Theshani Nuradha, Kasun T. Hemachandra, Tharaka Samarasinghe, Sachille Atapattu
Conference
GLOBECOM 2019 IEEE Globecom Workshops (GC Wkshps) , pp. 1-6 · 2019 · Cited by 16
Wireless CommunicationsCommunication Theory and CodingUAVs and Aerial Robotics
Abstract
The paper considers physical layer security (PLS) of an untrusted unmanned aerial vehicle (UAV) network, where a multitude of UAVs communicate in full-duplex (FD) mode. A source-based jamming (SBJ) scheme is exploited for secure communication without utilizing any external jammers. Firstly, the optimal power allocation between the confidential signal and the jamming signal is derived to maximize the secrecy rate of each link between the source and the destination. Then, the best UAV selection scheme is proposed to maximize the overall secrecy rate of the network. The corresponding secrecy outage probability (SOP) and the average secrecy rate (ASR) of the network are analyzed based on the proposed UAV selection and the optimal power allocation schemes. Asymptotic results are also obtained to derive the achievable diversity order. Results are validated through numerical evaluations while …
Tharindu S Chathuranga, Rohan Munasinghe
Conference
MERCon 2019 Moratuwa Engineering Research Conference (MERCon) , pp. 633-637 · 2019 · Cited by 5
Computer VisionUAVs and Aerial RoboticsMobile Robotics and Navigation
Abstract
This paper presents a method for localizing an Unmanned Aerial Vehicle (UAV) using geo-referenced aerial images, in case of GPS failure. When flying in urban environments in low altitudes the inaccurate GPS localization has become a major problem. The proposed method fuses measurements from inertial sensors and visual odometer and perform image registration process using the images captured by the onboard down looking camera. A pre-built local orthomosaic map with geotagged aerial images is used for the registration. The problem of unreliable matches caused by the dynamic objects is addressed in our approach. The experiment results show that it is possible to localize the UAV in urban environments with a low margin of error by using our method.