Development of location estimation algorithm utilizing RSSI for LoRa positioning system

LoRa is identified as Long-Range low power network technology for Low Power Wide Area Network (LPWAN) usage. Nowadays, Global Positioning System (GPS) is an important system which is used for location and navigation predominantly used in outdoor but less accurate in indoor environment. Most of LoRa...

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Main Authors: Ja'afar, Abd Shukur, Suseenthiran, Kavetha, Abd. Aziz, Mohamad Zoinol Abidin, Awang Md Isa, Azmi, Johal, Muhammad Syahrir, Hashim, Nik Mohd Zarifie
Format: Article
Language:English
Published: Penerbit UTM Press 2021
Online Access:http://eprints.utem.edu.my/id/eprint/26831/2/17153-ARTICLE%20TEXT-58499-1-10-20211219.PDF
http://eprints.utem.edu.my/id/eprint/26831/
https://journals.utm.my/jurnalteknologi/article/view/17153/7803
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spelling my.utem.eprints.268312024-06-28T15:56:46Z http://eprints.utem.edu.my/id/eprint/26831/ Development of location estimation algorithm utilizing RSSI for LoRa positioning system Ja'afar, Abd Shukur Suseenthiran, Kavetha Abd. Aziz, Mohamad Zoinol Abidin Awang Md Isa, Azmi Johal, Muhammad Syahrir Hashim, Nik Mohd Zarifie LoRa is identified as Long-Range low power network technology for Low Power Wide Area Network (LPWAN) usage. Nowadays, Global Positioning System (GPS) is an important system which is used for location and navigation predominantly used in outdoor but less accurate in indoor environment. Most of LoRa technology have been used on the internet-of-things (ioT) but very few use it as localization system. In this project, a GPS-less solution is proposed where LoRa Positioning System was developed which consists of LoRa transmitter, LoRa transceiver and LoRa receiver. The system has been developed by collecting the RSSI which is then used for the distance estimation. Next, Kalman filter with certain model has been implemented to overcome the effect of multipath fading especially for indoor environment and the trilateration technique is applied to estimate the location of the user. Both distribution estimation results for Line-Of-Sight (LOS) and Non-Line-Of-Sight (NLOS) condition were analyzed. Then, the comparison RMSE achievement is analyzed between the trilateration and with the Kalman Filter. GPS position also were collected as comparison to the LoRa based positioning. Lastly, the Cumulative Density Function (CDF) shows 90% of the localization algorithm error for LOS is lower than 0.82 meters while for NLOS is 1.17 meters. Penerbit UTM Press 2021-11 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/26831/2/17153-ARTICLE%20TEXT-58499-1-10-20211219.PDF Ja'afar, Abd Shukur and Suseenthiran, Kavetha and Abd. Aziz, Mohamad Zoinol Abidin and Awang Md Isa, Azmi and Johal, Muhammad Syahrir and Hashim, Nik Mohd Zarifie (2021) Development of location estimation algorithm utilizing RSSI for LoRa positioning system. Jurnal Teknologi, 84 (1). pp. 97-105. ISSN 2180-3722 https://journals.utm.my/jurnalteknologi/article/view/17153/7803 10.11113/jurnalteknologi.v84.17153
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
description LoRa is identified as Long-Range low power network technology for Low Power Wide Area Network (LPWAN) usage. Nowadays, Global Positioning System (GPS) is an important system which is used for location and navigation predominantly used in outdoor but less accurate in indoor environment. Most of LoRa technology have been used on the internet-of-things (ioT) but very few use it as localization system. In this project, a GPS-less solution is proposed where LoRa Positioning System was developed which consists of LoRa transmitter, LoRa transceiver and LoRa receiver. The system has been developed by collecting the RSSI which is then used for the distance estimation. Next, Kalman filter with certain model has been implemented to overcome the effect of multipath fading especially for indoor environment and the trilateration technique is applied to estimate the location of the user. Both distribution estimation results for Line-Of-Sight (LOS) and Non-Line-Of-Sight (NLOS) condition were analyzed. Then, the comparison RMSE achievement is analyzed between the trilateration and with the Kalman Filter. GPS position also were collected as comparison to the LoRa based positioning. Lastly, the Cumulative Density Function (CDF) shows 90% of the localization algorithm error for LOS is lower than 0.82 meters while for NLOS is 1.17 meters.
format Article
author Ja'afar, Abd Shukur
Suseenthiran, Kavetha
Abd. Aziz, Mohamad Zoinol Abidin
Awang Md Isa, Azmi
Johal, Muhammad Syahrir
Hashim, Nik Mohd Zarifie
spellingShingle Ja'afar, Abd Shukur
Suseenthiran, Kavetha
Abd. Aziz, Mohamad Zoinol Abidin
Awang Md Isa, Azmi
Johal, Muhammad Syahrir
Hashim, Nik Mohd Zarifie
Development of location estimation algorithm utilizing RSSI for LoRa positioning system
author_facet Ja'afar, Abd Shukur
Suseenthiran, Kavetha
Abd. Aziz, Mohamad Zoinol Abidin
Awang Md Isa, Azmi
Johal, Muhammad Syahrir
Hashim, Nik Mohd Zarifie
author_sort Ja'afar, Abd Shukur
title Development of location estimation algorithm utilizing RSSI for LoRa positioning system
title_short Development of location estimation algorithm utilizing RSSI for LoRa positioning system
title_full Development of location estimation algorithm utilizing RSSI for LoRa positioning system
title_fullStr Development of location estimation algorithm utilizing RSSI for LoRa positioning system
title_full_unstemmed Development of location estimation algorithm utilizing RSSI for LoRa positioning system
title_sort development of location estimation algorithm utilizing rssi for lora positioning system
publisher Penerbit UTM Press
publishDate 2021
url http://eprints.utem.edu.my/id/eprint/26831/2/17153-ARTICLE%20TEXT-58499-1-10-20211219.PDF
http://eprints.utem.edu.my/id/eprint/26831/
https://journals.utm.my/jurnalteknologi/article/view/17153/7803
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score 13.160551