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

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

Unscented Kalman Filter (UKF)

RSSI-based Distance Localization

Wi-Fi Tracking System

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.

Fuada, Syifaul

Adiono, Trio

Prasetiyo, Prasetiyo

International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 16 (2020); pp. 225-233

1865-7923

International Association of Online Engineering (IAOE), Vienna, Austria

2020-09-22

Copyright (c) 2020 Syifaul Fuada, Trio Adiono, Prasetiyo Prasetiyo

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eng

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Non-refereed Article