Affiliation:
1. The School of Automation Science and Electrical Engineering, Beihang University, Beijing 100083, China
Abstract
Ground target detection and positioning systems based on lightweight unmanned aerial vehicles (UAVs) are increasing in value for aerial reconnaissance and surveillance. However, the current method for estimating the target’s position is limited by the field of view angle, rendering it challenging to fulfill the demands of a real-time omnidirectional reconnaissance operation. To address this issue, we propose an Omnidirectional Optimal Real-Time Ground Target Position Estimation System (Omni-OTPE) that utilizes a fisheye camera and LiDAR sensors. The object of interest is first identified in the fisheye image, and then, the image-based target position is obtained by solving using the fisheye projection model and the target center extraction algorithm based on the detected edge information. Next, the LiDAR’s real-time point cloud data are filtered based on position–direction constraints using the image-based target position information. This step allows for the determination of point cloud clusters that are relevant to the characterization of the target’s position information. Finally, the target positions obtained from the two methods are fused using an optimal Kalman fuser to obtain the optimal target position information. In order to evaluate the positioning accuracy, we designed a hardware and software setup, mounted on a lightweight UAV, and tested it in a real scenario. The experimental results validate that our method exhibits significant advantages over traditional methods and achieves a real-time high-performance ground target position estimation function.
Reference48 articles.
1. NLOS Target Positioning Method Based on UAV Millimeter-wave Radar;Xiang;IEEE Sens. J.,2023
2. A survey of indoor and outdoor uav-based target tracking systems: Current status, challenges, technologies, and future directions;Alhafnawi;IEEE Access,2023
3. A vision-based target detection, tracking, and positioning algorithm for unmanned aerial vehicle;Liu;Wirel. Commun. Mob. Comput.,2021
4. Multi-UAV cooperative system for search and rescue based on YOLOv5;Xing;Int. J. Disaster Risk Reduct.,2022
5. Madewell, E., Pollack, E., Kuni, H., Johri, S., Broyles, D., Vagners, J., and Leung, K. (2024, January 8–12). Beyond Visual Line-of-Sight Uncrewed Aerial Vehicle for Search and Locate Operations. Proceedings of the AIAA SCITECH 2024 Forum, Orlando, FL, USA.