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Journal of Sensors
Volume 2017, Article ID 5965716, 11 pages
Research Article

A Tightly Coupled Positioning Solution for Land Vehicles in Urban Canyons

1School of Instrument Science and Engineering, Southeast University, Nanjing, China
2Key Laboratory of Technology on Intelligent Transportation Systems, Ministry of Transport, Research Institute of Highway Ministry of Transport, Beijing 100088, China

Correspondence should be addressed to Xu Li; moc.361@liam.uxil

Received 14 November 2016; Revised 11 January 2017; Accepted 6 February 2017; Published 5 March 2017

Academic Editor: Pietro Siciliano

Copyright © 2017 Xu Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The integration between Global Navigation Satellite System (GNSS) and on-board sensors is widely used for vehicle positioning. However, as the main information source in the integration, the positioning performance of single- or multiconstellation GNSSs is severely degraded in urban canyons due to the effects of Non-Line-Of-Sight (NLOS) and multipath propagations. How to mitigate such effects is vital to achieve accurate positioning performance in urban canyons. This paper proposes a tightly coupled positioning solution for land vehicles, fusing dual-constellation GNSSs with other low-cost complementary sensors. First, the nonlinear filter model is established based on a cost-effective reduced inertial sensor system with 3D navigation solution. Then, an adaptive fuzzy unscented Kalman filter (AF-UKF) algorithm is developed to achieve the global fusion. In the implementation of AF-UKF, the fuzzy calibration logic (FCL) is designed and introduced to adaptively adjust the dependence on each received satellite measurement to effectively mitigate the NLOS and multipath interferences in urban areas. Finally, the proposed solution is evaluated through experiments. The results validate the feasibility and effectiveness of the proposed solution.