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Global navigation satellite systems play a significant role in the development of intelligent transport systems, where the estimation of the vehicle’s position is a key element. However, in strongly constrained environments such as city centers, the definition of quality metrics and the assessment of positioning performances are challenges to be addressed. Due to the variability of different urban scenarios, the modeling of the dynamics as well as the architecture of the positioning platform, which might embed other sensors and aiding means to the GNSS unit, make it hard to define unambiguous positioning metrics. Performance assessment through analytical models and simulators can be ineffective in terms of cost, complexity, and general validity and scalability of the results. This paper shows how a record and replay approach can be an efficient solution to grant fidelity to a realistic scenario. This work discusses advantages and disadvantages with emphasis on the case study of harsh scenarios. Such an approach requires proper data collections that allow the replay phase to test the GNSS-based positioning terminals. This paper presents the results obtained on a set of field tests related to different scenarios, selected as representative for the key performance indicators assessment.

Abstract-The limited availability and the lack of continuity in the service of Global Positioning Satellite Systems (GNSS) in harsh environments is a critical issue for Intelligent Transport Systems (ITS) applications relying on the position. This work is developed within the framework of vehicle-to-everything (V2X) communication, with the aim to guarantee a continuous position availability to all the agents belonging to the network when GNSS is not available for a subset of them. The simultaneous observation of shared satellites is exploited to estimate the NonLine-Of-Sight Inter-Agent Range within a real-time-connected network of receivers. It is demonstrated the effectiveness of a hybrid localization algorithm based on the the integration of standard GNSS measurements and linearised IAR estimates. The hybrid position estimation is solved through a self-adaptive iterative algorithm to find the position of receivers experiencing GNSS outages.

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