Title: A Collaborative Method for GNSS-based Inter-Agent Range Estimation and Hybrid Positioning Algorithm in Harsh Environment
Author(s): Alex Minetto, Calogero Cristodaro, Fabio Dovis
Published in: Proceedings of the 30th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2017)
September 25 - 29, 2017
Oregon Convention Center
Portland, Oregon
Pages: 3784 - 3795
Cite this article: Minetto, Alex, Cristodaro, Calogero, Dovis, Fabio, "A Collaborative Method for GNSS-based Inter-Agent Range Estimation and Hybrid Positioning Algorithm in Harsh Environment," Proceedings of the 30th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2017), Portland, Oregon, September 2017, pp. 3784-3795.
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Abstract: Harsh environment is the main impediment to GNSS service availability due to the obstruction of line-of-sight between the satellites and the receiver. A well-known countermeasure to this issue is the exploitation of additional measurements integrated with the GNSS solution, addressed to assure the continuity of service or to improve the positioning performance. Modern communication networks (i.e. 5G/LTE or VANET) provide limited delays allowing a quasi-real-time data transfers suitable for positioning applications. This work relies on such a kind of low-latency communication network, to cooperatively extract the pseudo-distance between pairs of agents equipped with Global Navigation Satellite Systems receivers, thus adapting the positioning algorithm to exploit the additional navigation data. The simultaneous observation of shared satellites allows to estimate the Non-Line-Of-Sight Inter-Agent Range and pseudo-Inter-Agent Range. This is pursued with the aim to guarantee a continuous position availability to the subset of receivers that are experiencing a GNSS positioning failure due to the limited visibility of the constellation, as it may happen in urban scenarios. In this context, the effectiveness of the hybrid cooperative positioning, smoothed with a properly designed Kalman Filter, is verified.