Blind Robust Multi-Horizon EFIR Filter for Tightly Integrating INS and UWB

Yuan Xu; Yuriy S. Shmaliy; Choon Ki Ahn; Xiyuan Chen; Hang Guo; Yuan Zhuang

doi:10.1109/JSEN.2021.3105566

Blind Robust Multi-Horizon EFIR Filter for Tightly Integrating INS and UWB

Yuan Xu, Yuriy S. Shmaliy, Choon Ki Ahn, Xiyuan Chen, Hang Guo, Yuan Zhuang

Research output: Contribution to journal › Article › peer-review

Abstract

In this paper, a novel model to localize a human accurately in indoor industrial environments by integrating the inertial navigation system (INS) technique with ultra wide band (UWB) technology is present. The distances between the target human and the reference node measured from INS and UWB are used by the fusion filter. To improve accuracy, the robust extended finite impulse response (EFIR) filtering algorithm is developed to operate on multi horizons (MHs), thereby providing blind suboptimal estimates. Experimental testing has shown that the real-time blind MH EFIR algorithm is almost as accurate as the EFIR filter, which requires a preliminarily determined optimal horizon.

Original language	English
Pages (from-to)	23037-23045
Number of pages	9
Journal	IEEE Sensors Journal
Volume	21
Issue number	20
DOIs	https://doi.org/10.1109/JSEN.2021.3105566
Publication status	Published - 2021 Oct 15

Keywords

extended FIR filter
Indoor localization scheme
multi-horizon
tightly integration

ASJC Scopus subject areas

Instrumentation
Electrical and Electronic Engineering

Access to Document

10.1109/JSEN.2021.3105566

Cite this

@article{75f1f77e4b66422298a28b664ae80a1d,

title = "Blind Robust Multi-Horizon EFIR Filter for Tightly Integrating INS and UWB",

abstract = "In this paper, a novel model to localize a human accurately in indoor industrial environments by integrating the inertial navigation system (INS) technique with ultra wide band (UWB) technology is present. The distances between the target human and the reference node measured from INS and UWB are used by the fusion filter. To improve accuracy, the robust extended finite impulse response (EFIR) filtering algorithm is developed to operate on multi horizons (MHs), thereby providing blind suboptimal estimates. Experimental testing has shown that the real-time blind MH EFIR algorithm is almost as accurate as the EFIR filter, which requires a preliminarily determined optimal horizon.",

keywords = "extended FIR filter, Indoor localization scheme, multi-horizon, tightly integration",

author = "Yuan Xu and Shmaliy, {Yuriy S.} and Ahn, {Choon Ki} and Xiyuan Chen and Hang Guo and Yuan Zhuang",

note = "Funding Information: This work was supported in part by the National Natural Science Foundation of China under Grant 61803175, in part by the Mexican Consejo Nacional de Ciencia y Tecnolog a Project A1-S-10287 under Grant CB2017-2018, and in part by the National Research Foundation of Korea (NRF) grant funded by the Korea Government (Ministry of Science and ICT) under Grant NRF-2020R1A2C1005449. Publisher Copyright: {\textcopyright} 2001-2012 IEEE.",

year = "2021",

month = oct,

day = "15",

doi = "10.1109/JSEN.2021.3105566",

language = "English",

volume = "21",

pages = "23037--23045",

journal = "IEEE Sensors Journal",

issn = "1530-437X",

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

number = "20",

}

TY - JOUR

T1 - Blind Robust Multi-Horizon EFIR Filter for Tightly Integrating INS and UWB

AU - Xu, Yuan

AU - Shmaliy, Yuriy S.

AU - Ahn, Choon Ki

AU - Chen, Xiyuan

AU - Guo, Hang

AU - Zhuang, Yuan

N1 - Funding Information: This work was supported in part by the National Natural Science Foundation of China under Grant 61803175, in part by the Mexican Consejo Nacional de Ciencia y Tecnolog a Project A1-S-10287 under Grant CB2017-2018, and in part by the National Research Foundation of Korea (NRF) grant funded by the Korea Government (Ministry of Science and ICT) under Grant NRF-2020R1A2C1005449. Publisher Copyright: © 2001-2012 IEEE.

PY - 2021/10/15

Y1 - 2021/10/15

N2 - In this paper, a novel model to localize a human accurately in indoor industrial environments by integrating the inertial navigation system (INS) technique with ultra wide band (UWB) technology is present. The distances between the target human and the reference node measured from INS and UWB are used by the fusion filter. To improve accuracy, the robust extended finite impulse response (EFIR) filtering algorithm is developed to operate on multi horizons (MHs), thereby providing blind suboptimal estimates. Experimental testing has shown that the real-time blind MH EFIR algorithm is almost as accurate as the EFIR filter, which requires a preliminarily determined optimal horizon.

AB - In this paper, a novel model to localize a human accurately in indoor industrial environments by integrating the inertial navigation system (INS) technique with ultra wide band (UWB) technology is present. The distances between the target human and the reference node measured from INS and UWB are used by the fusion filter. To improve accuracy, the robust extended finite impulse response (EFIR) filtering algorithm is developed to operate on multi horizons (MHs), thereby providing blind suboptimal estimates. Experimental testing has shown that the real-time blind MH EFIR algorithm is almost as accurate as the EFIR filter, which requires a preliminarily determined optimal horizon.

KW - extended FIR filter

KW - Indoor localization scheme

KW - multi-horizon

KW - tightly integration

UR - http://www.scopus.com/inward/record.url?scp=85113195568&partnerID=8YFLogxK

U2 - 10.1109/JSEN.2021.3105566

DO - 10.1109/JSEN.2021.3105566

M3 - Article

AN - SCOPUS:85113195568

SN - 1530-437X

VL - 21

SP - 23037

EP - 23045

JO - IEEE Sensors Journal

JF - IEEE Sensors Journal

IS - 20

ER -

Blind Robust Multi-Horizon EFIR Filter for Tightly Integrating INS and UWB

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this