Application of AUKF in GNSS/INS Integrated Navigation
Kaixin Luo, Fan Ying · CSAA/IET International Conference on Aircraft Utility Systems (AUS 2018) · 2018
The integration of Global Navigation Satellite System (GNSS) and Inertial Navigation System (INS) integrate the complementary characteristics of the two systems. When the GNSS signal is outage, the INS can work alone to maintain the continuous output. Unscented Kalman Filter (UKF) is the most common means for data fusion in integrated navigation systems. However, the standard UKF will be deteriorated or even divergent if the statistic of system noise are unknown or inaccurate. A novel adaptive UKF (AUKF) with noise statistic estimator has been chosen in this paper for improving the filtering accuracy of integrated navigation systems. In the proposed algorithm, we need to find out the innovation and residual sequences, estimate and adjust the covariance matrices of the process and measurement noises online according to the covariance matching technique. Thus, we can improve the filter effect, reduce the error, and improve the precision of integrated navigation system.