Project Outline:
As drones are becoming ubiquitous in our daily life, privacy and security concerns caused by them are of ever increasing. For example, they could be illegally used for spying or flying in protected regions (e.g., nearby airports). Therefore, drone detection is on a high demand. This project focuses on drone detection based on radio frequency (RF) used in their wireless communications with the controllers or ground stations. The first task of this project is to conduct a thorough literature review on different RF drone detection strategies, identifying the communication frequency, handshake process, and handover stages. The review should clarify the difference between drone RF and other RF (e.g., WiFi) signals. In addition, the frequency hopping may be used in drone communications and thus communication channel tracking should be also examined in this task. The second task of this project is to test various RF drone detection schemes on the available drone systems (e.g., DJI Matrice 300 RTK, DJI RoboMaster TT Starter) and software defined radios (SDRs) or spectrum analyzer. The last task is to develop new and novel RD drone detection schemes, of which the performance should be analyzed and tested. This project should lead to multiple high-quality journal publications.
Literature samples:
- 10 Counter-Drone Technologies To Detect And Stop Drones Today
- Drone Detection Approach Based on Radio-Frequency Using Convolutional Neural Network
- UAV Detection and Identification Based on WiFi Signal and RF Fingerprint
- Radio Frequency Toolbox for Drone Detection and Classification
Available platforms at ECU:
- DJI Matrice 300 RTK
- DJI RoboMaster TT Starter
- R&S FSV3000 Signal and spectrum analyzer
- Ettus USRP X310
- Ettus USRP N210
- Long range internet antenna Kit
- Practical example
Preferred Skills (not required): Experience with software define radios, MATLAB, basic wireless communication knowledge.
Project Area: Wireless Cybersecurity
Research Centre: Security Research Institute (SRI)
Supervisor(s): Dr Shihao YAN
Project level: Masters / PhD
Funding: Applicant should apply for ECUHDR or RTP Scholarship
Start date: Any
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