An enhanced trilateration algorithm for indoor RSSI based positioning system using zigbee protocol

Ainul, Rafina Destiarti (2022) An enhanced trilateration algorithm for indoor RSSI based positioning system using zigbee protocol. Jurnal Infotel (Informatics, Telecommunication, and Electronics), 14 (4). pp. 301-306. ISSN 2085-3688, e-ISSN : 2460-0997

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Abstract

The location information of the object based on wireless communication has a significant role in several Wireless Sensor Network (WSN) applications. Some applications require the appropriate details on the object’s position. The advantages of Zigbee as part of Radio Frequency (RF) technology include inexpensive, broad scalability, sufficient availability, and suitability for Indoor Positioning System (IPS) topology. In this paper, we propose IPS using a Received Signal Strength Indicator (RSSI) based Zigbee protocol. The proposed approach is based on the enhancement of the Trilateration algorithm. The main concept of conventional trilateration is using the three strongest RSSI from the reference node. However, the instability from measured RSSI influenced its estimation result. Therefore, quadratic weighted is added to this proposed scheme as the enhanced trilateration algorithm. The estimated distance output from the conventional trilateration algorithm will be recalculated for the weighted value and multiplied by each reference node, producing a lower estimation error. The simulation result shows that using an enhanced trilateration algorithm can improve the accuracy level of estimated position up to 90.55% with mean square error (MSE) of 2.03 meters stacked up with only using conventional trilateration is attained high estimated error up to 4.31 meters. Keywords – Conventional trilateration, enhanced trilateration, indoor positioning system, MSE, RSSI

Item Type:	Article
Uncontrolled Keywords:	Conventional trilateration, enhanced trilateration, indoor positioning system, MSE, RSSI
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Faculty of Engineering > Department of Electrical Engineering
Depositing User:	RAFINA DESTIARTI AINUL
Date Deposited:	02 Dec 2022 02:24
Last Modified:	26 Jan 2023 08:45
URI:	http://repository.ubaya.ac.id/id/eprint/42917

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