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

Authors

  • Syifaul Fuada Universitas Pendidikan Indonesia https://orcid.org/0000-0002-5258-5149
  • Trio Adiono University Center of Excellence on Microelectronics, Institut Teknologi Bandung, Indonesia
  • Prasetiyo Prasetiyo School of Electrical Engineering, Korea Advanced Institute of Science and Technology

DOI:

https://doi.org/10.3991/ijim.v14i16.14077

Keywords:

Unscented Kalman Filter (UKF), RSSI-based Distance Localization, Wi-Fi Tracking System

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.

Author Biographies

Syifaul Fuada, Universitas Pendidikan Indonesia

Syifaul Fuada is with the Program Studi Sistem Telekomunikasi Universitas Pendidikan Indonesia (UPI) as a Lecturer. His research interests include analog circuit design and instrumentation, circuit simulation, engineering education, IoT, multimedia learning development and Visible Light Communication.

Trio Adiono, University Center of Excellence on Microelectronics, Institut Teknologi Bandung, Indonesia

Trio Adiono is a Full professor and a senior lecturer at the School of Electrical Engineering and Informatics, and formerly serves as the Head of the Microelectronics Center, Institut Teknologi Bandung. His research interests include VLSI design, signal and image processing, VLC, smart cards, and electronics solution design and integration.

Prasetiyo Prasetiyo, School of Electrical Engineering, Korea Advanced Institute of Science and Technology

Prasetiyo received the B.S. degree in electrical engineering from Institut Teknologi Bandung, Indonesia, in 2015. Currently, he is master student at Korea Advanced Institute of Science and Technology. His research interests include Wireless communication, VLSI, analog integrated circuits design, and CMOS technology.

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Published

2020-09-22

How to Cite

Fuada, S., Adiono, T., & Prasetiyo, P. (2020). Accuracy Improvement of RSSI-based Distance Localization using Unscented Kalman Filter (UKF) Algorithm for Wi-Fi Tracking Application. International Journal of Interactive Mobile Technologies (iJIM), 14(16), pp. 225–233. https://doi.org/10.3991/ijim.v14i16.14077

Issue

Vol. 14 No. 16 (2020)

Section

Short Papers