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

被引:4
|
作者
Fuada S. [1 ]
Adiono T. [2 ]
Prasetiyo [3 ]
机构
[1] Universitas Pendidikan Indonesia, Bandung
[2] Institut Teknologi Bandung, Bandung
[3] Korea Advanced Institute of Science and Technology, Daejeon
关键词
RSSI-based distance localization; Unscented kalman filter (UKF); Wi-fi tracking system;
D O I
10.3991/ijim.v14i16.14077
中图分类号
TN713 [滤波技术、滤波器];
学科分类号
摘要
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.
引用
收藏
页码:225 / 233
页数:8
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