A new paper by researchers at Wuhan University in China explores recent advancements in radar systems for drone detection, focusing on two key challenges: extracting weak signals and reliably recognising 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,” the paper states. “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, the team, led by Jiangkun Gong, Jun Yan and Deren Li, proposes a reconfiguration of the conventional radar signal processing chain, reducing dependence on track-based recognition.
The paper includes a case study demonstrating the practical viability of this approach. The team says this study shows 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”.
For more information
Paper: Radar challenges and solutions for drone detection [registration required]
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