IIT-Madras designs drones to counter 'rogue' ones

At a time when drones are being used for various purposes, the Indian Institute of Technology-Madras has developed an Artificial Intelligence-powered drone that can counter ‘rogue drones.’

This system can be of invaluable assistance to law enforcement agencies, security services and armed forces to secure air space over critical civilian and military installations from surveillance by rogue drones.

It can track down rogue drones visually, hack into their GPS navigation system, following which the target drone is forced to change its flight path or land safely. A major advantage of this system is that it can be controlled over the Internet and can navigate autonomously as compared to most existing drones that operate on ‘line of sight', meaning the operator must keep the drone within their sight.

Using the Internet to control the drones also allows deploying a swarm of drones that can intelligently detect and track people, drones, vehicles and other objects.
This system was designed by a team comprising Vasu Gupta, a final year B. Tech student, Department of Aerospace Engineering, IIT Madras, and Rishabh Vashistha, a Project Associate working in RAFT Lab, Department of Aerospace Engineering, IIT Madras.

The Team was mentored by Dr. Ranjith Mohan, Assistant Professor, Department of Aerospace Engineering, IIT Madras.

Highlighting the unique aspects of this system, Dr Mohan, Assistant Professor, Department of Aerospace Engineering, in a press statement, said: “Our current prototype is equipped to detect and track objects visually, precisely land and fly over Internet. Our next step will be to conduct exhaustive tests on the system and ensure its reliability for catering to a wide range of demanding missions that pose challenge to our law enforcement and defence agencies. The programmable nature of our aerial vehicles also opens up the possibility of swarming multiple vehicles to act as a team and accomplish a common mission.”

The researchers designed a visual-based tracking system using Deep Neural Networks (Artificial Intelligence) to secure airspaces and land stretches efficiently by employing a swarm of drones.

The motion detection algorithms are powered by AI and can detect motion even in dark conditions without the need of an IR (infrared) camera.

The drone works by employing a software-defined radio and broadcasting spoofed GPS signals by making use of the ephemeris data of GNSS constellations. The target drone’s GPS sensor locks onto the fake radio station transmitting at a much higher power than the available satellite’s transmission power.

Following this, the drone generates fake GPS packets by mathematically modelling the time differences at the receiver’s end. Using four of such time differences, the GPS sensor calculates its 3D position and calibrates the rogue drones’ time to the spoofed clock. This way, they alter the latitude, longitude, altitude and time of the rogue drones.

Algorithmically altering the 3D position allows them to move the target drone locally. Moreover, when a large variance is given in the spoofed GPS position, a failsafe (if any) is invoked at the target side which results in a safe landing of the target drone.

“We have tested this electronic countermeasure of ours against nearly all the civilian GPS receivers used by the UAV industry such as ublox, DJI inhouse GNSS and we have been able to take down the drones almost instantaneously (within 4-5 seconds)," the statement said quoting the researchers.