WARTK Fundamentals - Revision history

Claudia.Prajanu at 12:19, 27 July 2018

2018-07-27T12:19:09Z

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	The '''Wide Area RTK''' concept was introduced in the late 1990s to address RTK deficiencies by the [http://www.gage.es/ Research Group of Astronomy and Geomatics (gAGE)] from the Technical University of Catalonia (UPC). The WARTK method increases the RTK/NRTK service area, with permanent reference stations separated by up to 500–900 kilometers, this implies requiring 100 to 1,000 times fewer baselines than RTK technique to cover a given region.<ref>[http://~~www.~~insidegnss.com/~~node~~/~~1917~~ Hernández-Pajares, et al, ''Wide-Area RTK: High Precision Positioning on a Continental Scale'', Inside GNSS, March/April 2010.]</ref>		The '''Wide Area RTK''' concept was introduced in the late 1990s to address RTK deficiencies by the [http://www.gage.es/ Research Group of Astronomy and Geomatics (gAGE)] from the Technical University of Catalonia (UPC). The WARTK method increases the RTK/NRTK service area, with permanent reference stations separated by up to 500–900 kilometers, this implies requiring 100 to 1,000 times fewer baselines than RTK technique to cover a given region.<ref>[http://insidegnss.com/wide-area-rtk/ Hernández-Pajares, et al, ''Wide-Area RTK: High Precision Positioning on a Continental Scale'', Inside GNSS, March/April 2010.]</ref>

	==WARTK Technique==		==WARTK Technique==

Filipe.Pelica: Included editor logo.

2014-09-18T17:13:36Z

Included editor logo.

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	\|YearOfPublication=2011		\|YearOfPublication=2011
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Filipe.Pelica: fixed broken link.

2014-09-12T14:34:18Z

fixed broken link.

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	[[File:Wartk gAGEUPC.jpg\|thumb\|left\|300px\|'''Figure 1:''' WARTK Technique (image cortesy of gAGE/UPC)]]		[[File:Wartk gAGEUPC.jpg\|thumb\|left\|300px\|'''Figure 1:''' WARTK Technique (image cortesy of gAGE/UPC)]]

	Indeed, the Ionosphere produces ambiguity estimation biases and correlations whose mitigation is the main problem of several techniques such as [[RTK Fundamentals\|LAMBDA method]]<ref name="Lambda">[http://~~enterprise~~.lr.~~tudelft~~.nl/~~publications~~/~~files/Teunissen_JoG_1995_V70N1-2~~.pdf ''The least-squares ambiguity decorrelation adjustment: a method for fast GPS integer ambiguity estimation''] by P. Teunissen, 1995.</ref>, which takes into account these correlations in order to get reliable ambiguities for short baselines. With this RTK technique several thousands of reference receivers would be needed to provide service to Europe. To solve this limitation, WARTK provides to the users with a very accurate ionospheric refraction estimate to be removed from the user navigation filter equations. This was fulfilled by developing a very precise technique to compute ionospheric corrections in real-time using a 3-D voxel model of the ionosphere, estimated by means of a Kalman filter, and using exclusively GNSS data gathered from fixed receivers separated several hundreds of kilometers. In this way, just few dozens of fixed reference GNSS receivers are enough to ensure a sub-decimeter positioning service at continental scale, over Europe for example.<ref name="galgpsWARTK">M. Hernandez-Pajares, et al. ''Wide Area Real Time Kinematics with Galileo and GPS Signals'', Proceedings of the Institute of Navigation, Long Beach, California, 2004.</ref>		Indeed, the Ionosphere produces ambiguity estimation biases and correlations whose mitigation is the main problem of several techniques such as [[RTK Fundamentals\|LAMBDA method]]<ref name="Lambda">[http://espace.library.curtin.edu.au/cgi-bin/espace.pdf?file=/2012/05/29/file_1/185929 ''The least-squares ambiguity decorrelation adjustment: a method for fast GPS integer ambiguity estimation''] by P. Teunissen, 1995.</ref>, which takes into account these correlations in order to get reliable ambiguities for short baselines. With this RTK technique several thousands of reference receivers would be needed to provide service to Europe. To solve this limitation, WARTK provides to the users with a very accurate ionospheric refraction estimate to be removed from the user navigation filter equations. This was fulfilled by developing a very precise technique to compute ionospheric corrections in real-time using a 3-D voxel model of the ionosphere, estimated by means of a Kalman filter, and using exclusively GNSS data gathered from fixed receivers separated several hundreds of kilometers. In this way, just few dozens of fixed reference GNSS receivers are enough to ensure a sub-decimeter positioning service at continental scale, over Europe for example.<ref name="galgpsWARTK">M. Hernandez-Pajares, et al. ''Wide Area Real Time Kinematics with Galileo and GPS Signals'', Proceedings of the Institute of Navigation, Long Beach, California, 2004.</ref>

