In this paper an Indoor Navigation System with map-matching capabilities in real-time on a smart phone is presented. The basis of the system is an in-house development of an Integrated Pedestrian Navigation System, based on 2 low-cost IMUs, an electronic compass and an altimeter with a drifting navigation solution. Combining this system with an additional laser ranger and SLAM algorithms, we are able to build accurate maps of office buildings for already visited rooms in post processing.This paper presents a map matching algorithm based on a new reduced particle filter in order to use these maps later for realtime applications without an expensive laser ranger but relying only on the dual inertial system. It can be used with both, preprocessed SLAM maps or with already available maps. Finally to smooth the resulting trajectory after particle filtering we propose the use of a new "balanced bubble band smoother" allowing the trajectory to optimally match to both, map and recorded IMU data. This new approach makes it possible to do map matching online on a smart phone.

Indoor navigation using inertial sensors with additional radio-signal support is considered in this paper. The experimental results of data fusion between a navigation system, based on inertial measurement unit (IMU) and impulsebased UWB localization system, are presented. The IMU is additionally supported by a pedestrian step length estimations, barometer and electronic compass. The Ultra-Wideband part consists of receiver, carried by the person, and access points distributed in the scenario. The focus of the paper is put on hardware implementation and choice of the optimal data fusion technique. The presented results indicate the clear benefit of tightly coupled navigation filter, where the time differences of arrival of UWB signals are directly processed, without prior calculation of the localization solution.

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