An Intelligent Multi-sensor System for Pedestrian Navigation

G. Retscher

Institute of Geodesy and Geophysics, Vienna University of Technology, Austria.

DOI:                 

Abstract

In the research project “Pedestrian Navigation Systems in Combined Indoor/Outdoor Environements” (NAVIO) we are working on the development of modern intelligent systems and services for pedestrian navigation and guidance. In the project modern and advanced intelligent mobile multi-sensor systems should be employed for 3-D position determination of a user. Due to the fact that satellite positioning with GNSS (Galileo, GPS, etc.) does not work under any environmental condition (e.g. in urban “canyons” with no satellite visibility and indoor) a combination and integration with other sensors (e.g. dead reckoning sensors, inertial navigation systems (INS), indoor location techniques, cellular phone positioning, etc.) is essential. In our approach a loose coupling of the employed sensors should be achieved and it is proposed to develop a multisensor fusion model which makes use of knowledgebased systems. As far as we can see now knowledgebased systems can be especially useful. Thereby the decision which sensors should be used to obtain an optimal estimate of the current user’s position and the weightings of the observations shall be based on knowledge-based systems. The new algorithm would be of great benefit for the integration of different sensors as the performance of the service would be significantly improved. In this paper the basic principle of the new approach will be described. To test and to demonstrate our approach and results, the project takes a use case scenario into account, i.e., the guidance of visitors to departments of the Vienna University of Techology from nearby public transport stops. The results of first field tests could confirm that such a service can achieve a high level of performance for the guidance of a pedestrian in an urban area and mixed indoor and outdoor environments. Standard deviations in the range of few meters can be achieved for 3-D positioning in urban areas although obstructions cause frequent loss of lock for satellite positioning. Thereby GPS outages of up to 150 m can be bridged using dead reckoning observations with the required positioning accuracy. For indoor areas satellite positioning can be replaced by indoor positioning systems (e.g. WiFi, UWB). Due to the development of advanced sensors it can be expected that such multisensor solutions will be deployed in pedestrians navigation services. We believe that these services will play an important role in the field of location-based services in the near future as a rapid development has already started which is driven by their possible applications.

Keywords

Pedestrian Navigation, Integrated Positioning, Multi-Sensor Fusion, Kalman Filter, Knowledge-Based Systems.

Conflicts of Interest

The authors declare no conflicts of interest.

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