NDLI: Trust aware particle filters for autonomous vehicles

Content Provider	IEEE Xplore Digital Library
Author	Basciftci, Y.O. Ozguner, F.
Copyright Year	2012
Description	Author affiliation: Department of Electrical and Computer Engineering, The Ohio State University, Columbus, 43210 USA (Basciftci, Y.O.; Ozguner, F.)
Abstract	Cyber-Physical Systems have been widely employed in safety critical applications including intelligent highways, autonomous vehicles and robotic systems. State estimation is crucial for Cyber-Physical Systems because control commands that are sent to physical systems depend on the estimated states. The particle filter is a good candidate for state estimation due to its applicability to nonlinear and/or non-Gaussian dynamic systems. However, classical particle filters are not robust against false data injection from sensors compromised by attackers. In this paper, we propose a novel particle filter algorithm, trust aware particle filter, that is robust to false data injection attacks. We develop a framework in which a state estimator assigns trust values to sensors based on the measurements and we utilize the trust values in the state estimation. Simulation results demonstrate the robustness of the trust aware particle filter in the presence of false data injection attacks.
Starting Page	50
Ending Page	54
File Size	354330
Page Count	5
File Format	PDF
ISBN	9781467309929
e-ISBN	9781467309936
DOI	10.1109/ICVES.2012.6294259
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-24
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Atmospheric measurements Noise Sensor fusion Particle measurements Robustness State estimation
Content Type	Text
Resource Type	Article

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