On Designing PMI Kalman Filter for INS/GPS Integrated Systems With Unknown Sensor Errors

Abstract

In this paper, a Kalman filter with proportional gain and multiintegral (PMI) gains is proposed to inertial navigation system (INS) and global positioning system (GPS) integration. A generalized fault is first introduced to represent the unexpected inertial sensors' biases resulted by environment condition changes or performance degradation of INS. Then, a linear time-varying system subject to fault is given to describe the dynamics of the INS/GPS integrated system. To achieve simultaneous estimation of navigation state and inertial sensors' biases, a PMI Kalman filter is developed in the framework of active fault tolerant filtering. Furthermore, a flight experiment is also given to illustrate the effectiveness of the proposed method. It is shown from the experimental results that the designed PMI Kalman filter can estimate biases more accurately than the traditional Kalman filter.