PMI based fault estimation for linear time-varying systems

In this paper, a Kalman filter with proportional gain and multi-integral gains (PMI Kalman filter) is first proposed for linear time-varying systems. After considering the unknown deterministic errors in inertial measurement unit (IMU) as faults, the designed PMI Kalman filter is applied to a Strapdown Inertial Navigation System/Global Positioning System (SINS/GPS) integrated measurement system. As a result, a simultaneous estimation of position, velocity, orientation and bias errors of inertial sensors is achieved. Furthermore, a flight experiment is also given to illustrate the effectiveness of the proposed method. It is shown by the experiment results that the designed PMI Kalman filter can estimate fault accurately than the existed Kalman filter with only proportional gain.