Abstract
The Non-gyro inertial measurement unit (NGIMU) uses only accelerometers replacing gyroscopes to compute the motion of a moving body. In a NGIMU system, an inevitable accumulation error of navigation parameters is produced due to the existence of the dynamic noise of the accelerometer output. When designing an integrated navigation system, which is based on a proposed nine-configuration NGIMU and a single antenna Global Positioning System (GPS) by using the conventional Kalman filter (CKF), the filtering results are divergent because of the complicity of the system measurement noise. So a fuzzy logic adaptive Kalman filter (FLAKF) is applied in the design of NGIMU/GPS. The FLAKF optimizes the CKF by detecting the bias in the measurement and prevents the divergence of the CKF. A simulation case for estimating the position and the velocity is investigated by this approach. Results verify the feasibility of the FLAKF.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
DiNapoli, L.D.: The Measurement of Angular Velocities without the Use of Gyros. The Moore School of Electrical Engineering, pp. 34–41. University of Pennsylvania, Philadelphia (1965)
Alfred, R.: Schuler: Measuring Rotational Motion with Linear Accelerometers. IEEE Trans. on AES. 3(3), 465–472 (1967)
Merhav, S.J.: A Nongyroscopic Inertial Measurement Unit. J. Guidance. 5(3), 227–235 (1982)
Tan, C.-W., Park, S.: Design of gyroscope-free navigation systems. Intelligent Transportation Systems. In: 2001 Proceedings, Oakland, pp. 286–291 (2001)
Lee, S.-C., Huang, Y.-C.: Innovative estimation method with measurement likelihood for all-accelerometer type inertial navigation system. IEEE Trans. on AES 38(1), 339–346 (2002)
Qi, W., Mingli, D., Peng, Z.: A New Scheme of Non-gyro Inertial Measurement Unit for Estimating Angular Velocity. In: The 29th Annual Conference of the IEEE Industry Electronics Society (IECON 2003), Virginia, pp. 1564–1567 (2003)
Sasiadek, J.Z., Wang, Q., Zeremba, M.B.: Fuzzy Adaptive Kalman Filtering For INS/GPS Data Fusion. In: Proceedings of the 15th IEEE International Symposium on Intelligent Control, Rio, Patras, GREECE, pp. 181–186 (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ding, M., Wang, Q. (2005). An Integrated Navigation System of NGIMU/ GPS Using a Fuzzy Logic Adaptive Kalman Filter. In: Wang, L., Jin, Y. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2005. Lecture Notes in Computer Science(), vol 3613. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539506_100
Download citation
DOI: https://doi.org/10.1007/11539506_100
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28312-6
Online ISBN: 978-3-540-31830-9
eBook Packages: Computer ScienceComputer Science (R0)