Outlier-resistant sequential filtering fusion for cyber-physical systems with quantized measurements under denial-of-service attacks

Abstract

In this paper, an outlier-resistant sequential fusion problem is concerned for cyber-physical systems with quantized measurements under denial-of-service attacks. The multi-sensor measurements are quantized by a bank of logarithmic quantizers before entering into communication networks. The denial-of-service attack is, from the defenders' perspective, regarded to be randomly occurring and such an occurrence is governed by a Bernoulli-distributed sequence of certain probability distribution. To suppress effects from measurement outliers onto innovations, tailored saturation functions are dedicatedly introduced to filter structures at both local and fusion stages, thereby keeping satisfactory fusion performance. By finding solutions to a set of matrix difference equations, upper bounds are initially acquired on estimator error covariances, and associated estimator parameters are subsequently secured via minimizing these acquired bounds. Two examples are finally presented to showcase the applicability of this outlier-resistant sequential fusion algorithm.