  This paper discusses the challenges of detecting and categorizing small
drones with radar automatic target recognition (ATR) technology. The authors
suggest integrating ATR capabilities into drone detection radar systems to
improve performance and manage emerging threats. The study focuses primarily on
drones in Group 1 and 2. The paper highlights the need to consider kinetic
features and signal signatures, such as micro-Doppler, in ATR techniques to
efficiently recognize small drones. The authors also present a comprehensive
drone detection radar system design that balances detection and tracking
requirements, incorporating parameter adjustment based on scattering region
theory. They offer an example of a performance improvement achieved using
feedback and situational awareness mechanisms with the integrated ATR
capabilities. Furthermore, the paper examines challenges related to one-way
attack drones and explores the potential of cognitive radar as a solution. The
integration of ATR capabilities transforms a 3D radar system into a 4D radar
system, resulting in improved drone detection performance. These advancements
are useful in military, civilian, and commercial applications, and ongoing
research and development efforts are essential to keep radar systems effective
and ready to detect, track, and respond to emerging threats.
