access icon free Circular particle fusion filter applied to map matching

© The Institution of Engineering and Technology
Received 03/10/2016, Accepted 12/07/2017, Revised 01/06/2017, Published 14/07/2017

Navigation in constrained areas such as ports or dense urban environments is often exposed to global navigation satellite system (GNSS) satellites masking caused by the infrastructures. In this case, the GNSS positioning is inaccurate or unavailable and proprioceptive sensors are generally used to temporarily localise the vehicle on a map. However, the drift of these sensors rapidly causes the navigation system to fail. In this study, the navigation is computed using magnetometer and GNSS observations defined in an absolute reference frame. The heading measurements are coupled with a digital map of the road network in order to localise the vehicle in a map matching process. The contribution of this study is the proposition of a particle filter that fuses the position and direction observations to estimate the vehicle position. In this context, when the GNSS signal is masked, the observations of direction are used to compute the vehicle position. The proposed filter is defined in both circular and linear domains in order to take into account the nature of the observations. The proposed approach is assessed on real and synthetic data.

Inspec keywords: intelligent transportation systems; road vehicles; cartography; particle filtering (numerical methods); satellite navigation; sensor fusion

Other keywords: circular particle fusion filter; road network; GNSS satellites; GNSS positioning; global navigation satellite system; map matching

Subjects: Geography and cartography computing; Filtering methods in signal processing; Interpolation and function approximation (numerical analysis); Traffic engineering computing; Sensor fusion; Interpolation and function approximation (numerical analysis); Radionavigation and direction finding

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