Jellyfish: non-radio frequency counter drone technology

Peng Zhang; Lance Lowenberg; Michael Tall; Michael Ouimet

doi:10.1117/12.2563637

23 April 2020 Jellyfish: non-radio frequency counter drone technology

Peng Zhang, Lance Lowenberg, Michael Tall, Michael Ouimet

Proceedings Volume 11425, Unmanned Systems Technology XXII; 114250E (2020) https://doi.org/10.1117/12.2563637
Event: SPIE Defense + Commercial Sensing, 2020, Online Only

Abstract

In contrast of RF jamming devices for counter-UAV measure, which proves ineffective for autonomous UAV, we propose Jellyfish - a vision-based and machine learning driven defensive approach using inexpensive drones. Jellyfish minimizes cost while maximizing the effectiveness of countering autonomous UAV threats. In software aspect, we collect synthetic and real-world imagery and train deep learning model for real-time adversarial drone detection and tracking and then feed tracking output to a highly responsive controller to mirror the movement of the adversary. On the other hand, we design a lightweight and self-releasable capturing mechanism, similar to the tentacles of a jellyfish (hence the name “Jellyfish"), to optimize both the capturing area and defending drone's maneuverability and survivability.

Citation Download Citation

Peng Zhang, Lance Lowenberg, Michael Tall, and Michael Ouimet "Jellyfish: non-radio frequency counter drone technology", Proc. SPIE 11425, Unmanned Systems Technology XXII, 114250E (23 April 2020); https://doi.org/10.1117/12.2563637

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available