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http://dx.doi.org/10.9708/jksci.2018.23.12.011

Airborne Antenna Switching Strategy Using Deep Learning on UAV Line-Of-Sight Datalink System  

Jo, Se-Hyeon (Hanwha Systems Co.)
Lee, Woo-Sin (Hanwha Systems Co.)
Kim, Hack-Joon (Hanwha Systems Co.)
Jin, So-Yeon (Hanwha Systems Co.)
Yoo, In-Deok (Hanwha Systems Co.)
Publication Information
Journal of the Korea Society of Computer and Information / v.23, no.12, 2018 , pp. 11-19 More about this Journal
Abstract
In the Unmanned Aerial Vehicle Line-Of-Sight datalink system, there is a possibility that the communication line is disconnected because line of sight can not be secured by one antenna due to changes in position and posture of the air vehicle. In order to prevent this, both top and bottom of air vehicle are equipped with antennas. At this time, if the signal can be transmitted and received by switching to an antenna advantageous for securing the line of sight, communication disconnection can be minimized. The legacy antenna switching method has disadvantages such that diffraction, fading due to the surface or obstacles, interference and reflection of the air vehicle are not considered, or antenna switching standard is not clear. In this paper, we propose an airborne antenna switching method for improving the performance of UAV LOS datalink system. In the antenna switching method, the performance of each of the upper and lower parts of the mounted antenna according to the position and attitude of the air vehicle is predicted by using the deep learning in an UAV LOS datalink system in which only the antenna except the receiver is duplicated. Simulation using flying test dataset shows that it is possible to switch antennas considering the position and attitude of unmanned aerial vehicle in the datalink system.
Keywords
Deep learning; LOS; Datalink; Antenna; Switching; UAV;
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Times Cited By KSCI : 1  (Citation Analysis)
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