A New Type of 5G-Oriented Integrated BDS/SON High-Precision Positioning

China is promoting the construction of an integrated positioning, navigation, and timing (PNT) systems with the BeiDou Navigation Satellite System (BDS) as its core. To expand the positioning coverage area and improve the positioning performance by taking advantage of device-to-device (D2D) and self...

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Autores principales: Wenhua Tong, Decai Zou, Tao Han, Xiaozhen Zhang, Pengli Shen, Xiaochun Lu, Pengbo Wang, Ting Yin
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Lenguaje:EN
Publicado: MDPI AG 2021
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spelling oai:doaj.org-article:6a3a3ea29c5e431ca86ca2b08e818a092021-11-11T18:51:58ZA New Type of 5G-Oriented Integrated BDS/SON High-Precision Positioning10.3390/rs132142612072-4292https://doaj.org/article/6a3a3ea29c5e431ca86ca2b08e818a092021-10-01T00:00:00Zhttps://www.mdpi.com/2072-4292/13/21/4261https://doaj.org/toc/2072-4292China is promoting the construction of an integrated positioning, navigation, and timing (PNT) systems with the BeiDou Navigation Satellite System (BDS) as its core. To expand the positioning coverage area and improve the positioning performance by taking advantage of device-to-device (D2D) and self-organizing network (SON) technology, a BDS/SON integrated positioning system is proposed for the fifth-generation (5G) networking environment. This system relies on a combination of time-of-arrival (TOA) and BeiDou pseudo-range measurements to effectively supplement BeiDou signal blind spots, expand the positioning coverage area, and realize higher precision in continuous navigation and positioning. By establishing the system state model, and addressing the single-system positioning divergence and insufficient accuracy, a robust adaptive fading filtering (RAF) algorithm based on the prediction residual is proposed to suppress gross errors and filtering divergence in order to improve the stability and accuracy of the positioning results. Subsequently, a federated Kalman filtering (FKF) algorithm operating in fusion-feedback mode is developed to centrally process the positioning information of the combined system. Considering that the prediction error can reflect the magnitude of the model error, an adaptive information distribution coefficient is introduced to further improve the filtering performance. Actual measurement and significance test results show that by integrating BDS and SON positioning data, the proposed algorithm realizes robust, reliable, and continuous high precision location services with anti-interference capabilities and good universality. It is applicable in scenarios involving unmanned aerial vehicles (UAVs), autonomous driving, military, public safety and other contexts and can even realize indoor positioning and other regional positioning tasks.Wenhua TongDecai ZouTao HanXiaozhen ZhangPengli ShenXiaochun LuPengbo WangTing YinMDPI AGarticleBeidou Navigation Satellite Systemself-organizing networkrobust filteringfading filteringfederated kalman filteringScienceQENRemote Sensing, Vol 13, Iss 4261, p 4261 (2021)
institution DOAJ
collection DOAJ
language EN
topic Beidou Navigation Satellite System
self-organizing network
robust filtering
fading filtering
federated kalman filtering
Science
Q
spellingShingle Beidou Navigation Satellite System
self-organizing network
robust filtering
fading filtering
federated kalman filtering
Science
Q
Wenhua Tong
Decai Zou
Tao Han
Xiaozhen Zhang
Pengli Shen
Xiaochun Lu
Pengbo Wang
Ting Yin
A New Type of 5G-Oriented Integrated BDS/SON High-Precision Positioning
description China is promoting the construction of an integrated positioning, navigation, and timing (PNT) systems with the BeiDou Navigation Satellite System (BDS) as its core. To expand the positioning coverage area and improve the positioning performance by taking advantage of device-to-device (D2D) and self-organizing network (SON) technology, a BDS/SON integrated positioning system is proposed for the fifth-generation (5G) networking environment. This system relies on a combination of time-of-arrival (TOA) and BeiDou pseudo-range measurements to effectively supplement BeiDou signal blind spots, expand the positioning coverage area, and realize higher precision in continuous navigation and positioning. By establishing the system state model, and addressing the single-system positioning divergence and insufficient accuracy, a robust adaptive fading filtering (RAF) algorithm based on the prediction residual is proposed to suppress gross errors and filtering divergence in order to improve the stability and accuracy of the positioning results. Subsequently, a federated Kalman filtering (FKF) algorithm operating in fusion-feedback mode is developed to centrally process the positioning information of the combined system. Considering that the prediction error can reflect the magnitude of the model error, an adaptive information distribution coefficient is introduced to further improve the filtering performance. Actual measurement and significance test results show that by integrating BDS and SON positioning data, the proposed algorithm realizes robust, reliable, and continuous high precision location services with anti-interference capabilities and good universality. It is applicable in scenarios involving unmanned aerial vehicles (UAVs), autonomous driving, military, public safety and other contexts and can even realize indoor positioning and other regional positioning tasks.
format article
author Wenhua Tong
Decai Zou
Tao Han
Xiaozhen Zhang
Pengli Shen
Xiaochun Lu
Pengbo Wang
Ting Yin
author_facet Wenhua Tong
Decai Zou
Tao Han
Xiaozhen Zhang
Pengli Shen
Xiaochun Lu
Pengbo Wang
Ting Yin
author_sort Wenhua Tong
title A New Type of 5G-Oriented Integrated BDS/SON High-Precision Positioning
title_short A New Type of 5G-Oriented Integrated BDS/SON High-Precision Positioning
title_full A New Type of 5G-Oriented Integrated BDS/SON High-Precision Positioning
title_fullStr A New Type of 5G-Oriented Integrated BDS/SON High-Precision Positioning
title_full_unstemmed A New Type of 5G-Oriented Integrated BDS/SON High-Precision Positioning
title_sort new type of 5g-oriented integrated bds/son high-precision positioning
publisher MDPI AG
publishDate 2021
url https://doaj.org/article/6a3a3ea29c5e431ca86ca2b08e818a09
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