	The WARTK central processing facility (CPF) (see Figure 1) uses, in a first step, a tomographic model of the ionosphere, that maps the ionosphere at large scale in real-time with data measured by a network of permanent GNSS receivers. The second step of the technique is to characterize the ''medium scale traveling ionospheric disturbances'' (MSTID) that affect the users, specially at mid-latitude<ref>O. Colombo,et al, ''Ionospheric tomography helps resolve GPS ambiguities On The Fly at distances of hundreds of kilometers during increased geomagnetic activity'', IEEE Book, 2000, ISBN: 0-7803-4330-1.</ref>. The whole model is integrated in the positioning filter of the CPF, ensuring a reliable ambiguity fixing among the rover and the nearest permanent station.		The WARTK central processing facility (CPF) (see Figure 1) uses, in a first step, a tomographic model of the ionosphere, that maps the ionosphere at large scale in real-time with data measured by a network of permanent GNSS receivers. The second step of the technique is to characterize the ''medium scale traveling ionospheric disturbances'' (MSTID) that affect the users, specially at mid-latitude<ref>O. Colombo,et al, ''Ionospheric tomography helps resolve GPS ambiguities On The Fly at distances of hundreds of kilometers during increased geomagnetic activity'', IEEE Book, 2000, ISBN: 0-7803-4330-1.</ref>. The whole model is integrated in the positioning filter of the CPF, ensuring a reliable ambiguity fixing among the rover and the nearest permanent station.

Filipe.Pelica: fixed broken link.

2014-09-08T17:26:05Z

fixed broken link.

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	==WARTK Technique==		==WARTK Technique==

	In [[RTK Fundamentals\|RTK technique]] the differential ionospheric refraction on the signals typically limits the real-time ambiguity resolution (and the corresponding navigation with sub-decimeter errors) to baselines of few tens of km from the nearest reference site. The main techniques supporting this new approach, '''WARTK''', are related to an accurate real-time computation of ionospheric corrections, combined with an optimal processing of GNSS observables (carrier phases in particular) in both 2 and 3-frequency GNSS systems<ref>[http://www.gsa.europa.eu/~~index.cfm?objectid=42B6F1B2~~-~~A906~~-~~2D88~~-~~C40D0B75612EDD2D~~ WARTK-EGAL Project]</ref>. The navigation can be performed with few centimeters of error at distances of hundreds of kilometers from the nearest reference station.		In [[RTK Fundamentals\|RTK technique]] the differential ionospheric refraction on the signals typically limits the real-time ambiguity resolution (and the corresponding navigation with sub-decimeter errors) to baselines of few tens of km from the nearest reference site. The main techniques supporting this new approach, '''WARTK''', are related to an accurate real-time computation of ionospheric corrections, combined with an optimal processing of GNSS observables (carrier phases in particular) in both 2 and 3-frequency GNSS systems<ref>[http://www.gsa.europa.eu/wartk-based-egnos-and-galileo-technical-feasibility-study WARTK-EGAL Project]</ref>. The navigation can be performed with few centimeters of error at distances of hundreds of kilometers from the nearest reference station.

