New Kalman Filtering Algorithm for Passive-BD/SINS Integrated Navigation System Based on UKF

One of the disadvantages of passive-BD navigation system is that the pseudo-range error from its receiver is significant and difficult to be modeled. Therefore, passive-BD/SINS integrated navigation system using traditional indirect Kalman filtering method can not achieve high positioning accuracy and costs too much calculating time. This study optimizes the filtering algorithm for integrated system with the shortcomings of BD system such as limited satellite number and fixed satellite position. An improved filtering algorithm based on Unscented Kalman Filter (UKF) is proposed after comparing the advantages and disadvantages of the traditional direct filtering method, the Extended Kalman (EKF) filtering method, and the UKF. The main feature of our new algorithm is that it requires no accurate error models and can effectively solve the nonlinear problem of the system state equation. The theoretical and experimental results show that our algorithm can improve the positioning accuracy and simplify the adjustment process of filtering parameters to reduce the total calculating time. Besides, our algorithm has many practical values to the further study of filtering algorithm for other integrated navigation systems.