The Optimized Design of the Integrated Navigation Filter

Abstract

Since the raw pseudorange and pseudorange rate are taken as the measurements, the measurement equation of the tightly coupled SINS/GPS integrated navigation system is nonlinear. As a typical non-linear filtering algorithm, the Extended Kalman Filtering (EKF) linearizes the measurements and has high estimation accuracy in the tightly coupled SINS/GPS integrated navigation system. The state vector of the tightly coupled SINS/GPS integrated navigation system includes the states of two subsystems, therefore the dimension of the state vector is high. The dimension of the measurement vector depends on the number of received satellite signals. If many satellite signals are received, the dimension of the measurement vector is high. The high dimensions of the state vector and measurement vector will result in large computation load for the EKF. To solve this problem, this paper proposes an optimized filtering scheme based on the two-stage Kalman filtering and sequential Kalman filtering. In that case, the estimation accuracy is not seriously affected while the computation load is significantly reduced. The semi-physical simulation results prove the estimation accuracy of the proposed optimized filtering scheme.