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Irregular terrain boundary and area estimation with UAV
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论文类型: 期刊论文
发表时间: 2019-11-01
发表刊物: SOFT COMPUTING
收录刊物: SCIE
卷号: 23
期号: 22
页面范围: 11523-11537
ISSN号: 1432-7643
关键字: Boundary and area estimation; Unmanned aerial vehicle; Integrated navigation system; Pseudorange relative differential positioning; Extended Kalman Particle Filter
摘要: 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.

张驰

副教授   硕士生导师

性别: 男

毕业院校:东北大学

学位: 博士

所在单位:生物医学工程学院

学科:生物医学工程. 信号与信息处理

电子邮箱:chizhang@dlut.edu.cn

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