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Airborne Integrated Navigation System Based on SINS/GPS/TAN/EOAN

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  • Junjun Tang
  • Peijuan Li

Abstract

Considering the drawbacks that GPS signal is susceptible to obstacles and TAN becomes useless in some area when without any terrain data or with a featureless terrain field, to realize long-distance and high-precision navigation, a navigation system based on SINS/GPS/TAN/EOAN is presented. When GPS signal is available, GPS is used to correct errors of SINS; when GPS is unavailable, a terrain selection method based on the entropy weighted gray relational decision-making method is use to distinguish terrain into matchable areas and unmatchable areas; then, for the matchable areas, TAN is used to correct errors of SINS, for the unmatchable areas, EOAN is used to correct errors of SINS. The principles of SINS, GPS, TAN, and EOAN are analyzed, the mathematic models of SINS/GPS, SINS/TAN, and SINS/EOAN are constructed, and finally the federated Kalman filter is used to fuse navigation information. Simulation results show that the trajectory of SINS/GPS/TAN/EOAN is close to the ideal one in both matchable area or unmatchable area and whose navigation errors are obviously reduced, which is important for the realization of long-time and high-precision positioning.

Suggested Citation

  • Junjun Tang & Peijuan Li, 2020. "Airborne Integrated Navigation System Based on SINS/GPS/TAN/EOAN," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-9, November.
    • Handle: RePEc:hin:jnlmpe:3218942
    DOI: 10.1155/2020/3218942
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    Cited by:

    1. Brown, Austin L. & Sperling, Daniel & Austin, Bernadette & DeShazo, JR & Fulton, Lew & Lipman, Timothy & Murphy, Colin W & Saphores, Jean Daniel & Tal, Gil & Abrams, Carolyn & Chakraborty, Debapriya &, 2021. "Driving California’s Transportation Emissions to Zero," Institute of Transportation Studies, Working Paper Series qt3np3p2t0, Institute of Transportation Studies, UC Davis.
    2. Dansong Yue & Shuqi Shang & Kai Feng & Haiqing Wang & Xiaoning He & Zelong Zhao & Ning Zhang & Baiqiang Zuo & Dongwei Wang, 2023. "Research on the Model of a Navigation and Positioning Algorithm for Agricultural Machinery Based on the IABC-BP Network," Agriculture, MDPI, vol. 13(9), pages 1-24, September.

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