Interval Estimation of Unmanned Underwater Vehicle State and Fault based on Zonotopic Kalman Filter

This paper investigates a method for interval estimation of the UUV state and fault in the presence of external disturbances and noise that are unknown but bounded. An augmented descriptor system is constructed by incorporating sensor faults into the system state, thereby enabling a unified estimation framework. According to this augmented system, this paper proposes a method of generating bounds for both sensor state and fault based on the zonotopic Kalman filter. Furthermore, a gain optimization strategy based on Frobenius norm minimization is introduced to enhance the compactness of the estimated intervals. Finally, the effectiveness of the proposed method is validated through pool experiments.