A Framework of Cubature-<italic>H&#x1D62;/H_&#x221E;</italic> -Fault Detection and Robust H-Infinity Kalman Filter of Ship SINS/GNSS Integrated System

Abstract

xThis article deals with the problem of considering both robust fault detection and accurate state estimation for a strapdown inertial navigation system and global navigation satellite system (SINS/GNSS)-integrated navigation system for ships within a unified framework. Under the assumption that the process disturbance and measurement noise being ℓ2-norm bounded, a cubature Hi/H∞ fault detection filter (FDF) considering both sensitivity and robustness to disturbance is proposed to detect faults with a postfilter and an observer gain. However, the estimated state value of the above algorithm is theoretically a suboptimal solution. To solve this limitation, an adaptive algorithm based on the measurement residual and a scaling factor is proposed to improve the accuracy of state estimation in the proposed cubature Hi/H∞ FDF. To guarantee stability when faults are extremely large, the framework uses a robust H-infinity cubature Kalman filter. Finally, a simulation is implemented to demonstrate the effectiveness of the proposed method, considering the threshold selection for different cases.

Keywords

• SINS/GNSS-integrated navigation on ships
• cubature Kalman filter (CKF)
• Hᵢ/H∞ fault detection filter (FDF)%22%2C%22default_operator%22%3A%22AND%22%7D%7D%7D"> <italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">Hᵢ/H∞</italic> fault detection filter (FDF)
• adaptive algorithm
• H-infinity robust filter