	[[File:Wartk gAGEUPC.jpg\|thumb\|left\|300px\|'''Figure 1:''' WARTK Technique (image cortesy of gAGE/UPC)]]		[[File:Wartk gAGEUPC.jpg\|thumb\|left\|300px\|'''Figure 1:''' WARTK Technique (image cortesy of gAGE/UPC)]]

Carlos.Lopez at 11:42, 23 February 2012

2012-02-23T11:42:18Z

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	{{Article Infobox2		{{Article Infobox2
	\|Category=Fundamentals		\|Category=Fundamentals
	\|~~Authors~~=GMV		\|Editors=GMV
	\|Level=Basic		\|Level=Basic
	\|YearOfPublication=2011		\|YearOfPublication=2011
	~~\|Logo=GMV~~
	\|Title={{PAGENAME}}		\|Title={{PAGENAME}}
	}}		}}

Irene.Hidalgo: /* WARTK Models and Algorithms */

2011-11-27T10:41:17Z

WARTK Models and Algorithms

← Older revision		Revision as of 10:41, 27 November 2011
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	* WARTK algorithm user.		* WARTK algorithm user.
	There are two different techniques at user level to solve the ambiguity, differentiating between dual-frequency data or 3-frequency data.<ref name:=subdmWARTK>Hernández-Pajares,et al, ''Feasibility of Wide-Area Subdecimeter Navigation With GALILEO and Modernized GPS'', IEEE Transactions on Geoscience and Remote Sensing, Vol.41(9), pp.2128-2131, 2003.</ref>		There are two different techniques at user level to solve the ambiguity, differentiating between dual-frequency data or 3-frequency data.<ref name=subdmWARTK>Hernández-Pajares,et al, ''Feasibility of Wide-Area Subdecimeter Navigation With GALILEO and Modernized GPS'', IEEE Transactions on Geoscience and Remote Sensing, Vol.41(9), pp.2128-2131, 2003.</ref>
	#WARTK-2 algorithm: In the case of dual-frequency user, the ambiguity resolution can be obtained with the well-known LAMBDA method, explained in article [[RTK Fundamentals\|RTK Fundamentals]]. The main difference with classical RTK is that the ionospheric delay is much more precise, the one received from the WARTK CPF.		#WARTK-2 algorithm: In the case of dual-frequency user, the ambiguity resolution can be obtained with the well-known LAMBDA method, explained in article [[RTK Fundamentals\|RTK Fundamentals]]. The main difference with classical RTK is that the ionospheric delay is much more precise, the one received from the WARTK CPF.
	#WARTK-3 algorithm: For the three frequency case, the ambiguity fixing is done with three-carrier ambiguity resolution (TCAR) approach<ref>R. A. Harris, ''Direct resolution of carrier-phase ambiguity by bridging the wavelength gap'', ESA Publ. TST/60 107/RAH/Word, 1997.</ref>. Using phases and pseudorange observables in the form of double differences. The ''extra-widelane'' and ''widelane'' phase combinations are <math>s_{ew}=s_1 - s_2</math> and <math>s_w=s_1 - s_3</math>, being 1, 2 y 3 each frequency. The TCAR method consists of three basic steps:<ref name:=subdmWARTK/>		#WARTK-3 algorithm: For the three frequency case, the ambiguity fixing is done with three-carrier ambiguity resolution (TCAR) approach<ref>R. A. Harris, ''Direct resolution of carrier-phase ambiguity by bridging the wavelength gap'', ESA Publ. TST/60 107/RAH/Word, 1997.</ref>. Using phases and pseudorange observables in the form of double differences. The ''extra-widelane'' and ''widelane'' phase combinations are <math>s_{ew}=s_1 - s_2</math> and <math>s_w=s_1 - s_3</math>, being 1, 2 y 3 each frequency. The TCAR method consists of three basic steps:<ref name=subdmWARTK/>
	:		:

