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Cluster Computing

, Volume 22, Supplement 3, pp 5965–5974 | Cite as

A combined GPS UWB and MARG locationing algorithm for indoor and outdoor mixed scenario

  • Kun Zhang
  • Chong ShenEmail author
  • Qun Zhou
  • Haifeng Wang
  • Qian Gao
  • Yushan Chen
Article

Abstract

An indoor or outdoor positioning system is hard to position in cross-region and complex environment. In order to make up for the loss of blind zone in scenario change, we proposed a cooperative positioning system based on GPS/UWB/MARG, which can achieve the seamless positioning between buildings in the hybrid scene. In the hybrid scene, using a weighted fusion algorithm to achieve the cooperative positioning of GPS and UWB, and MARG is used to improve the positioning accuracy of GPS. With data optimization and performance analysis of a subsystem, we process GPS/MARG data and UWB data by weighted fusion method. The optimal positioning information in different positioning environments will be output after independent judgment. The results show that, compared with GPS/MARG positioning system, the average positioning accuracy of the cooperative positioning system is improved by 64% in the hybrid scene. In addition, it expands the application scenario of a single positioning system.

Keywords

Global positioning system Ultra-wideband Cooperative positioning Weighted fusion Circular error probable 

Notes

Acknowledgements

This research was financially supported by the National Natural Science Foundation of China (No. 61461017); the Hainan Natural Science Foundation Innovation Research Team Project (No. 2017CXTD0004); the Hainan Province Key Research and Development Projects (No. ZDYF2016002); the Innovative Research Project of Postgraduates in Hainan Province (No. Hyb2017-07); the Open Topic of State Key Laboratory of Marine Resources Utilization in South China Sea of Hainan University (No. 2016013A); the Key Laboratory of Sanya Project (No. L1410).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Kun Zhang
    • 1
    • 2
    • 3
  • Chong Shen
    • 1
    • 3
    Email author
  • Qun Zhou
    • 1
    • 3
  • Haifeng Wang
    • 1
    • 2
  • Qian Gao
    • 1
    • 3
  • Yushan Chen
    • 1
    • 3
  1. 1.State Key Laboratory of Marine Resources Utilization in South China SeaHainan UniversityHaikouChina
  2. 2.College of Ocean Information EngineeringHainan Tropical Ocean UniversitySanyaChina
  3. 3.College of Information Science and TechnologyHainan UniversityHaikouChina

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