Indexed by:Journal Papers

Date of Publication:2019-11-01

Journal:SOFT COMPUTING

Included Journals:SCIE

Volume:23

Issue:22

Page Number:11523-11537

ISSN No.:1432-7643

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

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.