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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IEEE
2020-01-01
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Series: | IEEE Access |
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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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format | Article |
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issn | 2169-3536 |
language | English |
last_indexed | 2024-12-17T05:13:24Z |
publishDate | 2020-01-01 |
publisher | IEEE |
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series | IEEE Access |
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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