IIT Madras team develops AI-powered drone to counter rogue drones – Business Standard

Researchers at IIT Madras have developed an artificial intelligence (AI)-powered drone that can counter ‘Rogue Drones.’

This system can help law enforcement agencies, security services and armed forces secure airspace over critical civilian and military installations from surveillance by rogue drones.

The drone can track down rogue drones visually and hack into their GPS navigation system, following which the target drone is forced to change its flight path or land safely.

According to IIT, 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 that the operators need to keep the drone within their sight. Using the Internet to control the drones also allows for deploying a swarm of drones that can intelligently detect and track people, drones, vehicles and other objects.

The new system was designed by a team comprising Vasu Gupta, a final year B Tech student, Department of Aerospace Engineering, and Rishabh Vashistha, a Project Associate working in RAFT Lab, Department of Aerospace Engineering. The team was mentored by Dr Ranjith Mohan, Assistant Professor, Department of Aerospace Engineering.

Highlighting the unique aspects of this system, Dr Ranjith Mohan 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 the visual-based tracking system using deep neural networks (AI) to secure airspace 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.

Gupta said, “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 our 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 our spoofed clock. This way, we alter the latitude, longitude, altitude and time of the rogue drones.”

“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),” he said.

The team used an advance version of kernelised correlation filters for tracking objects once they are detected and locked onto. Such tracking features work on visual sensors like cameras and CMOS without using radars and sonars, the latter of which generally do not provide much informative data.