Open AccessAccuracy Improvement of Pedestrian Dead-Reckoning Based Map Heading Constraint in GNSS Denied Environments
Author(s) -
Mohamed A. Shebl,
Cairo Egypt,
Mohamed El-Tokhey,
Tamer Fathy,
Yasser M. Mogahed,
Mohamed Elhabiby
Publication year - 2020
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.d7845.049420
Subject(s) - gnss applications , dead reckoning , map matching , heading (navigation) , computer science , geospatial analysis , mobile mapping , real time computing , pedestrian , geocoding , mobile device , process (computing) , computer vision , artificial intelligence , global positioning system , remote sensing , engineering , geography , telecommunications , transport engineering , aerospace engineering , operating system , point cloud
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).