The proliferation of drones in both civilian and military domains has raised significant concerns regarding their potential misuse for malicious activities. In response, there has been a growing interest in developing effective counter-drone systems to mitigate potential threats posed by unauthorized drone operations. This paper provides a comprehensive review of recent advancements in counter-drone technology, focusing on detection, identification, tracking, and mitigation techniques. Various sensor modalities, including radar, electro-optical, acoustic, and radio frequency, are explored for their efficacy in detecting and tracking drones in different environments and scenarios. Furthermore, we discuss emerging trends such as machine learning and artificial intelligence algorithms for enhancing the accuracy and efficiency of counter-drone systems. Additionally, we evaluate the legal and ethical considerations surrounding the deployment of counter-drone technology, emphasizing the need for a balanced approach that ensures security without infringing upon individual privacy rights. By synthesizing current research and technological developments, this paper aims to provide valuable insights into the state-of-the-art in counter-drone systems and inform future research directions in this rapidly evolving field. Keywords: Counter-drone systems, Drone detection, Radio frequency, Security measures, Radar
Elchin Guliyev (Fri,) studied this question.