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This paper presents a detection algorithm for sensor attacks and a resilientstate estimation scheme for a class of uniformly observable nonlinear systems.An adversary is supposed to corrupt a subset of sensors with the possiblyunbounded signals, while the system has sensor redundancy. We design anindividual high-gain observer for each measurement output so that only theobservable portion of the system state is obtained. Then, a nonlinear errorcorrecting problem is solved by collecting all the information from thosepartial observers and exploiting redundancy. A computationally efficient,on-line monitoring scheme is presented for attack detection. Based on theattack detection scheme, an algorithm for resilient state estimation isprovided. The simulation results demonstrate the effectiveness of the proposedalgorithm.

Detection of Sensor Attack and Resilient State Estimation for Uniformly Observable Nonlinear Systems having Redundant Sensors