The usage of Global Navigation Satellites Systems (GNSS) for localisation purposes demands a permanent evaluation of the position information provided for the receiver, as well as a standardised GNSS-Receivers validation methodology and subsequently quality control procedures oriented to land vehicles within the ergodic hypothesis. The use of an independent reference system should provide enough information to validate the localisation system, but the lack of proper evaluation and procedures presents significant blind spots for future applications in both the GNSS-Receiver and the correspondent reference system. To solve these problems an approach based on artificial intelligence (AI) is presented. Also the development of an advanced filter technique for positioning estimation results in significant improvements of the reference system, even allowing a standalone GNSSdependent reference system when no independent systems are available. The presented developments are the bases for future intelligent GNSS-based localisation systems. The methodologies combine the advanced Particle Filter (PF) for positioning estimation with the newly developed Mahalanobis Ellipses Filter (MEF) methodology for accuracy-based data evaluation and the Artificial Neural Networks (ANN) models for both quantitative and qualitative validation. In this thesis the bases of the intelligent GNSS-based localisation system are presented and developed follows the BMW principle. In German the BMW principle stands for Beschreibungsmittel (means of description), Methode (methods) and Werkzeug (tool). The resulting system described along the thesis is applied and tested in a demonstrator tool, validating the developed methodologies in both software and hardware level. The proposed methodologies for the development of an intelligent GNSS-based localisation system are a substantial contribution for intelligent GNSS-based validation tools that will enable future safety-relevant applications, in field such as on-board uncertainty evaluation of vehicle localisation; advanced driver assistance systems; and GNSS-based vehicle localisation with intelligent maps for track selective enabled-localisation.


    Access

    Download

    Check availability in my library


    Export, share and cite



    Title :

    Development of Intelligent GNSS-based Land Vehicle Localisation Systems


    Additional title:

    Entwicklung intelligenter GNSS-basierten Landfahrzeug Lokalisierungssysteme



    Publication date :

    2015



    Type of media :

    Miscellaneous


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    DDC:    629 / 006



    Development of intelligent GNSS-based land vehicle localisation systems

    Grasso Toro, Federico / Technische Universität Braunschweig | TIBKAT | 2015


    Development of intelligent GNSS-based land vehicle localisation systems

    Grasso Toro, Federico / Technische Universität Braunschweig | TIBKAT | 2015

    Free access



    Infrastructure camera calibration with GNSS for vehicle localisation

    Ojala, Risto / Vepsäläinen, Jari / Pirhonen, Jesse et al. | Wiley | 2023

    Free access