Radio frequency based distributed system for noncooperative UAV classification and positioning
SIGNAL (programming language)
Time of arrival
DOI:
10.1016/j.jiixd.2023.07.002
Publication Date:
2023-08-09T01:57:45Z
AUTHORS (3)
ABSTRACT
With the increasing popularity of civilian unmanned aerial vehicles (UAVs), safety issues arising from unsafe operations and terrorist activities have received growing attention. To address this problem, an accurate classification positioning system is needed. Considering that UAVs usually use radio frequency (RF) signals for video transmission, in paper, we design a passive distributed monitoring can classify locate according to their RF signals. Specifically, three receivers are arranged different locations receive Due noncooperation between UAV receivers, it necessary detect whether there signal Hence, convolutional neural network (CNN) proposed not only presence UAV, but also its type. After detected, time difference arrival (TDOA) arriving at receiver estimated by cross-correlation method obtain corresponding distance difference. Finally, Chan algorithm used calculate location UAV. We deploy constructed software defined (SDR) on campus playground, conduct extensive experiments real wireless environment. The experimental results successfully validated system.
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