Robust indoor localization using optimal fusion filter for sensors and map layout information

A person has to deal with large and unknown scenarios, for example a client searching for a expositor in a trade fair or a passenger looking for a gate in an airport. Due to the fact that position awareness represents a great advantage for people, a navigation system implemented for a commercial smartphone can help the user to save time and money. In this work a navigation example application able to localize and provide directions to a desired destination in an indoor environment is presented and evaluated. The position of the user is calculated with information from the smartphone builtin sensors, WiFi adapter and floor-plan layout of the indoor environment. A commercial smartphone is used as the platform to implement the example application, due to it´s hardware features, computational power and the graphic user interface available for the users. Evaluations verified that room accuracy is achieved for robust localization by using the proposed technologies and algorithms. The used optimal sensor fusion filter for different sources of information and the easy to deploy infrastructure in a new environment show promise for mobile indoor navigation systems.