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Dynamic state estimation in the presence of compromised sensory data

Nakahira, Yorie and Mo, Yilin (2015) Dynamic state estimation in the presence of compromised sensory data. In: 54th IEEE Conference on Decision and Control (CDC). IEEE , Piscataway, NJ, pp. 5808-5813. ISBN 978-1-4799-7884-7. http://resolver.caltech.edu/CaltechAUTHORS:20160217-090514485

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Abstract

In this article, we consider the state estimation problem of a linear time invariant system in adversarial environment. We assume that the process noise and measurement noise of the system are l∞ functions. The adversary compromises at most γ sensors, the set of which is unknown to the estimation algorithm, and can change their measurements arbitrarily. We first prove that if after removing a set of 2γ sensors, the system is undetectable, then there exists a destabilizing noise process and attacker's input to render the estimation error unbounded. For the case that the system remains detectable after removing an arbitrary set of 2γ sensors, we construct a resilient estimator and provide an upper bound on the l∞ norm of the estimation error. Finally, a numerical example is provided to illustrate the effectiveness of the proposed estimator design.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1109/CDC.2015.7403132 DOIArticle
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7403132&isnumber=7402066PublisherArticle
Additional Information:© 2015 IEEE. This paper is supported in part by TerraSwarm, one of six centers of STARnet, a Semiconductor Research Corporation program sponsored by MARCO and DARPA.
Funders:
Funding AgencyGrant Number
Semiconductor Research CorporationUNSPECIFIED
Microelectronics Advanced Research Corporation (MARCO)UNSPECIFIED
Defense Advanced Research Projects Agency (DARPA)UNSPECIFIED
Record Number:CaltechAUTHORS:20160217-090514485
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20160217-090514485
Official Citation:Nakahira, Yorie; Mo, Yilin, "Dynamic state estimation in the presence of compromised sensory data," in Decision and Control (CDC), 2015 IEEE 54th Annual Conference on , vol., no., pp.5808-5813, 15-18 Dec. 2015 doi: 10.1109/CDC.2015.7403132
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:64527
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:17 Feb 2016 18:43
Last Modified:17 Feb 2016 18:43

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