Alwin, PouloseOdongo, Steven EyobuHan, Dong Seog2023-02-192023-02-192019Poulose, A., Eyobu, O. S., & Han, D. S. (2019, February). A combined PDR and Wi-Fi trilateration algorithm for indoor localization. In 2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) (pp. 072-077). IEEE.978-1-5386-7822-0https://nru.uncst.go.ug/handle/123456789/7883Indoor localization using Wi-Fi or pedes- trian dead reckoning (PDR) has several limitations in terms of Wi-Fi signal fluctuations and PDR drift errors. To overcome these limitations, we propose a sensor fusion framework for Wi-Fi and PDR systems. The pro- posed sensor fusion will overcome the PDR drift errors by analysing the Wi-Fi signal strength and the PDR results will compensate the Wi-Fi signal fluctuations. Based on the experiments conducted, results show that the proposed fusion indoor positioning algorithm shows high position accuracy over Wi-Fi localization and PDR systems when used independently. Our proposed combined position estimation algorithm achieves an improved average localization accuracy of 1.6 m when compared to the Wi-Fi and PDR systems when used independently.enIndoor localizationWi-FiSmart phoneQuaternionKalman filterSensor fusionPedes- trian dead reckoning (PDR)Android-based smart- phoneTrilaterationRSSIOther