Abstract
To improve the alignment accuracy and convergence speed of Strapdown inertial navigation system, an initial alignment which is based on Bilinear Recursive Least Square adaptive filter is proposed. The error model for the Strapdown Inertial Navigation System (SINS) is derived from the dynamic model by considering a small misalignment angle. In the literature many algorithms are proposed for the proper estimation of alignment accuracy for INS and it is still a challenge. In this paper, two algorithms which are mainly based on nonlinear adaptive filter viz. Volterra Recursive Least Square (VRLS) and Bilinear Recursive Least Square (BRLS) are proposed and compared for proper estimation of accurate azimuth alignment error. The comparative performances of the aforesaid algorithms are studied and the performance of proposed BRLS algorithm is found to be effective which is obtained in existence of two different white Gaussian noises. The simulation work is done in MATLAB simulating environment. For the realization and validation of proposed BRLS algorithm, the comparative analysis is also precisely presented.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Titterton, D., Weston, J. In: Strapdown Inertial Navigation Technology, Institution of Electrical Engineers (2004)
Wang, X., Shen, G.: A Fast and Accurate Initial Alignment Method for Strapdown Inertial Navigation System on Stationary Base. Journal of Control Theory and Applications, 145–149 (2005)
Sun, F., Zhang, H.: Application of a New Adaptive Kalman Filitering Algorithm in Initial Alignment of INS. In: Proceedings of the IEEE International Conference on Information and Automation, Beijing, China, pp. 2312–2316 (2011)
Gong-Min, V., Wei-Sheng, Y., De-Min, X.: Application of simplified UKF in SINS initial alignment for large misalignment angles. Journal of Chinese Inertial Technology 16(3), 253–264 (2008)
Anderson, B.D.O., Moore, J.B.: Optimal Filtering. Prentice-Hall Inc., Englewood Cliffs (1979)
Savage, P.G.: A unified mathematical framework for strapdown algorithm design. J. Guid. Contr. Dyn. 29, 237–249 (2006)
Silson, P.M.: Coarse alignment of a ship’s strapdown inertial attitude reference system using velocity loci. IEEE Transcript Instrumentation Measurement (2011)
Li, Q., Ben, Y., Zhu, Z., Yang, J.: A Ground Fine Alignment of Strapdown INS under a Vibrating Base. J. Navigation 1, 1–15 (2013)
Wu, M., Wu, Y., Hu, X., Hu, D.: Optimization-based alignment for inertial navigation systems: Theory and algorithm. Aeros. Science & Technology, 1–17 (2011)
Salychev, O.S.: Applied Estimation Theory in Geodetic and Navigation Applications. Lecture Notes for ENGO 699.52, Department of Geomatics Engineering, University of Calgary (2000)
Julier, S.J., Uhlmann, J.K.: Unscented filtering and nonlinear estimation. In: Proc. of the IEEE Aerospace and Electronic Systems, pp. 401–422 (2004)
Paulo, S.R.: Adaptive Filtering Algorithms and Practical Implementation, 3rd edn. Springer
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Malakar, B., Roy, B.K. (2014). Application of Bilinear Recursive Least Square Algorithm for Initial Alignment of Strapdown Inertial Navigation System. In: Kumar Kundu, M., Mohapatra, D., Konar, A., Chakraborty, A. (eds) Advanced Computing, Networking and Informatics- Volume 1. Smart Innovation, Systems and Technologies, vol 27. Springer, Cham. https://doi.org/10.1007/978-3-319-07353-8_1
Download citation
DOI: https://doi.org/10.1007/978-3-319-07353-8_1
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07352-1
Online ISBN: 978-3-319-07353-8
eBook Packages: EngineeringEngineering (R0)