A RSS-based localization method using HMM-based error correction

IF 1.2 Q4 TELECOMMUNICATIONS

Journal of Location Based Services Pub Date : 2018-10-02 DOI:10.1080/17489725.2018.1535140

Ahmad Alabadleh, Saqer Aljaafreh, A. Aljaafreh, K. Alawasa

引用次数: 12

Abstract

ABSTRACT Indoor localization and tracking systems are harvesting more attention from the researchers. Recently, several approaches for localization systems have been proposed that use the sensors which are available on smartphones. In this paper, a new filtering approach based on Hidden Markov Model (HMM) techniques to enhance the accuracy of the localization system is presented. The proposed approach filtered out the undesirable Received Signal Strength (RSS) values which affect the accuracy of the system using the hidden states. The proposed approach helps in the direction and the distance estimation. The results of the proposed approach show a significant improvement in terms of distance estimation and the filtering of the RSS values.

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基于HMM纠错的RSS定位方法

摘要室内定位和跟踪系统越来越受到研究者的关注。最近，已经提出了几种使用智能手机上可用的传感器的定位系统的方法。本文提出了一种新的基于隐马尔可夫模型（HMM）技术的滤波方法，以提高定位系统的精度。所提出的方法使用隐藏状态过滤掉了影响系统精度的不期望的接收信号强度（RSS）值。所提出的方法有助于方向和距离估计。所提出的方法的结果在距离估计和RSS值的滤波方面显示出显著的改进。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Location Based Services TELECOMMUNICATIONS-

CiteScore

3.70

自引率

8.70%

发文量

期刊介绍： The aim of this interdisciplinary and international journal is to provide a forum for the exchange of original ideas, techniques, designs and experiences in the rapidly growing field of location based services on networked mobile devices. It is intended to interest those who design, implement and deliver location based services in a wide range of contexts. Published research will span the field from location based computing and next-generation interfaces through telecom location architectures to business models and the social implications of this technology. The diversity of content echoes the extended nature of the chain of players required to make location based services a reality.