kalman filtering to improve the localization accuracy of USBL. Finally, we resort to a federated Kalman filter to integrate the SINS/DVL/USBL combined localization system. Experimental results illustrated the navigation and localization system could enhance the positioning accuracy effectively.

Original languageEnglish
Title of host publicationProceedings - 5th IEEE International Conference on Smart Internet of Things, SmartIoT 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages28-32
Number of pages5
ISBN (Electronic)9781665445115
DOIs
StatePublished - 2021
Externally publishedYes
Event5th IEEE International Conference on Smart Internet of Things, SmartIoT 2021 - Virtual, Online, Korea, Republic of
Duration: 13 Aug 202115 Aug 2021

Publication series

NameProceedings - 5th IEEE International Conference on Smart Internet of Things, SmartIoT 2021

Conference

Conference5th IEEE International Conference on Smart Internet of Things, SmartIoT 2021
Country/TerritoryKorea, Republic of
CityVirtual, Online
Period13/08/2115/08/21

Keywords

  • Federated Kalman filters
  • Integrated localization
  • Localization

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