Drone Detection Radar / CUAS Radar

Unmanned Aerial Vehicles (UAVs / UAS / Drones) present a significant threat within contemporary military and defense environments, as well as within airspace-controlled areas such as airports, correctional facilities and sports arenas. Deploying specialist radar systems tailored for drone detection has therefore become imperative within these environments. 

These systems, typically referred to as Counter-Unmanned Aerial Systems (CUAS) radar, or Drone Detection Radar, utilize advanced, optimized technologies to detect and track unauthorized drones, allowing for swift and effective mitigation.

The Challenges for Conventional Radar in Detecting Drones

Since the 1930s, radar systems have been the principal means of detecting, locating, identifying and tracking aircraft in all weathers, day and night. However, many conventional air search radars are not capable of detecting drones accurately and reliably due to their low Radar Cross Section (RCS) – a measurement of how ‘visible’ a target is to a radar. 

Generally speaking, the larger the object, the larger the RCS and the easier it is for a radar to detect. Drones are available in a wide variety of shapes and sizes, but it is the smallest aircraft which can create the biggest problems for radar engineers due to their low RCS – often comparable to that of a bird. 

And to compound matters, drones are typically constructed from lightweight non-metallic materials like plastic or carbon fiber. These materials are poor conductors of electromagnetic RF signals and so reflect less RF energy to the radar, which effectively reduces the drone’s RCS further and makes it more difficult to detect.

Specialist Drone Detection CUAS Radar Systems

These engineering challenges have triggered a growing drone detection radar industry, with a raft of specialist suppliers developing cutting-edge radar solutions specifically optimized for drone detection applications.

Radar Technology, Processing Algorithms and AI

Drone detection radar systems use sophisticated radar target detection technologies such as Frequency Modulated Continuous Wave (FMCW) radar, Pulse-Doppler radar, and phased array radar, with advanced signal processing techniques such as waveform diversity and adaptive beamforming, and processing algorithms that often integrate the use of Artificial Intelligence (AI) and machine learning. 

AI techniques embedded in the drone detection radar’s software can be ‘trained’ to recognise ornithological flight characteristics and to ignore targets exhibiting these. Drones tend to follow straight, predictable patterns of flight, unlike birds, greatly helping detection.

Exploiting Micro-Doppler Shift for Drone Detection

Another drone detection technique involves exploiting micro-Doppler Shift. Doppler Shift occurs when the transmitted frequency of a radar signal rises or lowers after it collides with a target moving to or from the radar. The fast-moving blades of the drone’s rotors cause very small changes in the returned frequency of the signal. These frequencies rise and fall as the blades move towards and away from the radar.

As drones often have multiple rotors, the radar’s processor will detect several micro-Doppler Shifts caused by all these rotors. This multitude of infinitesimally small shifts lets the radar determine that the target is a drone and not a bird given that the Doppler Shift caused by flapping bird wings will be very different in their characteristics. Moreover, drone rotors are continually spinning whereas bird wings are not always flapping.

This combination of specialist radar detection technology and advanced, powerful signal processing enables drone detection radar systems to achieve superior drone detection accuracy while mitigating interference.

Drone Detection Radar in CUAS Defense Systems

A drone detection radar system is often integrated into a comprehensive CUAS defense solution, which features a suite of complementary Counter-Unmanned Aerial System technologies such as Electro-Optical and Infrared (EO/IR) Sensors, Radio Frequency (RF) Detection Systems, Acoustic Sensors and Electronic Countermeasures (ECM). These systems leverage the strengths of each component for enhanced situational awareness, improved threat assessment, and effective mitigation of drones.