Work

A Novel Vision‐Based PRPL Multistage Image Processing Algorithm for Autonomous Aerial Refueling

Year: 2021

Type: article

Abstract: Autonomous aerial refueling (AAR) technology can increase the flight endurance of unmanned air vehicles (UAVs) effectively. Drogue detection and target tracking method are significant for probe‐drogue refueling system in the docking stage. This paper proposes a novel vision‐based multistage image processing algorithm of drogue detection and target tracking for AAR. This algorithm divides the whole task into four stages: preprocessor, recognizer, predictor, and locker (PRPL). The adaptive threshold segmentation (ATS) algorithm and support vector machine (SVM) classifier are utilized in preprocessor and recognizer for drogue detection. An improved kernelized correlation filter (IKCF) tracking algorithm and scale adaptive method by window position as well as image resolution adjusted are adopted in predictor and locker for target tracking in complex dynamic environments. Finally, the proposed PRPL multistage image processing strategy is tested using an autonomous aerial refueling testbed. The results indicate that the proposed algorithm achieves high precision, good reliability, and real‐time capability compared with conventional algorithms. The average processing time is within 11 ms in various environments, which can meet the requirement for drogue detection and tracking in AAR.

Source: Wireless Communications and Mobile Computing

DOI: 10.1155/2021/2778857

Authors: Ling Wu, Yongrong Sun, Kedong Zhao, Xiyu Fu

Institutions: Nanhang Jincheng College, Nanjing University of Aeronautics and Astronautics

Language: English

Topic: Video Surveillance and Tracking Methods

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $2,550