Accuracy improvement of RSSI-based distance localization using unscented kalman filter (UKF) algorithm for wi-fi tracking application

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Syifaul Fuada, Trio Adiono, Prasetiyo

2020 International Journal of Interactive Mobile Technologies Vol. 14 Issue 16 Article Cited by 9 SDG 17SDG 9SDG 16 Quartile

Abstract

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. © 2020 by the authors.

Affiliations

Universitas Pendidikan Indonesia, Bandung, Indonesia; Institut Teknologi Bandung, Bandung, Indonesia; Korea Advanced Institute of Science and Technology, Daejeon, South Korea

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