Irene.Hidalgo: /* WARTK Models and Algorithms */

2011-11-27T10:40:26Z

WARTK Models and Algorithms

← Older revision		Revision as of 10:40, 27 November 2011
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	* WARTK algorithm user.		* WARTK algorithm user.
	There are two different techniques at user level to solve the ambiguity, differentiating between dual-frequency data or 3-frequency data		There are two different techniques at user level to solve the ambiguity, differentiating between dual-frequency data or 3-frequency data.<ref name:=subdmWARTK>Hernández-Pajares,et al, ''Feasibility of Wide-Area Subdecimeter Navigation With GALILEO and Modernized GPS'', IEEE Transactions on Geoscience and Remote Sensing, Vol.41(9), pp.2128-2131, 2003.</ref>
	#WARTK-2 algorithm: In the case of dual-frequency user, the ambiguity resolution can be obtained with the well-known LAMBDA method, explained in article [[RTK Fundamentals\|RTK Fundamentals]]. The main difference with classical RTK is that the ionospheric delay is much more precise, the one received from the WARTK CPF.		#WARTK-2 algorithm: In the case of dual-frequency user, the ambiguity resolution can be obtained with the well-known LAMBDA method, explained in article [[RTK Fundamentals\|RTK Fundamentals]]. The main difference with classical RTK is that the ionospheric delay is much more precise, the one received from the WARTK CPF.
	#WARTK-3 algorithm: For the three frequency case, the ambiguity fixing is done with three-carrier ambiguity resolution (TCAR) approach<ref>R. A. Harris, ''Direct resolution of carrier-phase ambiguity by bridging the wavelength gap'', ESA Publ. TST/60 107/RAH/Word, 1997.</ref>. Using phases and pseudorange observables in the form of double differences. The ''extra-widelane'' and ''widelane'' phase combinations are <math>s_{ew}=s_1 - s_2</math> and <math>s_w=s_1 - s_3</math>, being 1, 2 y 3 each frequency. The TCAR method consists of three basic steps:		#WARTK-3 algorithm: For the three frequency case, the ambiguity fixing is done with three-carrier ambiguity resolution (TCAR) approach<ref>R. A. Harris, ''Direct resolution of carrier-phase ambiguity by bridging the wavelength gap'', ESA Publ. TST/60 107/RAH/Word, 1997.</ref>. Using phases and pseudorange observables in the form of double differences. The ''extra-widelane'' and ''widelane'' phase combinations are <math>s_{ew}=s_1 - s_2</math> and <math>s_w=s_1 - s_3</math>, being 1, 2 y 3 each frequency. The TCAR method consists of three basic steps:<ref name:=subdmWARTK/>
	:		:

Irene.Hidalgo: /* WARTK Models and Algorithms */

2011-11-27T10:22:21Z

WARTK Models and Algorithms

← Older revision		Revision as of 10:22, 27 November 2011
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	* The Real-time tomographic model.		* The Real-time tomographic model.

	The free electron density can be described as a random walk process in time that can best be estimated in a Sun-fixed reference frame where it is relatively stationary (variation of 10% during one day in mean latitudes and Solar Maximum conditions). The tomographic model adopted is spatially formed by a set of cells or volume elements (voxels), especially suitable to detect local features, that cover all the ionosphere sampled by the GPS satellite/receiver rays. These voxels, which electron density is considered uniform at any given time, can be taken with the same size for describing a region sampled from an approximately homogeneously distributed network of reference stations. A voxel size of 3x5 degrees in latitude and solar longitude, and two layers with boundaries at 60-740-1420 km have been adopted. This is adequate to get precise ionospheric determinations from ground GPS data.<ref>Hernández-Pajares, et al, ''New approaches in global ionospheric determination using ground GPS data'', Journal of Atmospheric and Solar-Terrestrial Physics 61, 1237-1247, 1999.</ref>.		The free electron density can be described as a random walk process in time that can best be estimated in a Sun-fixed reference frame where it is relatively stationary (variation of 10% during one day in mean latitudes and Solar Maximum conditions). The tomographic model adopted is spatially formed by a set of cells or volume elements (voxels), especially suitable to detect local features, that cover all the ionosphere sampled by the GPS satellite/receiver rays. These voxels, which electron density is considered uniform at any given time, can be taken with the same size for describing a region sampled from an approximately homogeneously distributed network of reference stations. A voxel size of 3x5 degrees in latitude and solar longitude, and two layers with boundaries at 60-740-1420 km have been adopted. This is adequate to get precise ionospheric determinations from ground GPS data.<ref>Hernández-Pajares, et al, ''New approaches in global ionospheric determination using ground GPS data'', Journal of Atmospheric and Solar-Terrestrial Physics 61, 1237-1247, 1999.</ref><ref name=400kmWARTK>Hernández-Pajares, et al, ''Application of ionospheric tomography to real-time GPS carrier-phase ambiguities resolution, at scales of 400-1000 km and with high geomagnetic activity'', Geophysical Research Letters Vol. 27(13), pp. 2009-2012, 2000.</ref>

