Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Ezuma, Martins"'
Autor:
Khawaja, Wahab, Ezuma, Martins, Semkin, Vasilii, Erden, Fatih, Ozdemir, Ozgur, Guvenc, Ismail
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 transform future air operations, there are instances where they can be use
Externí odkaz:
http://arxiv.org/abs/2402.05909
Autor:
Khawaja, Wahab, Ezuma, Martins, Semkin, Vasilii, Erden, Fatih, Ozdemir, Ozgur, Guvenc, Ismail
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, there are instances where the UAVs can be used for malicious purposes.
Externí odkaz:
http://arxiv.org/abs/2211.10038
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 15 GHz and 25 GHz in an anechoic chamber, for both vertical-vertical a
Externí odkaz:
http://arxiv.org/abs/2112.09774
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 is important to have a system that can detect or identify the presence
Externí odkaz:
http://arxiv.org/abs/2107.04908
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 detection of unmanned aerial vehicles (UAV) in an environment. However, lit
Externí odkaz:
http://arxiv.org/abs/2104.06614
This paper presents a radar cross-section (RCS)-based statistical recognition system for identifying/ classifying unmanned aerial vehicles (UAVs) at microwave frequencies. First, the paper presents the results of the vertical (VV) and horizontal (HH)
Externí odkaz:
http://arxiv.org/abs/2102.11954
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 and Bluetooth, by using machine learning algorithms, and a pre-traine
Externí odkaz:
http://arxiv.org/abs/2102.11894
Publikováno v:
2021 IEEE Aerospace Conference
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 channel. The communication units have dynamics based on the logistic map.
Externí odkaz:
http://arxiv.org/abs/2101.03880
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 cross-section (RCS) of small drones. This paper describes a compact-ra
Externí odkaz:
http://arxiv.org/abs/1911.05926
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 frequency (RF) surveillance system. The system uses a multistage detector to
Externí odkaz:
http://arxiv.org/abs/1909.05429