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Cluster Computing

, Volume 22, Supplement 3, pp 5603–5612 | Cite as

A passive detection and tracking divers method based on energy detection and EKF algorithm

  • Yun Li
  • Sumit ChakravartyEmail author
  • Shanlin Sun
  • Zhicheng Tan
  • Lili Sheng
  • Ming Yang
  • Xintong Wu
Article

Abstract

Divers have always played a strategic role throughout history. They are competent to perform numerous tasks which are inaccessible to others. However, they can also prove to be a formidable foe, especially in shallow port, waterway locations. This is evident from numerous criminal incidents in past wherein divers played a significant role. In order to protect these maritime locations from possible damages by unfriendly divers and effectively improve security of Territorial Ocean, this paper presents a passive detection and tracking of diver procedure based on Energy Detection and extended Kalman Filter (EKF) algorithm is proposed, simple named PDTDM. PDTDM method can effectively distinguish divers from marine animals in complexity underwater environment. PDTDM method can perform nonlinear tracking with high accuracy with low energy consumption. Difference time-delay and Doppler shift obtained from “chirp” analysis are used as parameters for EKF to generate the track which is then applied into, energy detection and 3D location framework is used to obtain reliable coordinates of divers. It is also used to differentiate divers from other possible marine artifacts. Simulation shows that PDTDM method can reduce energy consumption using the reliable detection scheme while improve the accuracy of tracking divers.

Keywords

Divers Energy detection Three-dimensional localization technology EKF 

Notes

Acknowledgements

This work was supported in part by the following projects: the National Natural Science Foundation of China through the Grants 61571318, the Guangxi Nature Science Fund (2015GXNSF AA139298, 2016GXNSFAA380226), Guangxi Science and Technology Project (AC16380094, 1598008-29), Guangxi Nature Science Fund Key Project (2016 GXNSFDA380031), and Guangxi University Science Research Project (ZD 2014146).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  • Yun Li
    • 1
    • 2
  • Sumit Chakravarty
    • 3
    Email author
  • Shanlin Sun
    • 1
  • Zhicheng Tan
    • 1
  • Lili Sheng
    • 1
  • Ming Yang
    • 3
  • Xintong Wu
    • 4
  1. 1.College of Electronic Information and AutomationGuilin University of Aerospace TechnologyGuilinChina
  2. 2.School of Electronic and Information EngineeringTianjin UniversityTianjinChina
  3. 3.Department of Electrical EngineeringKennesaw State UniversityMariettaUSA
  4. 4.School of information and communicationGuilin University of Electronic TechnologyGuilinChina

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