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Accession Number ADA585155
Title System State Estimation in the Presence of False Information Injection.
Publication Date 2012
Media Count 5p
Personal Author L. Huie R. Niu
Abstract The problem of system state estimation in the presence of an adversary is investigated for linear dynamic systems. It is assumed that the adversary injects additive false information into the sensor measurement. The impact of the false information on the Kalman filter s estimation performance is analyzed for a general dynamic system. To be concrete, a target tracking system has been used as an example. In such a system, if the false information is injected only once, the effect of the false information on the Kalman filter proves to be diminishing over time, even when the Kalman filter is unaware of the false information injection. The convergence rate as a function of the maneuvering index is analyzed. If the false information is repeatedly injected into the system, the induced estimation error proves to reach a finite steady state. Numerical examples are presented to support the theoretical results.
Keywords Convergence
False information
Kalman filtering
Linear systems
Numerical analysis

Source Agency Non Paid ADAS
NTIS Subject Category 72F - Statistical Analysis
Corporate Author Air Force Research Lab., Rome, NY. Information Dir.
Document Type Technical report
Title Note Conference paper.
NTIS Issue Number 1403
Contract Number N/A

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