Software defined jamming detection of drones

Abstract

The increasing use of wireless technologies in many aspects of people's lives has led to a congested electromagnetic spectrum, making it critical to manage the limited available spectrum as efficiently as possible. This is particularly important for military activities such as electronic warfare, where jamming is used to disrupt enemy communication, self-attacking drones, and surveillance drones. However, current detection methods used by Sri Lankan armed personnel, such as optical sensors and RADAR, do not include Radio Frequency (RF) analysis, which is crucial for identifying the signals used to operate drones. To combat security vulnerabilities posed by the rogue or unidentified transmitters, RF transmitters should be detected not only by the available data content of broadcasts but also by the physical properties of the transmitters. This requires faster fingerprinting and identifying procedures that go beyond the traditional hand-engineered methods. In this thesis, RF data from the drone remote is identified and collected using Software Defined Radio (SDR), a radio that employs software to perform signal-processing tasks that were previously accomplished by hardware. A deep learning model is then provided to train and detect modulation strategies utilized in drone communication, as well as a suitable jamming strategy. This thesis presents an overview of neutralization of Unmanned Aerial Vehicle (UAV), communication signals, and Deep Learning (DL) applications. It also proposes an intelligent system for modulation detection and jamming of drones based on SDR. The DL approaches in these applications, as well as the development of more complicated UAV neutralization methods, appear to be promising research fields. Finally, the goal of this thesis is to connect recent research themes in the disciplines of UAV neutralization, signals of communications, and Machine Learning (ML) and DL applications in order to produce a more efficient and effective approach for identifying and neutralizing drones. The proposed intelligent system for modulation detection and jamming of drones based on SDR, along with use of deep learning approaches, holds great potential for future research in this field