Dynamic state estimation in the presence of compromised sensory data
- Creators
- Nakahira, Yorie
- Mo, Yilin
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.
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.Additional details
- Eprint ID
- 64527
- Resolver ID
- CaltechAUTHORS:20160217-090514485
- Semiconductor Research Corporation
- Microelectronics Advanced Research Corporation (MARCO)
- Defense Advanced Research Projects Agency (DARPA)
- Created
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2016-02-17Created from EPrint's datestamp field
- Updated
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2021-11-10Created from EPrint's last_modified field