8 citations · 36 across the 12 of their papers we have counts for
14 papers · 1 filter
A Survey on Detection, Classification, and Tracking of UAVs using Radar and Communications Systems
Wahab Khawaja, Martins Ezuma, Vasilii Semkin +3
The use of unmanned aerial vehicles (UAVs) for a variety of commercial, civilian, and defense applications has increased many folds in recent years. While UAVs are expected to tran…
A Survey on Detection, Tracking, and Classification of Aerial Threats using Radars and Communications Systems
Wahab Khawaja, Martins Ezuma, Vasilii Semkin +3
The use of unmanned aerial vehicles (UAVs) for different applications has increased many folds in recent years. The UAVs are expected to change the future air operations. However,…
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…
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…
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…
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…
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…
FPGA prototyping of synchronized chaotic map for UAV secure communication
Christian Nwachioma, Martins Ezuma, Olusiji . O. Medaiyese
We propose a design that uses the principle of chaos for UAV secure communication. A UAV identified as an aerial base station communicates with a ground base station over an RF cha…
Compact-Range RCS Measurements and Modeling of Small Drones at 15 GHz and 25 GHz
Martins Ezuma, Mark Funderburk, Ismail Guvenc
The knowledge of the radar signature of aerial targets, such as drones, is critical in designing an effective radar detection system. It is a challenging task to measure the radar…
Detection and Classification of UAVs Using RF Fingerprints in the Presence of Interference
Martins Ezuma, Fatih Erden, Chethan Kumar Anjinappa +2
This paper investigates the problem of detection and classification of unmanned aerial vehicles (UAVs) in the presence of wireless interference signals using a passive radio freque…
Micro-UAV Detection with a Low-Grazing Angle Millimeter Wave Radar
Martins Ezuma, Ozgur Ozdemir, Chethan Kumar Anjinappa +2
Millimeter wave radars are popularly used in last-mile radar-based defense systems. Detection of low-altitude airborne target using these radars at low-grazing angles is an importa…
Micro-UAV Detection and Classification from RF Fingerprints Using Machine Learning Techniques
Martins Ezuma, Fatih Erden, Chethan Kumar Anjinappa +2
This paper focuses on the detection and classification of micro-unmanned aerial vehicles (UAVs) using radio frequency (RF) fingerprints of the signals transmitted from the controll…
Effect of Passive Reflectors for Enhancing Coverage of 28 GHz mmWave Systems in an Outdoor Setting
Wahab Ali Gulzar Khawaja, Ozgur Ozdemir, Fatih Erden +3
The availability of large unused spectrum at millimeter wave (mmWave) frequency bands has steered the future 5G research towards these bands. However, mmWave signals are attenuated…
Indoor Coverage Enhancement for mmWave Systems with Passive Reflectors: Measurements and Ray Tracing Simulations
Wahab Khawaja, Ozgur Ozdemir, Yavuz Yapici +3
The future 5G networks are expected to use millimeter wave (mmWave) frequency bands, mainly due to the availability of large unused spectrum. However, due to high path loss at mmWa…