A Novel Method for Optimum Global Positioning System Satellite Selection Based on a Modified Genetic Algorithm.
In this paper, a novel method for selecting a navigation satellite subset for a global positioning system (GPS) based on a genetic algorithm is presented. This approach is based on minimizing the factors in the geometric dilution of precision (GDOP) using a modified genetic algorithm (MGA) with an e...
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Public Library of Science (PLoS)
2016-01-01
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Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC4778922?pdf=render |
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author | Jiancai Song Guixiang Xue Yanan Kang |
author_facet | Jiancai Song Guixiang Xue Yanan Kang |
author_sort | Jiancai Song |
collection | DOAJ |
description | In this paper, a novel method for selecting a navigation satellite subset for a global positioning system (GPS) based on a genetic algorithm is presented. This approach is based on minimizing the factors in the geometric dilution of precision (GDOP) using a modified genetic algorithm (MGA) with an elite conservation strategy, adaptive selection, adaptive mutation, and a hybrid genetic algorithm that can select a subset of the satellites represented by specific numbers in the interval (4 ∼ n) while maintaining position accuracy. A comprehensive simulation demonstrates that the MGA-based satellite selection method effectively selects the correct number of optimal satellite subsets using receiver autonomous integrity monitoring (RAIM) or fault detection and exclusion (FDE). This method is more adaptable and flexible for GPS receivers, particularly for those used in handset equipment and mobile phones. |
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institution | Directory Open Access Journal |
issn | 1932-6203 |
language | English |
last_indexed | 2024-12-24T00:06:10Z |
publishDate | 2016-01-01 |
publisher | Public Library of Science (PLoS) |
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spelling | doaj.art-c26b3af5f1804d3fb7ea14cea17dc5222022-12-21T17:25:00ZengPublic Library of Science (PLoS)PLoS ONE1932-62032016-01-01113e015000510.1371/journal.pone.0150005A Novel Method for Optimum Global Positioning System Satellite Selection Based on a Modified Genetic Algorithm.Jiancai SongGuixiang XueYanan KangIn this paper, a novel method for selecting a navigation satellite subset for a global positioning system (GPS) based on a genetic algorithm is presented. This approach is based on minimizing the factors in the geometric dilution of precision (GDOP) using a modified genetic algorithm (MGA) with an elite conservation strategy, adaptive selection, adaptive mutation, and a hybrid genetic algorithm that can select a subset of the satellites represented by specific numbers in the interval (4 ∼ n) while maintaining position accuracy. A comprehensive simulation demonstrates that the MGA-based satellite selection method effectively selects the correct number of optimal satellite subsets using receiver autonomous integrity monitoring (RAIM) or fault detection and exclusion (FDE). This method is more adaptable and flexible for GPS receivers, particularly for those used in handset equipment and mobile phones.http://europepmc.org/articles/PMC4778922?pdf=render |
spellingShingle | Jiancai Song Guixiang Xue Yanan Kang A Novel Method for Optimum Global Positioning System Satellite Selection Based on a Modified Genetic Algorithm. PLoS ONE |
title | A Novel Method for Optimum Global Positioning System Satellite Selection Based on a Modified Genetic Algorithm. |
title_full | A Novel Method for Optimum Global Positioning System Satellite Selection Based on a Modified Genetic Algorithm. |
title_fullStr | A Novel Method for Optimum Global Positioning System Satellite Selection Based on a Modified Genetic Algorithm. |
title_full_unstemmed | A Novel Method for Optimum Global Positioning System Satellite Selection Based on a Modified Genetic Algorithm. |
title_short | A Novel Method for Optimum Global Positioning System Satellite Selection Based on a Modified Genetic Algorithm. |
title_sort | novel method for optimum global positioning system satellite selection based on a modified genetic algorithm |
url | http://europepmc.org/articles/PMC4778922?pdf=render |
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