	The resolution of the model initialized with data from the previous day, is performed using the geometry-free combination of phases, <math>L_1</math> and <math>L_2</math>, of the transmitter T measured from the receiver R. The estimation of this ionospheric model is done by means of a Kalman filter with 10 minutes of updating time (similar performance with 2 minutes), in such a way that the results of the last batch are used to estimate the ionospheric delays up to the next updating time. Then, all ionospheric delays are estimated only from the previous data, as must be done in real-time.<ref>Hernández-Pajares, et al, ''Application of ionospheric tomography to real-time GPS carrier-phase ambiguities resolution, at scales of 400-1000 km and with high geomagnetic activity'', Geophysical Research Letters Vol. 27(13), pp. 2009-2012, 2000.</~~ref~~>		The resolution of the model initialized with data from the previous day, is performed using the geometry-free combination of phases, <math>L_1</math> and <math>L_2</math>, of the transmitter T measured from the receiver R. The estimation of this ionospheric model is done by means of a Kalman filter with 10 minutes of updating time (similar performance with 2 minutes), in such a way that the results of the last batch are used to estimate the ionospheric delays up to the next updating time. Then, all ionospheric delays are estimated only from the previous data, as must be done in real-time.<ref name=400kmWARTK/>

	* WARTK algorithm user.		* WARTK algorithm user.

Irene.Hidalgo: /* WARTK Models and Algorithms */

2011-11-27T10:18:25Z

WARTK Models and Algorithms

← Older revision		Revision as of 10:18, 27 November 2011
Line 29:		Line 29:
	The free electron density can be described as a random walk process in time that can best be estimated in a Sun-fixed reference frame where it is relatively stationary (variation of 10% during one day in mean latitudes and Solar Maximum conditions). The tomographic model adopted is spatially formed by a set of cells or volume elements (voxels), especially suitable to detect local features, that cover all the ionosphere sampled by the GPS satellite/receiver rays. These voxels, which electron density is considered uniform at any given time, can be taken with the same size for describing a region sampled from an approximately homogeneously distributed network of reference stations. A voxel size of 3x5 degrees in latitude and solar longitude, and two layers with boundaries at 60-740-1420 km have been adopted. This is adequate to get precise ionospheric determinations from ground GPS data.<ref>Hernández-Pajares, et al, ''New approaches in global ionospheric determination using ground GPS data'', Journal of Atmospheric and Solar-Terrestrial Physics 61, 1237-1247, 1999.</ref>.		The free electron density can be described as a random walk process in time that can best be estimated in a Sun-fixed reference frame where it is relatively stationary (variation of 10% during one day in mean latitudes and Solar Maximum conditions). The tomographic model adopted is spatially formed by a set of cells or volume elements (voxels), especially suitable to detect local features, that cover all the ionosphere sampled by the GPS satellite/receiver rays. These voxels, which electron density is considered uniform at any given time, can be taken with the same size for describing a region sampled from an approximately homogeneously distributed network of reference stations. A voxel size of 3x5 degrees in latitude and solar longitude, and two layers with boundaries at 60-740-1420 km have been adopted. This is adequate to get precise ionospheric determinations from ground GPS data.<ref>Hernández-Pajares, et al, ''New approaches in global ionospheric determination using ground GPS data'', Journal of Atmospheric and Solar-Terrestrial Physics 61, 1237-1247, 1999.</ref>.

