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Acta Aeronautica et Astronautica Sinica ›› 2023, Vol. 44 ›› Issue (17): 328143-328143.doi: 10.7527/S1000-6893.2022.28143

• Electronics and Electrical Engineering and Control • Previous Articles     Next Articles

Surveying and mapping path planning method for UAV-borne SAR considering terains

Yougang XIAO, Xiangna MAN, Guohua WU, Qizhang LUO()   

  1. College of Traffic and Transportation Engineering,Central South University,Changsha 410073,China
  • Received:2022-10-20 Revised:2022-12-03 Accepted:2023-01-18 Online:2023-09-15 Published:2023-02-13
  • Contact: Qizhang LUO E-mail:qz_luo@csu.edu.cn
  • Supported by:
    National Natural Science Foundation of China(62073341)

Abstract:

Synthetic Aperture Radar (SAR) can obtain high-resolution images regardless of the influence of weather and time; therefore, it is widely used in mapping, disaster monitoring, environmental monitoring, resource reconnaissance, etc. Due to the side-view imaging of SAR, the radar beam will be blocked by obstacles in some complex terrains, resulting in layover and shadow. This will not only cause data missing but also aggravate the workload of subsequent data processing. To address the above problems, it is usually necessary to ensure the overlap ratio of adjacent flight swaths to reduce the influence of layover and shadow on image quality when planning the path of the Unmanned Aerial Vehicle (UAV)-borne SAR. To reduce the overlap ratio while ensuring high-quality images, this paper studies the SAR mapping path planning problem considering terrains. Taking the lateral overlap ratio, coverage ratio, and overlap ratio as evaluation targets, a UAV-borne SAR mapping path planning method is proposed based on simulated annealing. Simulation experiments are carried out to verify the proposed method. The experimental results show that the method proposed can control the lateral overlap ratio of flight swath within the set value, and make the coverage ratio reach more than 90%. The number of paths decreased by 31.21% compared with that of the method based on the average altitude plane, and the coverage ratio of test area increased by 84.8% compared with that of the method without considering the terrain. The geometric deformation ratio and the number of redundant paths are also reduced by 8.73% and 100% respectively compared with that of the Greedy algorithm.

Key words: area coverage, path planning, UAV surveying and mapping, UAV-borne SAR, terains, simulated annealing

CLC Number: