INS/BDS integrated navigation filter algorithm based on Unscented Kalman Filter

Abstract

The inertial navigation system (INS) can continuously provide position information, with high precision in short time, but the positioning error accumulates over time. The BeiDou navigation satellite system (BDS) has long term stability, but susceptible to interference, data update frequency is low. INS and BDS constitute the integrated navigation system, it can learn from each other. In this paper, the INS/BDS tightly integrated navigation method is described, and the algorithm steps and characteristics of Unscented Kalman Filter (UKF) are introduced in details. The mathematical model of the integrated navigation system was established, and the error equation of the integrated navigation system was deduced, the application of unscented Kalman filter in INS/BDS tightly integrated navigation was studied, and compared with Extended Kalman Filter (EKF) algorithm. The experimental results showed that UKF filter can provide higher filtering accuracy than EKF in INS/BDS tight combination.