Our paper adapts recent advances in the SLAM (Simultaneous Localization and Mapping) literature to the problem of multipath mitigation and proposes a novel approach to successfully localize a vehicle despite a significant number of multipath observations. We show that GNSS-based localization problems can be modelled as factor graphs and solved using efficient nonlinear least squares methods that exploit the sparsity inherent in the problem formulation. Using a recently developed novel approach for robust optimization, satellite observations that are subject to multipath errors can be successfully identified and rejected during the optimization process. We demonstrate the feasibility of the proposed approach on a real-world urban dataset and compare it to an existing method of multipath detection.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Multipath mitigation in GNSS-based localization using robust optimization


    Contributors:


    Publication date :

    2012-06-01


    Size :

    2217418 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Multipath Mitigation in GNSS-Based Localization Using Robust Optimization

    Sunderhauf, N. / Obst, M. / Protzel, P. et al. | British Library Conference Proceedings | 2012


    GNSS Multipath Mitigation using Antenna Motion

    Psiaki, Mark L | Online Contents | 2015


    Probabilistic Multipath Mitigation for GNSS-based Vehicle Localization in Urban Areas

    Obst, M. / Adam, C. / Wanielik, G. et al. | British Library Conference Proceedings | 2013


    GNSS Multipath Mitigation with a Moving Antenna Array

    Daneshmand, S. / Broumandan, A. / Sokhandan, N. et al. | IEEE | 2013


    Deep Neural Network Correlators for GNSS Multipath Mitigation

    Li, Haoqing / Borhani-Darian, Parisa / Wu, Peng et al. | IEEE | 2023