Abstract
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.
Highlights
The importance of accuracy and integrity in a positioning system has increasingly been emphasized in many intelligent transportation system or intelligent vehicle applications such as advanced driver assistance systems, intersection collision warnings, and traffic control [1,2,3]
A fuzzy calibration logic (FCL) is designed and introduced, which can determine the dependable degree of each received satellite measurement according to its features including current geometrical distribution and carrier-to-noise ratio
To verify the positioning performance of the proposed solution, experiments were conducted on a Chery TIGGO5 SUV vehicle
Summary
Received 14 November 2016; Revised 11 January 2017; Accepted 6 February 2017; Published 5 March 2017. The integration between Global Navigation Satellite System (GNSS) and on-board sensors is widely used for vehicle positioning. 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. 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. The results validate the feasibility and effectiveness of the proposed solution
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