Yao Xing
Guangxi Colleges and Universities Key Laboratory of Unmanned Aerial Vehicle(UAV)Telemetry，Guilin University of Aerospace Technology，Guilin 541004,ChinaLiu Qiong
Guangxi Colleges and Universities Key Laboratory of Unmanned Aerial Vehicle(UAV)Telemetry，Guilin University of Aerospace Technology，Guilin 541004,ChinaTan Zhicheng
1.Guangxi Colleges and Universities Key Laboratory of Unmanned Aerial Vehicle(UAV)Telemetry，Guilin University of Aerospace Technology，Guilin 541004,China； 2.School of Information Science and Engineering，Xiamen University，Xiamen 361005,China1.Guangxi Colleges and Universities Key Laboratory of Unmanned Aerial Vehicle(UAV)Telemetry，Guilin University of Aerospace Technology，Guilin 541004,China; 2.School of Information Science and Engineering，Xiamen University，Xiamen 361005,China
TP391
Since the popularity of UAVs has brought about many privacy and security problems, the solution should comply with dynamic and effective detection of UAV signals, so as to achieve effective control. This paper proposes a software radio intrusion detection method for UAV with hardware implementation. It uses adaptive denoising and cubic clustering to recognize and classify UAV signals. Simulation results show that the detection probability can reach 100% when the SNR is above -16.2 dB. Based on the software radio platform AD9361+FPGA+STM32 as the core, it carries out the relevant engineering implementation. The measured results show that it is practical and effective, which can effectively identify UAV signals and types in both indoor and outdoor complex environments with strong application prospect.
