Multi-Source Data Fusion Method for Indoor Localization System

Jishi Cui; Bin Li; Lyuxiao Yang; Nan Wu

doi:10.1109/ICCC49849.2020.9238826

Multi-Source Data Fusion Method for Indoor Localization System

Jishi Cui, Bin Li^*, Lyuxiao Yang, Nan Wu

^*Corresponding author for this work

Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

In this paper, a multi-source data fusion method for indoor localization system is designed to realize the high-accuracy locations. The indoor localization system consists of WiFi nodes, ultra-wideband (UWB) nodes and inertial measurement unit (IMU), where the IMU is integrated in a android smartphone. For our indoor localization system, there include two stages: offline stage and online stage. In the offline stage, we use crowdsourcing method to train a fingerprint database, which can be constructed at a low labor cost. In the online stage, particle filter to estimate the locations based on WiFi received signal strengths, UWB rangings, and IMU data. Experimental results show that our indoor localization system based on the multi-source data fusion method expands the coverage and improves the localization accuracy.

Original language	English
Title of host publication	2020 IEEE/CIC International Conference on Communications in China, ICCC 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	29-33
Number of pages	5
ISBN (Electronic)	9781728173276
DOIs	https://doi.org/10.1109/ICCC49849.2020.9238826
Publication status	Published - 9 Aug 2020
Event	2020 IEEE/CIC International Conference on Communications in China, ICCC 2020 - Chongqing, China Duration: 9 Aug 2020 → 11 Aug 2020

Publication series

Name	2020 IEEE/CIC International Conference on Communications in China, ICCC 2020

Conference

Conference	2020 IEEE/CIC International Conference on Communications in China, ICCC 2020
Country/Territory	China
City	Chongqing
Period	9/08/20 → 11/08/20

Keywords

Indoor localization
crowdsourcing method
multi-source data fusion
particle filter

Access to Document

10.1109/ICCC49849.2020.9238826

Cite this

Cui, J., Li, B., Yang, L., & Wu, N. (2020). Multi-Source Data Fusion Method for Indoor Localization System. In 2020 IEEE/CIC International Conference on Communications in China, ICCC 2020 (pp. 29-33). Article 9238826 (2020 IEEE/CIC International Conference on Communications in China, ICCC 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCC49849.2020.9238826

@inproceedings{4dc46a55bf804f80a5d5a56d1901d202,

title = "Multi-Source Data Fusion Method for Indoor Localization System",

abstract = "In this paper, a multi-source data fusion method for indoor localization system is designed to realize the high-accuracy locations. The indoor localization system consists of WiFi nodes, ultra-wideband (UWB) nodes and inertial measurement unit (IMU), where the IMU is integrated in a android smartphone. For our indoor localization system, there include two stages: offline stage and online stage. In the offline stage, we use crowdsourcing method to train a fingerprint database, which can be constructed at a low labor cost. In the online stage, particle filter to estimate the locations based on WiFi received signal strengths, UWB rangings, and IMU data. Experimental results show that our indoor localization system based on the multi-source data fusion method expands the coverage and improves the localization accuracy.",

keywords = "Indoor localization, crowdsourcing method, multi-source data fusion, particle filter",

author = "Jishi Cui and Bin Li and Lyuxiao Yang and Nan Wu",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE/CIC International Conference on Communications in China, ICCC 2020 ; Conference date: 09-08-2020 Through 11-08-2020",

year = "2020",

month = aug,

day = "9",

doi = "10.1109/ICCC49849.2020.9238826",

language = "English",

series = "2020 IEEE/CIC International Conference on Communications in China, ICCC 2020",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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booktitle = "2020 IEEE/CIC International Conference on Communications in China, ICCC 2020",

address = "United States",

}

Cui, J, Li, B, Yang, L & Wu, N 2020, Multi-Source Data Fusion Method for Indoor Localization System. in 2020 IEEE/CIC International Conference on Communications in China, ICCC 2020., 9238826, 2020 IEEE/CIC International Conference on Communications in China, ICCC 2020, Institute of Electrical and Electronics Engineers Inc., pp. 29-33, 2020 IEEE/CIC International Conference on Communications in China, ICCC 2020, Chongqing, China, 9/08/20. https://doi.org/10.1109/ICCC49849.2020.9238826

Multi-Source Data Fusion Method for Indoor Localization System. / Cui, Jishi; Li, Bin; Yang, Lyuxiao et al.
2020 IEEE/CIC International Conference on Communications in China, ICCC 2020. Institute of Electrical and Electronics Engineers Inc., 2020. p. 29-33 9238826 (2020 IEEE/CIC International Conference on Communications in China, ICCC 2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Multi-Source Data Fusion Method for Indoor Localization System

AU - Cui, Jishi

AU - Li, Bin

AU - Yang, Lyuxiao

AU - Wu, Nan

PY - 2020/8/9

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N2 - In this paper, a multi-source data fusion method for indoor localization system is designed to realize the high-accuracy locations. The indoor localization system consists of WiFi nodes, ultra-wideband (UWB) nodes and inertial measurement unit (IMU), where the IMU is integrated in a android smartphone. For our indoor localization system, there include two stages: offline stage and online stage. In the offline stage, we use crowdsourcing method to train a fingerprint database, which can be constructed at a low labor cost. In the online stage, particle filter to estimate the locations based on WiFi received signal strengths, UWB rangings, and IMU data. Experimental results show that our indoor localization system based on the multi-source data fusion method expands the coverage and improves the localization accuracy.

AB - In this paper, a multi-source data fusion method for indoor localization system is designed to realize the high-accuracy locations. The indoor localization system consists of WiFi nodes, ultra-wideband (UWB) nodes and inertial measurement unit (IMU), where the IMU is integrated in a android smartphone. For our indoor localization system, there include two stages: offline stage and online stage. In the offline stage, we use crowdsourcing method to train a fingerprint database, which can be constructed at a low labor cost. In the online stage, particle filter to estimate the locations based on WiFi received signal strengths, UWB rangings, and IMU data. Experimental results show that our indoor localization system based on the multi-source data fusion method expands the coverage and improves the localization accuracy.

KW - Indoor localization

KW - crowdsourcing method

KW - multi-source data fusion

KW - particle filter

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DO - 10.1109/ICCC49849.2020.9238826

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ER -

Multi-Source Data Fusion Method for Indoor Localization System

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