Thomas Verheyde, TéSA - Cooperative Research Laboratory, France; Antoine Blais, Christophe Macabiau, ENAC - École Nationale de l'Aviation Civile, Université de Toulouse, France; François-Xavier Marmet, CNES - Centre National d'Études Spatiales, France

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The release of Android Global Navigation Satellite Systems (GNSS) raw measurements in late 2016 unlocked the access of smartphones' embedded positioning chipset capabilities for developers and the scientific community. This groundbreaking announcement was followed by technical innovations, made by smartphone brands and chipset manufacturers, in order to obtain the world's most precise smartphone on the market. In recent years, several studies investigated the development of advanced positioning techniques (e.g. Precise Point Positioning (PPP), Real-Time Kinematic (RTK)) using Android raw data measurements. However, most studies drawn their conclusions based on one smartphone brand and model in optimal open-sky conditions despite the fact that most smartphone-based positioning activities are achieved in urban and sub-urban areas. In order to overcome urban smartphone-based positioning issues, we ambition to develop a collaborative user’s network taking advantage of the tremendous numbers of connected Android devices in today's busy city centers. A throughout study has been conducted in the city center of Toulouse in France for characterizing smartphone positioning performance in both nominal and urban conditions. Various limiting factors were exposed during our data collection campaign. Nevertheless, the investigation conducted on Android GNSS raw measurement uncovered smartphone positioning potential for navigation applications in constraint environment. A methodology assessment has been implemented in order to identify, characterize and compare smartphones’ positioning performances. A classification of key parameters has been determined focusing on the implementation of collaborative algorithms, revealing the attributes and components for smartphone-based collaborative methods. Thereafter, a comprehensive state of the art review on existing cooperative positioning techniques, has been achieved. An evaluation of the feasibility and the applicability of those methods into the smartphone domain has been made. We present a method based on simple assumptions, without third-party equipment and data, only relying on smartphones’ own data combination. Our cooperative network can be described as a low-cost embedded structure aiming at providing positioning assistance to its users.