Radar Challenges and Solutions for Drone Detection

This paper explores recent advancements in radar systems for drone detection, focusing on two key challenges: extracting weak signals and reliably recognizing small drone echoes. Traditional approaches often employ multi-layered sensor architectures–combining radars at various frequency bands with EO/IR (Electro-Optical/Infrared) sensors–based on the assumption that a single radar cannot effectively address these issues. In contrast, we argue that an effective drone detection radar should function as a comprehensive WYSIWYG (What You See Is What You Get) platform, offering 24/7 autonomous operation, long detection range, real-time responsiveness, and robust recognition capabilities. To achieve this, we propose a reconfiguration of the conventional radar signal processing chain, reducing dependence on track-based recognition. A case study demonstrates the practical viability of this approach, showing that a single radar, equipped with track-free Automatic Target Recognition (ATR) technology, can deliver long-range detection, real-time performance, and reliable classification of small drones.