Chong, Yu Quan (National University of Singapore), Ong, Edmond (National University of Singapore), Srigrarom, Sutthiphong (National University of Singapore)

Identification of Drone Thermal Signature by convolutional neural network

Scheduled for presentation during the Regular Session "Learning Methods I" (WeA2), Wednesday, June 16, 2021, 10:50−11:10, Kozani

2021 International Conference on Unmanned Aircraft Systems (ICUAS), June 15-18, 2021, Athens, Greece

This information is tentative and subject to change. Compiled on April 25, 2024

Abstract

This paper presents the work on drone detection and identification by using thermal infrared emission for night operation. Through both indoor and outdoor trials, the characteristics of the thermal signature emitted by a drone when captured by a drone detection system is examined, and their implications on a machine learning problem are studied. Thermal maps are processed through a transfer learning using YOLOv3 based CNN model to detect and generate a bounding box around the thermal signature of the drone. The presented approach also seeks to utilise the characteristics of drone motion for more effective drone detection through machine learning.