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

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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.
Publisher
International Association of Online Engineering
Issue Date
2020
Language
English
Article Type
Article
Citation

International Journal of Interactive Mobile Technologies, v.14, no.16, pp.225 - 233

ISSN
1865-7923
DOI
10.3991/ijim.v14i16.14077
URI
http://hdl.handle.net/10203/281357
Appears in Collection
RIMS Journal Papers
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