An effective indoor positioning system by modified linearized least square approach using UWB technology

被引:0
|
作者
Al-NussairiAhmed Kateb Jumaah
Wahidah Hashim
A. K. Alami
机构
[1] Universiti Tenaga Nasional,College of Computing and Informatics
[2] Al-Manara College for Medical Sciences,undefined
来源
Applied Geomatics | 2024年 / 16卷
关键词
UWB; IPS; Localization; Wireless sensor network (WSN);
D O I
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中图分类号
学科分类号
摘要
Ultra-wideband is among the key radio spectrums that can be utilized for indoor localization. It is a short-range radio frequency (RF) spectrum that can be utilized to locate the exact position of devices, people, and assets for wireless communication. However, it has a significant limitation in that it requires a non-line-of-sight (NLOS) mitigation and identification techniques to precisely locate a mobile station in a hard indoor environment (more obstacles) between the anchor nodes and mobile station. The NLOS approach will make positioning more difficult. The goals of this work are (i) to find the minimum required number of anchor nodes for cost and time saving have been fixed; (ii) to ensure that the designed system’s precision is maintained, it must be compatible with a variety of indoor conditions. In this paper, we develop a novel indoor positioning system algorithm called enhanced linearized least square (ELLS) that employs UWB technology without relying on an NLOS credentials technique. In this paper, we use real-world trials to test and validate the system we have developed. The developed system does have a mean positioning accuracy of 0.46 m2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathrm{m}}^{2}$$\end{document} of mean square error (MSE) in a harsh environment. It surpasses the majority of indoor positioning systems currently available while being less complex, less expensive, and more accurate.
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页码:17 / 28
页数:11
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