Global Navigation Satellite Systems (GNSS) is utilized to provide route guidance information to land and autonomous vehicles. The GNSS–based positioning and navigation (POS/NAV) usually suffer from satellite signal blockage, interference, and multipath in urban areas. Autonomous land vehicles are equipped with cameras, radars, and laser ranging devices. The availability of these systems provides an attractive opportunity to increase the POS/NAV system accuracy. This research focuses on the development of an integrated multi-sensor POS/NAV system capable of offering seamless positioning for autonomous land vehicles. A new multi-sensor POS/NAV module integrating both adaptive cruise control frequency modulated continuous wave (ACC-FMCW) radar (RAD), and magnetometer measurements with the reduced inertial sensor system (RISS) was designed to update the navigation system during GNSS outages. Augmenting RAD/RISS system with the magnetometer measurements produces a robust solution. The designed system is further improved by utilizing fast orthogonal search (FOS) to provide nonlinear error modeling of the residual errors associated with the RAD/RISS positioning solution in order to reduce the error growth overextended and frequent GNSS outages.The proposed systems were evaluated on several real road test trajectories involving different types of land vehicles experiencing different motion dynamics. GNSS outages of up to 10 minutes were intentionally introduced to examine the performance. The results show that the proposed methods have resulted in a significant performance improvement in the positioning accuracy that can reach more than 80% if compared to the present techniques that rely only on integrating the inertial sensor technology with GNSS.


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    Titel :

    A Novel Multi-Level Integrated Navigation System for Challenging GNSS Environments


    Beteiligte:


    Erscheinungsdatum :

    2021-08-01


    Format / Umfang :

    4781352 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch