Automated drone detection and targeting system

Project Title

Automated drone detection and targeting system

Project Area of Specialization RoboticsProject Summary

Drones have undergone tremendous development in recent years. Although they can be used for the betterment of the society, they can also be used by malicious entities to conduct physical and cyber-attacks to infrastructure, private/public property, and people. Their great agility commences new threats in security and public privacy. The small size makes it effortless to perform challenging missions very precisely. The radar system provides good capabilities at long ranges but the limitation to these systems is their inability to sense smaller and slower aircrafts flying at lower altitudes. Therefore, the aim of this project is to develop an integrated real-time drone detection system that can detect an Unmanned Aerial Vehicle(UAV) based on Real-time frequency monitoring for all frequencies and coordinates ( Heading, Height) at the same time and interpret the images of it in terms of polar coordinates. Initially, neural networks will be used to train the detection and tracking algorithm. As a result the trained  algorithms will be tested and validated for real-time drones infiltration scenarios The proposed system develops a model which detects a UAV that attempts to trespass the secured territory at low altitude, providing its precise location, calculating the distance and targeting the UAV.

Project Objectives

The core objectives of this project include:

• Efficient detection of a low altitude flying drone and its location using the input sensors and image processing.
• Development of neural network-based system to monitor and interpret the data acquired from input sensors.
• Visualization of the target in polar coordinates with a 360 coverage in software platform.
• Development of a prototype which will have the ability to target the detected drone in the vicinity.
• Electronic Jamming System to cut off Drone wireless telemetry(optional).

Project Implementation Method

The internal architecture of the proposed model will work on these four basic step

1. Detection

 This phase of the project handles the capturing of image through several cameras. Once we have the image we will only detect the aerial objects.

       2. Identification

Once we have detected the aerial objects in an image, we will further proceed towards the identification of the UAV’s from other flying objects.

      3. Tracking

As we have distinguished the UAV from other aerial objects we can then track the movement of the target trespassing the premises.

   4. Targeting

The last stage includes the targeting of the UAV through a mock laser system.

Benefits of the Project

Benefitis of the project are as folllows

• Security
• Surveillance
• Visiual and sound detection
• Low altitude drone detection
• Low cost
• Portable

Technical Details of Final Deliverable

Final deliverable consists of a trained model which can detect UAV in low range, which will be displayed on real time monitoring screen. This will help the user to identify and target the threat with the help of this system. Key deliverable are as follows:

• Efficient detection.
• Considerable Frame per second.
• Latitude and longitude acquisition.
•  Noise from acaustic input to indentify UAV.

Final Deliverable of the Project HW/SW integrated systemCore Industry ITOther Industries Security Core Technology RoboticsOther Technologies Artificial Intelligence(AI)Sustainable Development Goals Industry, Innovation and InfrastructureRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	71000
Cameras	Equipment	4	5000	20000
Acoustic Sensors	Equipment	10	200	2000
GPU unit	Equipment	1	35000	35000
Screen	Equipment	1	4000	4000
Stands	Equipment	4	1500	6000
Cables/wires	Equipment	20	100	2000
Miscellaneous	Miscellaneous	1	2000	2000