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Mitigating BeiDou Satellite-Induced Code Bias: Taking into Account the Stochastic Model of Corrections

The BeiDou satellite-induced code biases have been confirmed to be orbit type-, frequency-, and elevation-dependent. Such code-phase divergences (code bias variations) severely affect absolute precise applications which use code measurements. To reduce their adverse effects, an improved correction m...

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Autores principales: Guo, Fei, Li, Xin, Liu, Wanke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4934335/
https://www.ncbi.nlm.nih.gov/pubmed/27322283
http://dx.doi.org/10.3390/s16060909
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author Guo, Fei
Li, Xin
Liu, Wanke
author_facet Guo, Fei
Li, Xin
Liu, Wanke
author_sort Guo, Fei
collection PubMed
description The BeiDou satellite-induced code biases have been confirmed to be orbit type-, frequency-, and elevation-dependent. Such code-phase divergences (code bias variations) severely affect absolute precise applications which use code measurements. To reduce their adverse effects, an improved correction model is proposed in this paper. Different from the model proposed by Wanninger and Beer (2015), more datasets (a time span of almost two years) were used to produce the correction values. More importantly, the stochastic information, i.e., the precision indexes, were given together with correction values in the improved model. However, only correction values were given while the precision indexes were completely missing in the traditional model. With the improved correction model, users may have a better understanding of their corrections, especially the uncertainty of corrections. Thus, it is helpful for refining the stochastic model of code observations. Validation tests in precise point positioning (PPP) reveal that a proper stochastic model is critical. The actual precision of the corrected code observations can be reflected in a more objective manner if the stochastic model of the corrections is taken into account. As a consequence, PPP solutions with the improved model outperforms the traditional one in terms of positioning accuracy, as well as convergence speed. In addition, the Melbourne-Wübbena (MW) combination which serves for ambiguity fixing were verified as well. The uncorrected MW values show strong systematic variations with an amplitude of half a wide-lane cycle, which prevents precise ambiguity determination and successful ambiguity resolution. After application of the code bias correction models, the systematic variations can be greatly removed, and the resulting wide lane ambiguities are more likely to be fixed. Moreover, the code residuals show more reasonable distributions after code bias corrections with either the traditional or the improved model.
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spelling pubmed-49343352016-07-06 Mitigating BeiDou Satellite-Induced Code Bias: Taking into Account the Stochastic Model of Corrections Guo, Fei Li, Xin Liu, Wanke Sensors (Basel) Article The BeiDou satellite-induced code biases have been confirmed to be orbit type-, frequency-, and elevation-dependent. Such code-phase divergences (code bias variations) severely affect absolute precise applications which use code measurements. To reduce their adverse effects, an improved correction model is proposed in this paper. Different from the model proposed by Wanninger and Beer (2015), more datasets (a time span of almost two years) were used to produce the correction values. More importantly, the stochastic information, i.e., the precision indexes, were given together with correction values in the improved model. However, only correction values were given while the precision indexes were completely missing in the traditional model. With the improved correction model, users may have a better understanding of their corrections, especially the uncertainty of corrections. Thus, it is helpful for refining the stochastic model of code observations. Validation tests in precise point positioning (PPP) reveal that a proper stochastic model is critical. The actual precision of the corrected code observations can be reflected in a more objective manner if the stochastic model of the corrections is taken into account. As a consequence, PPP solutions with the improved model outperforms the traditional one in terms of positioning accuracy, as well as convergence speed. In addition, the Melbourne-Wübbena (MW) combination which serves for ambiguity fixing were verified as well. The uncorrected MW values show strong systematic variations with an amplitude of half a wide-lane cycle, which prevents precise ambiguity determination and successful ambiguity resolution. After application of the code bias correction models, the systematic variations can be greatly removed, and the resulting wide lane ambiguities are more likely to be fixed. Moreover, the code residuals show more reasonable distributions after code bias corrections with either the traditional or the improved model. MDPI 2016-06-18 /pmc/articles/PMC4934335/ /pubmed/27322283 http://dx.doi.org/10.3390/s16060909 Text en © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Guo, Fei
Li, Xin
Liu, Wanke
Mitigating BeiDou Satellite-Induced Code Bias: Taking into Account the Stochastic Model of Corrections
title Mitigating BeiDou Satellite-Induced Code Bias: Taking into Account the Stochastic Model of Corrections
title_full Mitigating BeiDou Satellite-Induced Code Bias: Taking into Account the Stochastic Model of Corrections
title_fullStr Mitigating BeiDou Satellite-Induced Code Bias: Taking into Account the Stochastic Model of Corrections
title_full_unstemmed Mitigating BeiDou Satellite-Induced Code Bias: Taking into Account the Stochastic Model of Corrections
title_short Mitigating BeiDou Satellite-Induced Code Bias: Taking into Account the Stochastic Model of Corrections
title_sort mitigating beidou satellite-induced code bias: taking into account the stochastic model of corrections
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4934335/
https://www.ncbi.nlm.nih.gov/pubmed/27322283
http://dx.doi.org/10.3390/s16060909
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