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This paper discusses the challenges of detecting and categorizing smalldrones with radar automatic target recognition (ATR) technology. The authorssuggest integrating ATR capabilities into drone detection radar systems toimprove performance and manage emerging threats. The study focuses primarily ondrones in Group 1 and 2. The paper highlights the need to consider kineticfeatures and signal signatures, such as micro-Doppler, in ATR techniques toefficiently recognize small drones. The authors also present a comprehensivedrone detection radar system design that balances detection and trackingrequirements, incorporating parameter adjustment based on scattering regiontheory. They offer an example of a performance improvement achieved usingfeedback and situational awareness mechanisms with the integrated ATRcapabilities. Furthermore, the paper examines challenges related to one-wayattack drones and explores the potential of cognitive radar as a solution. Theintegration of ATR capabilities transforms a 3D radar system into a 4D radarsystem, resulting in improved drone detection performance. These advancementsare useful in military, civilian, and commercial applications, and ongoingresearch and development efforts are essential to keep radar systems effectiveand ready to detect, track, and respond to emerging threats.

Introduction to Drone Detection Radar with Emphasis on Automatic Target Recognition (ATR) technology