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Irregular terrain boundary and area estimation with UAV

  • Tianwei ShiEmail author
  • Wenhua Cui
  • Ling Ren
  • Chi Zhang
Methodologies and Application
  • 13 Downloads

Abstract

This paper presents a novel and real-time estimation methodology to estimate the boundary and area of unknown irregular terrain with segmental arcs, concave and convex polygons using an unmanned aerial vehicle (UAV) as the measuring platform. The real-time videos obtained from the front facing and bottom facing cameras on the center of mass of UAV are used to select the flight direction and the boundary points of the estimated terrain. The tightly coupled integrated navigation system composed of the Strap-down Inertial Navigation System and the dual Global Positioning System pseudorange relative differential positioning is utilized to collect the positioning data of boundary points. For the final output positioning data, firstly, the Pauta criterion is applied to remove the anomalous positioning data. Then, the Extended Kalman Particle Filter (EKPF) is employed to optimize the remaining positioning data. After EKPF, the positional accuracy is upgraded to sub-meter level significantly. The actual flight experimental results of boundary and area estimation demonstrate the feasibility and effectiveness of the proposed estimation methodology. The area estimation error can be limited within ± 1%. It is essential that using this methodology can achieve the unknown irregular terrain estimation and it is not be restricted by time and space.

Keywords

Boundary and area estimation Unmanned aerial vehicle Integrated navigation system Pseudorange relative differential positioning Extended Kalman Particle Filter 

Notes

Acknowledgements

Tianwei Shi has been supported by the Department of Education of Liaoning Province (2017FWDF03), Natural Science Foundation of Liaoning Province of China (20180550567) and University of Science and Technology Liaoning Youth Fund (2017QN05). Wenhua Cui has been supported by the Department of Education of Liaoning Province (2016HZZD05). Chi Zhang has been supported by the National Science Foundation of China (61703069).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of International Finance and BankingUniversity of Science and Technology LiaoNingAnshanChina
  2. 2.Research and Development CenterLiaoning Systemteq Information Technology Co., Ltd.AnshanChina
  3. 3.School of Biomedical EngineeringDalian University of TechnologyDalianChina

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