A Navigation Satellites Selection Method Based on ACO With Polarized Feedback

Selecting the optimal satellite subset for positioning from all satellites in view can not only achieve positioning accuracy but also reduce the computational burden. In this article, a navigation satellites selection method is proposed based on ant colony optimization with the improvement of polari...

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Main Authors: Huazheng Du, Yunqing Hong, Na Xia, Guofu Zhang, Yongtang Yu, Jiwen Zhang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9194229/
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author Huazheng Du
Yunqing Hong
Na Xia
Guofu Zhang
Yongtang Yu
Jiwen Zhang
author_facet Huazheng Du
Yunqing Hong
Na Xia
Guofu Zhang
Yongtang Yu
Jiwen Zhang
author_sort Huazheng Du
collection DOAJ
description Selecting the optimal satellite subset for positioning from all satellites in view can not only achieve positioning accuracy but also reduce the computational burden. In this article, a navigation satellites selection method is proposed based on ant colony optimization with the improvement of polarized feedback (ACO-PF). Firstly, the satellite selection problem is described as a combinatorial optimization problem, and the noise weighted geometric dilution of precision (NWGDOP) is defined as the criterion for satellite selection. Then the ant colony optimization (ACO) is incorporated to solve the problem, and a polarized feedback mechanism is presented to improve the convergence speed of algorithm. Meanwhile, a perturbation operator is designed to improve the global searching ability of the algorithm. The numerical experimental results show that ACO-PF can select the superior satellites combination which provides high-precision positioning. And its convergence outperforms the related algorithms by up to 50%. Besides, the achieved NWGDOP of ACO-PF is usually 0.065 smaller than ACO. Therefore, the ACO-PF method can be considered as a promising candidate for satellite selecting in navigation applications.
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spelling doaj.art-7309590434084ebe88fe0c7184096bac2022-12-21T22:02:11ZengIEEEIEEE Access2169-35362020-01-01816824616826110.1109/ACCESS.2020.30232449194229A Navigation Satellites Selection Method Based on ACO With Polarized FeedbackHuazheng Du0https://orcid.org/0000-0002-2217-8198Yunqing Hong1https://orcid.org/0000-0001-9748-6489Na Xia2https://orcid.org/0000-0001-9502-5558Guofu Zhang3https://orcid.org/0000-0002-6794-348XYongtang Yu4Jiwen Zhang5School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, ChinaSchool of Computer Science and Information Engineering, Hefei University of Technology, Hefei, ChinaSchool of Computer Science and Information Engineering, Hefei University of Technology, Hefei, ChinaSchool of Computer Science and Information Engineering, Hefei University of Technology, Hefei, ChinaChina Jikan Research Institute of Engineering Investigations and Design Company Ltd., Xi’an, ChinaChina Jikan Research Institute of Engineering Investigations and Design Company Ltd., Xi’an, ChinaSelecting the optimal satellite subset for positioning from all satellites in view can not only achieve positioning accuracy but also reduce the computational burden. In this article, a navigation satellites selection method is proposed based on ant colony optimization with the improvement of polarized feedback (ACO-PF). Firstly, the satellite selection problem is described as a combinatorial optimization problem, and the noise weighted geometric dilution of precision (NWGDOP) is defined as the criterion for satellite selection. Then the ant colony optimization (ACO) is incorporated to solve the problem, and a polarized feedback mechanism is presented to improve the convergence speed of algorithm. Meanwhile, a perturbation operator is designed to improve the global searching ability of the algorithm. The numerical experimental results show that ACO-PF can select the superior satellites combination which provides high-precision positioning. And its convergence outperforms the related algorithms by up to 50%. Besides, the achieved NWGDOP of ACO-PF is usually 0.065 smaller than ACO. Therefore, the ACO-PF method can be considered as a promising candidate for satellite selecting in navigation applications.https://ieeexplore.ieee.org/document/9194229/Ant colony optimization (ACO)noise weightedgeometric dilution of precision (GDOP)polarized feedbackperturbation operator
spellingShingle Huazheng Du
Yunqing Hong
Na Xia
Guofu Zhang
Yongtang Yu
Jiwen Zhang
A Navigation Satellites Selection Method Based on ACO With Polarized Feedback
IEEE Access
Ant colony optimization (ACO)
noise weighted
geometric dilution of precision (GDOP)
polarized feedback
perturbation operator
title A Navigation Satellites Selection Method Based on ACO With Polarized Feedback
title_full A Navigation Satellites Selection Method Based on ACO With Polarized Feedback
title_fullStr A Navigation Satellites Selection Method Based on ACO With Polarized Feedback
title_full_unstemmed A Navigation Satellites Selection Method Based on ACO With Polarized Feedback
title_short A Navigation Satellites Selection Method Based on ACO With Polarized Feedback
title_sort navigation satellites selection method based on aco with polarized feedback
topic Ant colony optimization (ACO)
noise weighted
geometric dilution of precision (GDOP)
polarized feedback
perturbation operator
url https://ieeexplore.ieee.org/document/9194229/
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