	The resolution of the model initialized with data from the previous day, is performed using the geometry-free combination of phases, <math>L_1</math> and <math>L_2</math>, of the transmitter T measured from the receiver R. The estimation of this ionospheric model is done by means of a Kalman filter with 10 minutes of updating time (similar performance with 2 minutes), in such a way that the results of the last batch are used to estimate the ionospheric delays up to the next updating time. Then, all ionospheric delays are estimated only from the previous data, as must be done in real-time.		The resolution of the model initialized with data from the previous day, is performed using the geometry-free combination of phases, <math>L_1</math> and <math>L_2</math>, of the transmitter T measured from the receiver R. The estimation of this ionospheric model is done by means of a Kalman filter with 10 minutes of updating time (similar performance with 2 minutes), in such a way that the results of the last batch are used to estimate the ionospheric delays up to the next updating time. Then, all ionospheric delays are estimated only from the previous data, as must be done in real-time.<ref>Hernández-Pajares, et al, ''Application of ionospheric tomography to real-time GPS carrier-phase ambiguities resolution, at scales of 400-1000 km and with high geomagnetic activity'', Geophysical Research Letters Vol. 27(13), pp. 2009-2012, 2000.</ref>

	* WARTK algorithm user.		* WARTK algorithm user.
	There are two different techniques at user level to solve the ambiguity, differentiating between dual-frequency data or 3-frequency data		There are two different techniques at user level to solve the ambiguity, differentiating between dual-frequency data or 3-frequency data

Irene.Hidalgo: /* WARTK Models and Algorithms */

2011-11-27T10:15:50Z

WARTK Models and Algorithms

← Older revision		Revision as of 10:15, 27 November 2011
Line 27:		Line 27:
	* The Real-time tomographic model.		* The Real-time tomographic model.

	The free electron density can be described as a random walk process in time that can best be estimated in a Sun-fixed reference frame where it is relatively stationary (variation of 10% during one day in mean latitudes and Solar Maximum conditions). The tomographic model adopted is spatially formed by a set of cells or volume elements (voxels), especially suitable to detect local features, that cover all the ionosphere sampled by the GPS satellite/receiver rays. These voxels, which electron density is considered uniform at any given time, can be taken with the same size for describing a region sampled from an approximately homogeneously distributed network of reference stations. A voxel size of 3x5 degrees in latitude and solar longitude, and two layers with boundaries at 60-740-1420 km have been adopted. This is adequate to get precise ionospheric determinations from ground GPS data<ref>Hernández-Pajares, et al, ''New approaches in global ionospheric determination using ground GPS data'', Journal of Atmospheric and Solar-Terrestrial Physics 61, 1237-1247, 1999.</ref>.		The free electron density can be described as a random walk process in time that can best be estimated in a Sun-fixed reference frame where it is relatively stationary (variation of 10% during one day in mean latitudes and Solar Maximum conditions). The tomographic model adopted is spatially formed by a set of cells or volume elements (voxels), especially suitable to detect local features, that cover all the ionosphere sampled by the GPS satellite/receiver rays. These voxels, which electron density is considered uniform at any given time, can be taken with the same size for describing a region sampled from an approximately homogeneously distributed network of reference stations. A voxel size of 3x5 degrees in latitude and solar longitude, and two layers with boundaries at 60-740-1420 km have been adopted. This is adequate to get precise ionospheric determinations from ground GPS data.<ref>Hernández-Pajares, et al, ''New approaches in global ionospheric determination using ground GPS data'', Journal of Atmospheric and Solar-Terrestrial Physics 61, 1237-1247, 1999.</ref>.

	The resolution of the model initialized with data from the previous day, is performed using the geometry-free combination of phases, <math>L_1</math> and <math>L_2</math>, of the transmitter T measured from the receiver R. The estimation of this ionospheric model is done by means of a Kalman filter with 10 minutes of updating time (similar performance with 2 minutes), in such a way that the results of the last batch are used to estimate the ionospheric delays up to the next updating time. Then, all ionospheric delays are estimated only from the previous data, as must be done in real-time.		The resolution of the model initialized with data from the previous day, is performed using the geometry-free combination of phases, <math>L_1</math> and <math>L_2</math>, of the transmitter T measured from the receiver R. The estimation of this ionospheric model is done by means of a Kalman filter with 10 minutes of updating time (similar performance with 2 minutes), in such a way that the results of the last batch are used to estimate the ionospheric delays up to the next updating time. Then, all ionospheric delays are estimated only from the previous data, as must be done in real-time.