Results 151 to 160 of about 3,720 (193)

Anti interference and fault tolerant control of UAVs integrating residual based diagnosis disturbance estimation with counter drone strategies. [PDF]

Sci Rep
Xie Z, Long Y.
europepmc   +1 more source

Real-Time jamming detection using windowing and hybrid machine learning models for pre-saturation alerts. [PDF]

Sci Rep
Sormayli J, Darvishi M, Zarrinnegar K, Mosavi MR.   +3 more
europepmc   +1 more source

DeepSpoofNet: a framework for securing UAVs against GPS spoofing attacks. [PDF]

PeerJ Comput Sci
Badar AUR, Mahmood D, Iqbal A, Kim SW, Akleylek S, Cengiz K, Nauman A.   +6 more
europepmc   +1 more source

Intelligent algorithmic framework for detection and mitigation of BeiDou spoofing attacks in vehicular ad hoc networks (VANETs). [PDF]

PeerJ Comput Sci
Tariq U.
europepmc   +1 more source

Combining Fast Orthogonal Search with Deep Learning to Improve Low-Cost IMU Signal Accuracy. [PDF]

Sensors (Basel)
Guan J, Mounier E, Iqbal U, Korenberg MJ.   +3 more
europepmc   +1 more source

GNSS Receiver Fingerprinting Based on Time Skew of Embedded CSAC Clock. [PDF]

Sensors (Basel)
Gui S, Dai L, Shi M, Wang J, Tang C, Wu H, Zhao J.   +6 more
europepmc   +1 more source

An Analysis of Spoofing Effects on a GNSS Receiver Using Real-Time GNSS Spoofing Simulator

Journal of Institute of Control, Robotics and Systems, 2013
In this paper, spoofing effects on a GNSS receiver were analyzed. The spoofer (spoofing device) was classified to two categories. One is an active spoofer and the other is a passive spoofer. The active spoofer was considered for analysis. For the analysis of spoofing effects on a GNSS receiver, a real-time GNSS spoofing simulator was developed.
Gyu-In Jee
exaly   +3 more sources