Robust state estimation based on statistical similarity measure with sliding window for non-Gaussian systems under multiple cyber attacks

• Published in: Journal of the Franklin Institute Vol. 362; no. 15; p. 107971
• Main Authors: Wang, Guoqing, Zhu, Zhaolei, Yang, Chunyu, Rong, Wanting, Ma, Lei
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.10.2025
• Subjects: Cyber attacks; Robust Kalman filter; Sliding window; Statistical similarity measure; Student’s t kernel function; Variational Bayesian; Variational Bayesian; Cyber attacks; Robust Kalman filter; Statistical similarity measure; Sliding window; Student’s t kernel function

This work proposes a robust and resilient state estimation framework for non-Gaussian systems under multiple cyber attacks, where the inputs and measurements are both threatened by random deception attacks with unknown probabilities. Motivated by the fact that existing robust estimation algorithms s...