An improved Sage-Husa adaptive filtering algorithm

In order to meet the requirement of precision and stability, a new method is proposed which uses fading factor and innovation threshold to estimate noise covariance matrix and modify the observation error covariance matrix dynamically. This algorithm was used to the GPS/INS integrated navigation system and compared with the simplified Sage-Husa filtering. The simulation results show that the improved Sage-Husa self-adaptive filtering algorithm, which makes the process better both in the precision and stability, is superior to the simplified Sage-Husa filtering.