Study and Design of GNSS-based Positioning Units Integrating Collaborative Virtual Ranging

In a Global Navigation Satellite System (GNSS) the distance from (at least) 4 satellite vehicles needs to be measured by a receiver to obtain an estimate of its position. This information is extracted from signals transmitted by satellites, but GNSS services can fail or lose reliability when propagation is not in Line-of-Sight (LOS) conditions. In this sense, an urban scenario represents a harsh environment where obstacles may obstruct the satellites view. As a result, limited availability and lack of continuity commonly arise.The rise of smart transport paradigm, and the development of Intelligent Transport Systems (ITS), is nowadays a task of interest for the GNSS community, since it is related to precise and reliable positioning systems. In view of such a framework, where the accurate estimation of the vehicle's position plays a key role, service discontinuity experienced by users is an even more dangerous threat.A well-known countermeasure to this issue is the integration of additional measurements within the navigation algorithm, addressed to assure the continuity of service or to improve the positioning performance. Furthermore, modern mobile communication technologies (i.e. 5G/LTE or DSRC networks) aim at providing ultra-low latency, fostering the exchange of navigation data as a promising alternative to sensors for retrieving additional measurements.This work is contextually addressed to such low-latency communication networks, where an additional range measurement is cooperatively obtained from pairs of agents equipped with GNSS receivers. This Inter-Agent range (IAR), is thus integrated as additional navigation data within a hybridized algorithm for positioning.The simultaneous observation of shared satellites allows to estimate the IAR between two asynchronous receivers. This range is obtained from a geometric calculation performed by the two agents and based on GNSS pseudorange measurements. The use of GNSS measurements for building an additional range allows its estimation even if the two communicating agents are not in LOS conditions, targeting a significant improvement with respect to state-of-the-art ranging technologies. Moreover, even though the algorithm is intrinsically cooperative, confidentiality is guaranteed by a protection mechanism that is based on virtual positions and a wise distribution of the computational tasks between the two agents.The implementation of the IAR algorithm requires the use of predictive filters. The relationship between the predicted position's uncertainty and the improvement of its precision raised by the inter-agent cooperation is non-trivial.In this work the effectiveness of the information enhancement is verified to prevent a potentially ill-conditioned problem. This aspect is characterized in a theoretical framework and inspected trough a simulation approach that allows also a performance evaluation in a realistic scenario.A comprehensive investigation of the cooperative network is carried out through several case studies and under specific parameters settings, including communication delays and predictive filter parameters. The networked agents are modeled with independent motions and sky visibility, in order to simulate a wide range of contexts. Furthermore, a novel algorithm for the navigation solution is implemented, proposing a tight-integration of GNSS pseudorange measurements and IAR in an Extended Kalman Filter.