@inproceedings{81154d0075d14a57abb7bad03273db70,
title = "Experimental analysis of micro-Doppler characteristics of drones and birds for classification purposes",
abstract = "This paper investigates the use of micro-Doppler signatures of drones and birds for their detection and classification. Assessments made from simulated results are verified by data collected using a 10-GHz continuous wave (CW) radar system. Time/Velocity spectrograms generated for micro-Doppler analysis of multiple drones and birds are used for target identification and movement classification within TensorFlow. Results using Support Vector Machine (SVM) indicate 96% accuracy for drones vs. birds and 85% accuracy among individual drone and bird distinction between 5 classes.",
author = "Bryan Tsang and Narayanan, {Ram M.} and Ramesh Bharadwaj",
note = "Publisher Copyright: {\textcopyright} COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.; Radar Sensor Technology XXVI 2022 ; Conference date: 06-06-2022 Through 12-06-2022",
year = "2022",
doi = "10.1117/12.2622408",
language = "English (US)",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Ranney, {Kenneth I.} and Raynal, {Ann M.}",
booktitle = "Radar Sensor Technology XXVI",
address = "United States",
}