Journal article Open Access

Accuracy Improvement of Pedestrian Dead-Reckoning Based Map Heading Constraint in GNSS-Denied Environments

Mohamed Shebl; Mohamed El-Tokhey; Tamer Fathy; Yasser Mogahed,; Mohamed El-Habiby

Sponsor(s)
Blue Eyes Intelligence Engineering & Sciences Publication(BEIESP)

the demand for navigation systems is rapidly increasing, especially in GNSS-denied environments. The ubiquitous use of smart mobile devices equipped with various sensors encouraged many researchers to investigate their use in improving indoor navigation, where GNSS is not available. Inertia navigation sensors installed in mobile devices are normally low cost and drift significantly. Consequently, there is a need for auxiliary systems to aid the navigation process, which can be achieved using external sensors or additional information extracted from, for example, base maps. In this research paper, maps have been selected as a navigation aid. Previously, maps were used for navigation aiding through geospatial data models and map-matching algorithms. These methods are based on creating geospatial data models on the fly and integrating them in the navigation database, which makes them computationally expensive and time-consuming. In this research paper, the maps were used in an innovative way. The map directions were used in Pedestrian a dead reckoning (PDR) mode to improve the low-accuracy directions derived from portable device sensors. This method is significantly computationally efficient compared to traditional geospatial map-matching algorithms. The new approach replaces the traditional geospatial database with a list of street directions and paths that are used as Map Heading Constraints (MHC) when navigating (walking) in straight directions. The proposed technique was tested on trajectories in GNSS denied environment (underground parking) using an iphone6s smart-phone and compared with other solutions that used the portable device sensors only. The comparison showed a significant improvement in position accuracy (up to 90%) in comparison to using the portable device sensors only (no aiding).

Files (894.7 kB)
Name Size
D7845049420.pdf
md5:9c16e05822c2b0b4e7d572d090818545
894.7 kB Download
6
11
views
downloads
Views 6
Downloads 11
Data volume 9.8 MB
Unique views 6
Unique downloads 11

Share

Cite as