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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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 |
_version_ |
1724184019910787072 |