A Loose Coupled Fusion of Inertial and UWB Assisted by a Decision Making Algorithm for Localization of Emergency Responders
Combining different technologies is gaining significant popularity among researchers and industry for the development of indoor positioning systems (IPSs) These hybrid IPSs emerge as a robust solution for indoor localization as the drawbacks of each technology can be mitigated or even eliminated by using complementary technologies. However, fusing position estimates from different technologies is still very challenging and, therefore, a hot research topic. In this work, we pose fusing the ultrawideband (UWB) position estimates with the estimates provided by a pedestrian dead reckoning (PDR) by using a Kalman filter. To improve the IPS accuracy, a decision making algorithm was developed that aims to assess the usability of UWB measurements based on the identification of non line of sight (NLOS) conditions. Three different data fusion algorithms are tested, based on three different time of arrival positioning algorithms, and experimental results show a localization accuracy of below 1.5 m for a 99th percentile.