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 ...
Development of Intelligent GNSS-based Land Vehicle Localisation Systems ; Entwicklung intelligenter GNSS-basierten Landfahrzeug Lokalisierungssysteme
29.05.2015
Hochschulschrift
Elektronische Ressource
Englisch
Development of Intelligent GNSS-based Land Vehicle Localisation Systems
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