Loading [a11y]/accessibility-menu.js
System state estimation in the presence of false information injection | IEEE Conference Publication | IEEE Xplore

System state estimation in the presence of false information injection


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...Show More

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.
Date of Conference: 05-08 August 2012
Date Added to IEEE Xplore: 04 October 2012
ISBN Information:
Print ISSN: 2373-0803
Conference Location: Ann Arbor, MI, USA

Contact IEEE to Subscribe

References

References is not available for this document.