Abstract
Unmanned aerial vehicle (UAV) technology has been widely utilized in military and civilian fields such as rescue, disaster relief, urban planning, and material transportation. Obtaining the current position information of a UAV is of great significance in the performance of its tasks. However, positioning technology may fail in harsh environments. This article proposes the following solutions to address this problem: we eliminate interference and recover useful information by a dark channel algorithm and an attention generation adv ersarial network; visual and geomagnetic signals are fused to improve the safety of positioning technology; and a two-path convolutional network is proposed to optimize the feature extraction method and extract the continuity information of data. Moreover, open research work and challenges are also discussed.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
