Acoustic AI Drone Detection Technology
Airspeed Electronics Ltd is an electronic design consultancy based in the United Kingdom. We specialise in designing high-reliability embedded systems for operation in demanding environments. We are currently developing a drone detection and tracking system called MANTIS. This work is being funded through a research grant provided by the UK Ministry of Defence.
MANTIS (MAchine learNing acousTIc Surveillance) is a system of distributed, intelligent acoustic sensors which use Artificial Intelligence methods for detection, classification and location estimation of drones and UAS, based on their acoustic signature.
The system offers wide-area deployment in complex environments, full 360⁰ tracking of multiple targets and ‘24/7’ autonomous operation. It can be used as a standalone system or integrated into layered Counter-UAS systems by connecting to common data interfaces.
We expect to have an operational system demonstrator by the end of 2020
Drones are difficult to detect
Small drones can be difficult to detect. RF sensors, such as RADAR may struggle due to the small physical size of the drone, and due to the use of RF transparent materials in their construction (e.g. plastics). In order for a RADAR to ‘see’ a small commercial drone requires the use of high frequencies, such as X-Band or higher (i.e. > 7 GHz). However, radio waves at such high frequencies are attenuated by rain, fog and smoke, which limits the effective range of the sensor. Low level objects such as trees and buildings can also generate clutter in the reflected RADAR signal. Under certain conditions, Electro-Optic (EO) sensors, such as cameras, also have performance limitations due to atmospheric conditions and ambient light levels.
The performance limitations in the sensing technology expose some vulnerabilities in existing counter drone systems. An aggressor may choose to exploit these vulnerabilities by flying at very low level, through ‘urban canyons’ or at night. C-UAS systems which use radiated telemetry emissions from the drone or drone pilot to locate the target drone may also soon become obsolete due to greater use of autonomy, allowing the UAS to complete its mission in ‘radio silence’.
Acoustic sensors can be made to work well for drone detection and tracking in situations where RF and EO sensors do not perform. A robust drone detection and tracking system could be built, which combines the capabilities of a RF or EO sensor with an acoustic sensing system, such as MANTIS. Some existing commercial systems have adopted this approach. It is clear, however, that of these existing systems, the best in class are limited to small-scale ‘point defence’ deployments and require a man-in-the-loop to operate. The proposed MANTIS system offers wide-area deployment in complex environments, full 360⁰ tracking of multiple targets and ‘24/7’ autonomous operation. It would therefore offer a step improvement in system performance.