some fixes/comments to introducton/related-work

tex/chapters/relatedwork.tex

@@ -3,7 +3,7 @@
 
 Like mentioned before, most state-of-the-art systems use recursive state estimators like Kalman- and particle filters.
 They differ mainly by the sensors used, their probabilistic models and how the environmental information are incorporated.
-For example \cite{Li2015} recently presented an approach combining methods of pedestrian dead reckoning (PDR), Wi-Fi
+For example \cite{Li2015} recently presented an approach combining methods of pedestrian dead reckoning (PDR), \docWIFI{}
 fingerprinting and magnetic matching using a Kalman filter. While providing good results, fingerprinting methods
 require an extensive offline calibration phase. Therefore, many other systems like \cite{Fang09} or \cite{Ebner-15}
 are using signal strength prediction models like the log-distance model or wall-attenuation-factor model.