Performance enhancement of MEMS-based INS/GPS integration for low-cost navigation applications

Aboelmagd Noureldin, Tashfeen B. Karamat, Mark D. Eberts, Ahmed El-Shafie

    Research output: Contribution to journalArticle

    244 Citations (Scopus)

    Abstract

    The relatively high cost of inertial navigation systems (INSs) has been preventing their integration with global positioning systems (GPSs) for land-vehicle applications. Inertial sensors based on microelectromechanical system (MEMS) technology have recently become commercially available at lower costs. These relatively lower cost inertial sensors have the potential to allow the development of an affordable GPS-aided INS (INS/GPS) vehicular navigation system. While MEMS-based INS is inherently immune to signal jamming, spoofing, and blockage vulnerabilities (as opposed to GPS), the performance of MEMS-based gyroscopes and accelerometers is significantly affected by complex error characteristics that are stochastic in nature. To improve the overall performance of MEMS-based INS/GPS, this paper proposes the following two-tier approach at different levels: 1) improving the stochastic modeling of MEMS-based inertial sensor errors using autoregressive processes at the raw measurement level and 2) enhancing the positioning accuracy during GPS outages by nonlinear modeling of INS position errors at the information fusion level using neuro-fuzzy (NF) modules, which are augmented in the Kalman filtering INS/GPS integration. Experimental road tests involving a MEMS-based INS were performed, which validated the efficacy of the proposed methods on several trajectories.

    Original languageEnglish
    Pages (from-to)1077-1096
    Number of pages20
    JournalIEEE Transactions on Vehicular Technology
    Volume58
    Issue number3
    DOIs
    Publication statusPublished - 2009

    Fingerprint

    Inertial Navigation System
    Inertial navigation systems
    Global Positioning System
    System Integration
    Micro-electro-mechanical Systems
    MEMS
    Global positioning system
    Navigation
    Enhancement
    Inertial Sensors
    Costs
    Sensors
    Nonlinear Modeling
    Stochastic Modeling
    Information fusion
    Information Fusion
    Kalman Filtering
    Gyroscope
    Neuro-fuzzy
    Autoregressive Process

    Keywords

    • Global positioning system (GPS)
    • Inertial navigation system (INS)
    • Kalman filter (KF)
    • Microelectromechanical system (MEMS)
    • Neuro-fuzzy (NF) systems
    • Wavelet

    ASJC Scopus subject areas

    • Electrical and Electronic Engineering
    • Aerospace Engineering
    • Automotive Engineering
    • Computer Networks and Communications
    • Applied Mathematics

    Cite this

    Performance enhancement of MEMS-based INS/GPS integration for low-cost navigation applications. / Noureldin, Aboelmagd; Karamat, Tashfeen B.; Eberts, Mark D.; El-Shafie, Ahmed.

    In: IEEE Transactions on Vehicular Technology, Vol. 58, No. 3, 2009, p. 1077-1096.

    Research output: Contribution to journalArticle

    Noureldin, Aboelmagd ; Karamat, Tashfeen B. ; Eberts, Mark D. ; El-Shafie, Ahmed. / Performance enhancement of MEMS-based INS/GPS integration for low-cost navigation applications. In: IEEE Transactions on Vehicular Technology. 2009 ; Vol. 58, No. 3. pp. 1077-1096.
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