A GNSS/INS Vehicle Integrated Navigation System Based on LSTM-EKF

Integration of GNSS and INS can provide continuous and accurate positioning information for vehicles. However, the accuracy of low-cost GNSS/INS vehicle integrated navigation systems is unreliable during GNSS outages, which are common in urban areas. So, a long and short-term memory (LSTM) networks-aided GNSS/INS integrated navigation system based on extended Kalman filter (EKF) is proposed in this paper. LSTM networks are trained to learn the relationship between position error and INS output when GNSS available. When GNSS outage occurs, LSTM networks predict and correct errors of the integrated navigation system to improve location precision. The experiment shows that the north error and east error of the GNSS/INS integrated navigation systems based on EKF is 1.93m and 13.92m during the 15s GNSS outage. Meanwhile, the north error and east error of the GNSS/INS integrated navigation systems based on LSTM-EKF is 1.17m and 0.84m. The comparison results indicate that the proposed system can effectively improve location precision during GNSS outages.