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Robust Cooperative Indoor Localization Based on Reliability Evaluation

delete2018-08-15
delete4
PRE
AI
T
Ting Lei
J
Jie Wang *
L
Lingyan Zhang
H
Hongyu Wang
Y
Yan Yu
DOI:10.1109/JSEN.2018.2850886delete
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摘要

摘要

En 中文
Due to the complex mixed non-line-of-sight (NLOS) and line-of-sight (LOS) propagation conditions, it is a challenging problem to achieve robust and high-performance localization in complex indoor scenarios. To solve this problem, this paper proposes a robust cooperative localization method (CLM) based on the reliability evaluation. The proposed CLM scheme lever-ages the advantages of the compressive sensing (CS) algorithm in the LOS condition and the particle filter (PF) algorithm in the NLOS condition. We propose a reliability evaluation method to evaluate the estimation results of the CS and PF algorithms, and develop a cooperative localization framework by considering the reliability when merging the estimation results. We also develop a localization system based on ultra-wideband hardware to evaluate the performance of the proposed CLM. Extensive experimental results carried out in different scenarios demonstrate the robust performance of the proposed schemes and the stability of the developed system.
Keyword:
Indoor localization
particle filter
compressive sensing
reliability evaluation
cooperative
AI总结

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对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

IEEE Sensors Journal 封面图
IEEE Sensors Journal
IF:
4.5
论文数:
2.2W
被引数:
7.3W

机构

D
Dalian University of Technology
学者数:
6.0W
论文数: 4.4W
被引数: 5.5W
D
Dalian Maritime University
学者数:
1.2W
论文数: 7.9K
被引数: 6.3K
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