A Fault Tolerant SINS/GPS/CNS Integrated Navigation Scheme Realized through Federated Kalman Filter

Abstract:

The complementary characteristics of the Strapdown Inertial Navigation System (SINS) and external non-inertial navigation aids like Global Positioning System (GPS) and Celestial Navigation System (CNS) make the integrated navigation system an appealing and cost effective solution for various applications. SINS exhibits position errors owing to errors in initialization of the inertial measurement unit (IMU) and the inherent accelerometer biases and gyroscope drifts. SINS also suffer from diverging azimuth errors and an exponentially increasing vertical channel error. Pitch and roll errors also exhibit unbounded growth with time. To mitigate this behavior of SINS, periodic corrections are opted for through measurements from external non-inertial navigation aids. These corrections can be in the form of position fixing, velocity fixing and attitude fixing from external aids like GPS, GLONASS (Russian Satellite Navigation System), BEIDU(Chinese Satellite Navigation System) and Celestial Navigation Systems (CNS) etc. In this research work GPS and CNS are used as external aids for SINS and the navigation solutions of all three systems (SINS, GPS and CNS) are fused using Federated Kalman Filter (FKF). The FKF differs from the conventional Central Kalman Filter (CKF) because each measurement is processed in Local Filters (LFs), and the results are combined in a Master Filter (MF). FKF is a partitioned estimation method that uses a two stage data processing scheme, in which the outputs of sensor related LFs are subsequently combined by a large MF. Each LF is dedicated to a separate sensor subsystem, and uses data from the common reference such as SINS. The SINS acts as a cardinal system in the combination, and its data is also available as measurement input for the master filter. In this research work, information from the GPS and the CNS are dedicated to the corresponding LFs. Each LF provides its solutions to the master filter all information is fused together forming a global solution. Simulation for the proposed architecture has validated the effectiveness of the scheme, by showing the substantial precision improvement in the solutions of position, velocity and attitude as compared to the pure SINS or any other standalone system.

• Periodical: Applied Mechanics and Materials (Volume 332)
• Pages: 104-110
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.332.104
• Online since: July 2013
• Authors: Muhammad Ushaq, Fang Jian Cheng, Ali Jamshaid
• Keywords: Celestial Navigation, Fault Tolerant Navigation, Federated Kalman Filter, Global Positioning System (GPS), Inertial Navigation, Integrated Navigation, Kalman Filter (KF)

References

[1] D. Titterton and Weston, Strapdown inertial navigation technology [M], 2nd ed. Reston, USA: The Institution of Electrical Engineers, 2004.

[2] J. Farrell and M. Barth, The global positioning system and inertial navigation [M], vol. 61. McGraw-Hill New York, NY, USA:, 1999.

[3] N. A. Carlson, "Federated filter for fault-tolerant integrated navigation systems [C]," in Position Location and Navigation Symposium, Navigation into the 21st Century, 1988, p.110–119.

DOI: 10.1109/plans.1988.195473

[4] N. A. Carlson, "Federated square root filter for decentralized parallel processors [J]," Aerospace and Electronic Systems, vol. 26, no. 3, p.517–525, 1990.

DOI: 10.1109/7.106130

[5] J. Ali, "Augmented Performance Navigation Solution Realized Through Advanced Filtering Methods for Multisensor Data Fusion[D]," 2006.

[6] W. Quan and B. Liu, INS/CNS/GNSS Integrated Navigation Technology (Chinese Book) [M]. 2011.

[7] G. M. Siouris, Aerospace avionics systems: A Modern Synthesis [M], vol. 466. London, UK: Academic press Inc, 1993.

[8] Y. Yang and X. Cui, "Adaptive Integrated Navigation for Multisensor Adjustment Outputs [J]," THE JOURNAL OF NAVIGATION, vol. 57, p.287–295, 2004.

DOI: 10.1017/s0373463304002711