Information Fusion Based on Complementary Filter for SINS/CNS/GPS Integrated Navigation System of Aerospace Plane

• Main Authors: Yanming Zhao, Gongmin Yan, Yongyuan Qin, Qiangwen Fu
• Format: Article
• Language: English
• Published: MDPI AG 2020-12-01
• Series: Sensors
• Subjects: aerospace plane; integrated navigation; complementary filter; information fusion
• Online Access: https://www.mdpi.com/1424-8220/20/24/7193

In order to solve the problems of heavy computational load and poor real time of the information fusion method based on the federated Kalman filter (FKF), a novel information fusion method based on the complementary filter is proposed for strapdown inertial navigation (SINS)/celestial navigation system (CNS)/global positioning system (GPS) integrated navigation system of an aerospace plane. The complementary filters are designed to achieve the estimations of attitude, velocity, and position in the SINS/CNS/GPS integrated navigation system, respectively. The simulation results show that the proposed information fusion method can effectively realize SINS/CNS/GPS information fusion. Compared with FKF, the method based on complementary filter (CF) has the advantages of simplicity, small calculation, good real-time performance, good stability, no need for initial alignment, fast convergence, etc. Furthermore, the computational efficiency of CF is increased by 94.81%. Finally, the superiority of the proposed CF-based method is verified by both the semi-physical simulation and real-time system experiment.