4.6 Article

Irregular terrain boundary and area estimation with UAV

Journal

SOFT COMPUTING
Volume 23, Issue 22, Pages 11523-11537

Publisher

SPRINGER
DOI: 10.1007/s00500-018-03692-8

Keywords

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

Funding

  1. Department of Education of Liaoning Province [2016HZZD05]
  2. Natural Science Foundation of Liaoning Province of China [20180550567]
  3. University of Science and Technology Liaoning Youth Fund [2017QN05]
  4. National Science Foundation of China [61703069]

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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.

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