On the generation algorithm of VRS virtual observations

Wei, Erhu; Chai, Hongzhou; Liu, Jingnan; An, Zhiguo

doi:10.1007/s11806-007-0021-4

Cited by 3 publications

(4 citation statements)

References 2 publications

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“…According to recent analysis, the length ofRTK baselines can be extended to at least 50 km when using VRS technology [8]. A horizontal accuracy of less than 2 cm, 2.4 cm and 4.4 cm over 20.7 km, 44.8 km and 62.5 km length baseline, respectively, can be achieved [9].…”

Section: Reviewofvrsalgorithmsmentioning

confidence: 99%

Analysis of the Impact of Virtual Reference Stations on Static Positioning

Kalita

Rzepecka

2014

The 9th International Conference "Environmental Engineering 2014"

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The aim of this work was to study the influence of artificial GPS observations, obtained by the Virtual Reference Station (VRS) technique on static positioning results in post-processing mode. The accuracy of positioning using VRS stations was investigated. Precise static determinations were analyzed. The VRS data were obtained from the POZGEO-D service of the ASG-EUPOS network. Test computations were performed with Leica GeoOffice and Ashtech Office Suite GPS software. The discussion of results is preceded by a general description of the VRS method and algorithms. The bulk of the paper is of practical character, it derives some advices to the users of active permanent networks like the EUPOS system. The last part of the paper is devoted to analyses of the virtual observations.

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Section: Reviewofvrsalgorithmsmentioning

confidence: 99%

Analysis of the Impact of Virtual Reference Stations on Static Positioning

Kalita

Rzepecka

2014

The 9th International Conference "Environmental Engineering 2014"

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“…In the original data center-based differential positioning (DCDP) method, each base station transmits the observed data to the data center continuously, the data center can obtain its synthesized difference value in view of the minimum variance or the weighted average algorithm according to multiple reference station observations [6]. After the error deviation is calculated, the data center broadcasts the deviation data to mobile receivers.…”

Section: Introductionmentioning

confidence: 99%

Edge Computing-based Differential Positioning Method for BeiDou Navigation Satellite System

Wang¹,

Li²,

Qiu³

2019

KSII TIIS

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BeiDou navigation satellite system (BDS) is one of the four main types of global navigation satellite systems. The current system has been widely used by the military and by the aerospace, transportation, and marine fields, among others. However, challenges still remain in the BeiDou system, which requires rapid responses for delay-sensitive devices. A differential positioning algorithm called the data center-based differential positioning (DCDP) method is widely used to avoid the influence of errors. In this method, the positioning information of multiple base stations is uploaded to the data center, and the positioning errors are calculated uniformly by the data center based on the minimum variance or a weighted average algorithm. However, the DCDP method has high delay and overload risk. To solve these problems, this paper introduces edge computing to relieve pressure on the data center. Instead of transmitting the positioning information to the data center, a novel method called edge computing-based differential positioning (ECDP) chooses the nearest reference station to perform edge computing and transmits the difference value to the mobile receiver directly. Simulation results and experiments demonstrate that the performance of the ECDP outperforms that of the DCDP method. The delay of the ECDP method is about 500ms less than that of the DCDP method. Moreover, in the range of allowable burst error, the median of the positioning accuracy of the ECDP method is 0.7923m while that of the DCDP method is 0.8028m.

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“…Existem diversas formas de se calcular as observações da estação de referência virtual (Van der MAREL, 1998;HU et al, 2003;WANNINGER, 2006;WEI et al, 2007;ALVES, 2008;MORETT NETTO, 2008). De modo geral são necessárias três etapas: deslocamento geométrico (DG), modelagem da atmosfera a partir das estações da rede de referência e interpolação dos erros calculados para a posição da estação de referência virtual.…”

Section: Z Uunclassified

“…Dentre as técnicas de posicionamento utilizando os sistemas de navegação por satélite globais (GNSS -Global Navigation Satellite Systems), merece destaque a que utiliza dados de uma rede de estações GNSS para gerar estações de referência virtuais. Desde que as estações da rede não estejam separadas por mais de 100 km e o receptor do usuário esteja dentro da região interna à rede de referência, esta técnica de posicionamento pode proporcionar posicionamento com precisão melhor que 10 cm a usuários de receptores de (WANNINGER, 1995, HAN;RIZOS, 1998;RAQUET, 1998, FORTES, 2003 HU et al, 2003;WANNINGER, 2006;WEI et al, 2007 SANZ, 1997;CANDER et al,1998;TULUNAY et al, 2006;HABARULEMA;MCKINNELL;CILLIERS, 2007;ACHARYA et al, 2011 (FORTES et al, 2000;WILLGALIS et al, 2002;SEJAS et al, 2003;RAMOS, 2007;ALVES, 2008, MORETT NETTO, 2008MONICO, 2011 sendo v k denominado de campo local induzido ou potencial de ativação.…”

Section: Introductionunclassified

Utilização de redes neurais artificiais na previsão do VTEC visando a geração de estações de referência virtuais em tempo-real.

Machado¹

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On the generation algorithm of VRS virtual observations

Cited by 3 publications

References 2 publications

Analysis of the Impact of Virtual Reference Stations on Static Positioning

Analysis of the Impact of Virtual Reference Stations on Static Positioning

Edge Computing-based Differential Positioning Method for BeiDou Navigation Satellite System

Utilização de redes neurais artificiais na previsão do VTEC visando a geração de estações de referência virtuais em tempo-real.

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