Indoor Navigation with a Smartphone Fusing Inertial and WiFi Data via Factor Graph Optimization

  • Michał NowickiEmail author
  • Piotr Skrzypczyński
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 162)


Mobile devices are getting more capable every year, allowing a variety of new applications, such like supporting pedestrian navigation in GPS-denied environments. In this paper we deal with the problem of combining in real-time dead reckoning data from the inertial sensors of a smartphone, and the WiFi signal fingerprints, which enable to detect the already visited places and therefore to correct the user’s trajectory. While both these techniques have been used before for indoor navigation with smartphones, the key contribution is the new method for including the localization constraints stemming from the highly uncertain WiFi fingerprints into a graphical problem representation (factor graph), which is then optimized in real-time on the smartphone. This method results in an Android-based personal navigation system that works robustly with only few locations of the WiFi access points known in advance, avoiding the need to survey WiFi signal in the whole area. The presented approach has been evaluated in public buildings, achieving localization accuracy which is sufficient for both pedestrian navigation and location-aware applications on a smartphone.


Navigation Localization Factor graph Data fusion WiFi IMU Smartphone Android 



This work is financed by the Polish Ministry of Science and Higher Education in years 2013–2015 under the grant DI2012 004142.


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Copyright information

© Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2015

Authors and Affiliations

  1. 1.Institute of Control and Information EngineeringPoznań University of TechnologyPoznańPoland

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