Accuracy Improvement of RSSI-based Distance Localization using Unscented Kalman Filter (UKF) Algorithm for Wi-Fi Tracking Application

Syifaul Fuada, Trio Adiono, Prasetiyo Prasetiyo


In this report, we perform the digital filter computation using Matlab for Wi-Fi tracking application. This work motivates to improve the accuracy of filter algorithm in the RSSI-based distance localization system. There are several aspects that we can improve, e.g., in the Filter part and Path-loss model. But, in this work, we focus on filter part; Unscented Kalman Filter (UKF) is implemented to replace linear Kalman Filter (KF), which is used in previous work. Based on the performance comparison, UKF has 90% hit ratio while linear KF has only 81.15 % hit ratio. We found that UKF can handle the noise in RSSI. Further work, the UKF algorithm is then embedded on the server system.


Unscented Kalman Filter (UKF), RSSI-based Distance Localization, Wi-Fi Tracking System

Full Text:


International Journal of Interactive Mobile Technologies (iJIM) – eISSN: 1865-7923
Creative Commons License
Scopus logo IET Inspec logo DBLP logo EBSCO logo Ulrich's logo MAS logo