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

• Main Authors: Syifaul Fuada, Trio Adiono, Prasetiyo Prasetiyo
• Format: Article
• Language: English
• Published: International Association of Online Engineering (IAOE) 2020-09-01
• Series: International Journal of Interactive Mobile Technologies
• Subjects: unscented kalman filter (ukf), rssi-based distance localization, wi-fi tracking system
• Online Access: https://online-journals.org/index.php/i-jim/article/view/14077

<p class="0abstract">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.</p>