Resilient state estimation for nonlinear systems: A binary encoding scheme under stochastic bit flips

Abstract

This article deals with the state estimation problem for a class of time-varying systems subject to stochastic nonlinearities and channel noise over sensor networks. A binary encoding scheme (BES) is employed in the filter design to overcome distortions caused by the limited communication capacity. In addition, stochastic perturbations are introduced into the filter gain to characterize the resilience of the filter. Measurements are transmitted as bit strings over a binary symmetric channel, taking into account the stochastic bit flips. An upper bound of estimation error covariance is derived with the help of the inductive approach, and such an upper bound is subsequently minimized to design the filter parameters at each time instant. Finally, a numerical example is employed to confirm the effectiveness of the proposed approach.