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Second Order Central Difference Filtering Algorithm for SINS/GPS Integrated Navigation in Guided Munitions

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6319))

Abstract

With the SINS/GPS integrated navigation system, the guided munitions can be carried out in complex weather, and have the high positioning navigation accuracy. This paper deduces key matrix of the second order central difference filtering (CDF2) equation. The CDF2 is described as a sigma point filter in a unified way where the filter linearizes the nonlinear dynamic and measurement functions by using an interpolation formula through systematically chosen sigma points. The effect which the key parameters of CDF2 bring to information fusion is analyzed qualitatively. The structure of loose integration is also given. According to the test data, the fusion algorithm based on CDF2 is applied. Compared to the original algorithm in longitude, latitude, altitude and velocity, the orientation precision is improved greatly.

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References

  1. Saulson, B.G.: Nonlinear estimation comparison for ballistic missile tracking. Automatica 43, 1424–1438 (2004)

    Google Scholar 

  2. Schei, T.S.: A finite-difference method for linearization in nonlinear estimation algorithms. Automatica 51, 252–260 (2003)

    Google Scholar 

  3. Kotecha, J.H., Djuric, P.M.: Gaussian particle filtering. IEEE Transactions on Signal Processing 51, 2592–2601 (2003)

    Article  MathSciNet  Google Scholar 

  4. Noureldin, A., El-Shafie, A., Taha, M.R.: Optimizing neuro-fuzzy modules for data fusion of vehicular navigation systems using temporal cross-validation. Eng. Appl. Artif. Intell. 20, 49–61 (2007)

    Article  Google Scholar 

  5. Noureldin, A., Osman, A., El-Sheimy, N.: A neuro-wavelet method for multisensor system integration for vehicular navigation. J. Meas. Sci. Technol. 15, 404–412 (2004)

    Article  Google Scholar 

  6. Semeniuk, L., Noureldin, A.: Bridging GPS outages using neural network estimates of INS position and velocity errors. Meas. Sci. Technol. 17(9), 2783–2798 (2006)

    Article  Google Scholar 

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© 2010 Springer-Verlag Berlin Heidelberg

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Cai, L., Zhang, X. (2010). Second Order Central Difference Filtering Algorithm for SINS/GPS Integrated Navigation in Guided Munitions. In: Wang, F.L., Deng, H., Gao, Y., Lei, J. (eds) Artificial Intelligence and Computational Intelligence. AICI 2010. Lecture Notes in Computer Science(), vol 6319. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16530-6_24

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  • DOI: https://doi.org/10.1007/978-3-642-16530-6_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16529-0

  • Online ISBN: 978-3-642-16530-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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