Organised by
ISIF
In Association with
USAL UC3M
Supported by
IEEE

SS16 - Data Fusion Methods for Indoor Localization of People and Objects

Indoor positioning has gained great importance since technology allows   for affordable realtime sensing and processing systems. Also the   pervasiveness of WSNs (e.g., in the form of WLAN) and mobile sensors   (such as smartphones) has inspired researchers and developers to  exploit  the existing infrastructure. Applications include pedestrian  navigation  in public buildings and shops, location based services,  safety for the  elderly and impaired, museum guides, surveillance tasks,  but also  tracking products in manufacturing, warehousing etc., the  list goes on.  Unlike outdoor environments, which are covered by GNSS to  a satisfiable  extent, indoor navigation faces additional challenges,  depending on the  underlying measurement system, such as occlusions,  reflections and  attenuation. There is a great variety of sensors and  measuring  principles, however, in practice every single measuring  technique  suffers from deficits. While RF and (ultra-)sound are subject  to  multipath propagation, optical systems are intolerant to NLOS   conditions. Some systems require setting up beacons, while others are   self-calibrating and easy-to-install. Obviously, data fusion can   overcome these limitations by combining complementary, and redundant   sensing techniques, and using elaborate algorithmic methods, such as   stochastic filtering. This Special Session addresses fundamental   techniques, recent developments and future research directions to help   clear the way toward robust, accurate, indoor localization. 

Topics of interest

  • Fusion  of any of the following: optical, (ultra-)sound,  magnetic, WLAN+RF  RSS, UWB, fingerprinting, INS, RFID, TOF, TOA, TDOA,  ... 
  • Hybrid pedestrian navigation, SLAM 
  • Efficient signal processing for real-time data fusion 
  • Dealing with multipath/NLOS conditions 
  • Sensor management: high redundancy, high precision, high performance... 

Keywords

SLAM, tracking, sensor management 

Special Session Organizers

  • Uwe D. Hanebeck, Karlsruhe Institute of Technology (Germany) 
  • Antonio Zea, Karlsruhe Institute of Technology (Germany) 
  • Florian Faion, Karlsruhe Institute of Technology (Germany) 

Special Session Contact