ANGLE: ANGular Location Estimation Algorithms

In this paper, we present two localization algorithms that exploit the Angle of Arrival (AoA) parameters of the received signal. The proposed ANGular Location Estimation (ANGLE) algorithms utilize a probabilistic model to describe the angular response of the received signal. Consequently, the ANGLE...

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Main Authors: Noori Bnilam, Emmeric Tanghe, Jan Steckel, Wout Joseph, Maarten Weyn
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
AoA
DoA
Online Access:https://ieeexplore.ieee.org/document/8959176/
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spelling doaj-c0cbc928573d4785b879ff2c4dc5fead2021-03-30T03:08:05ZengIEEEIEEE Access2169-35362020-01-018146201462910.1109/ACCESS.2020.29665198959176ANGLE: ANGular Location Estimation AlgorithmsNoori Bnilam0https://orcid.org/0000-0001-6352-8943Emmeric Tanghe1https://orcid.org/0000-0003-0020-6466Jan Steckel2Wout Joseph3https://orcid.org/0000-0002-8807-0673Maarten Weyn4IDLab–imec Research Group, University of Antwerp, Antwerp, BelgiumWaves–imec Research Group, Ghent University, Ghent, Belgium(Cosys-Lab) Research Group, University of Antwerp, Antwerp, BelgiumWaves–imec Research Group, Ghent University, Ghent, BelgiumIDLab–imec Research Group, University of Antwerp, Antwerp, BelgiumIn this paper, we present two localization algorithms that exploit the Angle of Arrival (AoA) parameters of the received signal. The proposed ANGular Location Estimation (ANGLE) algorithms utilize a probabilistic model to describe the angular response of the received signal. Consequently, the ANGLE algorithms can estimate the location of a transmitter using a single step Hadamard product. The first algorithm utilizes a Single Sample of the received signal (ANGLE-SS). The second algorithm, on the other hand, employs the signal Subspace Decomposition technique (ANGLE-SD). The localization capabilities of the ANGLE algorithms have been experimentally investigated in an office environment. The performances of the ANGLE algorithms have been validated against the performances of several AoA-based localization systems. The experimental results show that the ANGLE-SD algorithm outperforms all the studied AoA-based localization systems. The ANGLE-SS algorithm, on the other hand, outperforms every localization system that utilizes less than 50 samples of the received signal. The ANGLE algorithms are flexible, generic and computationally very efficient. These features allow the ANGLE algorithms to be easily deployed in any existing AoA-based localization system.https://ieeexplore.ieee.org/document/8959176/Angle of arrivalAoAdirection of arrivalDoAAoA-based localization systemsindoor localization systems
collection DOAJ
language English
format Article
sources DOAJ
author Noori Bnilam
Emmeric Tanghe
Jan Steckel
Wout Joseph
Maarten Weyn
spellingShingle Noori Bnilam
Emmeric Tanghe
Jan Steckel
Wout Joseph
Maarten Weyn
ANGLE: ANGular Location Estimation Algorithms
IEEE Access
Angle of arrival
AoA
direction of arrival
DoA
AoA-based localization systems
indoor localization systems
author_facet Noori Bnilam
Emmeric Tanghe
Jan Steckel
Wout Joseph
Maarten Weyn
author_sort Noori Bnilam
title ANGLE: ANGular Location Estimation Algorithms
title_short ANGLE: ANGular Location Estimation Algorithms
title_full ANGLE: ANGular Location Estimation Algorithms
title_fullStr ANGLE: ANGular Location Estimation Algorithms
title_full_unstemmed ANGLE: ANGular Location Estimation Algorithms
title_sort angle: angular location estimation algorithms
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2020-01-01
description In this paper, we present two localization algorithms that exploit the Angle of Arrival (AoA) parameters of the received signal. The proposed ANGular Location Estimation (ANGLE) algorithms utilize a probabilistic model to describe the angular response of the received signal. Consequently, the ANGLE algorithms can estimate the location of a transmitter using a single step Hadamard product. The first algorithm utilizes a Single Sample of the received signal (ANGLE-SS). The second algorithm, on the other hand, employs the signal Subspace Decomposition technique (ANGLE-SD). The localization capabilities of the ANGLE algorithms have been experimentally investigated in an office environment. The performances of the ANGLE algorithms have been validated against the performances of several AoA-based localization systems. The experimental results show that the ANGLE-SD algorithm outperforms all the studied AoA-based localization systems. The ANGLE-SS algorithm, on the other hand, outperforms every localization system that utilizes less than 50 samples of the received signal. The ANGLE algorithms are flexible, generic and computationally very efficient. These features allow the ANGLE algorithms to be easily deployed in any existing AoA-based localization system.
topic Angle of arrival
AoA
direction of arrival
DoA
AoA-based localization systems
indoor localization systems
url https://ieeexplore.ieee.org/document/8959176/
work_keys_str_mv AT nooribnilam angleangularlocationestimationalgorithms
AT emmerictanghe angleangularlocationestimationalgorithms
AT jansteckel angleangularlocationestimationalgorithms
AT woutjoseph angleangularlocationestimationalgorithms
AT maartenweyn angleangularlocationestimationalgorithms
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