activity
20182025
most citedComparative Analysis of Radar Cross Section Based UAV Classification Techniques

8 citations · 15 across the 8 of their papers we have counts for

collaborators
Showing 2021Show all

5 papers · 1 filter

eess.SP2021★ 8 cited

Comparative Analysis of Radar Cross Section Based UAV Classification Techniques

Martins Ezuma, Chethan Kumar Anjinappa, Vasilii Semkin +1

This work investigates the problem of unmanned aerial vehicles (UAVs) identification using their radar crosssection (RCS) signature. The RCS of six commercial UAVs are measured at…

eess.SP2021

Hierarchical Learning Framework for UAV Detection and Identification

Olusiji O Medaiyese, Martins Ezuma, Adrian P Lauf +1

The ubiquity of unmanned aerial vehicles (UAVs) or drones is posing both security and safety risks to the public as UAVs are now used for cybercrimes. To mitigate these risks, it i…

eess.SP2021

Semi-supervised Learning Framework for UAV Detection

Olusiji O Medaiyese, Martins Ezuma, Adrian P Lauf +1

The use of supervised learning with various sensing techniques such as audio, visual imaging, thermal sensing, RADAR, and radio frequency (RF) have been widely applied in the detec…

eess.SP2021

Radar Cross Section Based Statistical Recognition of UAVs at Microwave Frequencies

Martins Ezuma, Chethan Kumar Anjinappa, Mark Funderburk +1

This paper presents a radar cross-section (RCS)-based statistical recognition system for identifying/ classifying unmanned aerial vehicles (UAVs) at microwave frequencies. First, t…

eess.SP2021

Wavelet Transform Analytics for RF-Based UAV Detection and Identification System Using Machine Learning

Olusiji Medaiyese, Martins Ezuma, Adrian P. Lauf +1

In this work, we performed a thorough comparative analysis on a radio frequency (RF) based drone detection and identification system (DDI) under wireless interference, such as WiFi…