PPP has become a popular technique to process data from GPS receivers by introducing precise satellite orbit and clock information. Typically, a dual-frequency GPS receiver is utilized with dual-frequency pseudorange and carrier-phase measurements linearly combined to remove the first-order effect of the ionospheric refraction and the real-valued carrier-phase ambiguity terms are estimated from the measurement model. The tropospheric refraction is also estimated, along with the position and ambiguity parameters from the measurements (Héroux et al.,2004; Kouba and Héroux, 2001; Zumberge et al.,1997).

PPP is considered a cost effective technique as it enables sub-centimetre horizontal and few centimetre vertical positioning with a single GPS receiver; in contrast to the methods such as relative GPS, RTK and Network RTK that require more than one receiver. PPP can be used for the processing of static and kinematic data, both in real-time and post-processing (Héroux et al.,2004).

PPP’s application has been extended to the commercial sector, as well in areas such as agricultural industry for precision farming, marine applications (for sensor positioning in support of seafloor mapping and marine construction) and airborne mapping (Bisnath and Gao, 2008). In rural and remote areas where precise positioning and navigation is required and no reference stations are available, PPP proves to be an asset. Collins et al. (2008) are currently researching PPP ambiguity resolution to determine how plausible real-time PPP is for seismic monitoring. Based on PPP’s performance, it may be extended to other scientific applications such as ionospheric delay estimation, pseudorange multipath estimation, satellite pseudorange bias and satellite clock error estimation (Leandro,2009).

In PPP, when the number of tracked satellites is less than the minimum number of satellites required, filter re-initialization occurs and can result in tens of minutes of greater than decimetre resolution positioning, until filter re-convergence and similarity for the initial convergence (Bisnath and Gao, 2008). The solution convergence depends on several factors including: the number and geometry of visible satellites, observation quality, user environment and dynamics, and sampling rate. As these different factors interplay, the period of time (from session start) required for the solution to reach a pre-defined precision level will vary (Héroux et al.,2004).

One of the remaining unmodelled residual terms in PPP is (1) the pseudorange multipath and (2) noise, which, if efficiently accounted for, may provide improvement in the rate of convergence. Multipath occurs when signals travelling from a transmitter to a receiver propagate via multiple paths due to reflection and diffraction (Bisnath and Langley, 2001). The multipath effect introduces errors in both pseudorange and carrier-phase measurements. The magnitude of range error can reach up to 10 to 20 m for the pseudorange measurements and up to 5 cm for the carrier-phase measurements (Wells et al.,1999). The pseudorange noise comes from the receiver electronics itself or is picked up by receiver’s antenna.

PPP’s application has been extended to the commercial sector, as well in areas such as agricultural industry for precision farming, marine applications (for sensor positioning in support of seafloor mapping and marine construction) and airborne mapping (Bisnath and Gao, 2008). In rural and remote areas where precise positioning and navigation is required and no reference stations are available, PPP proves to be an asset. Collins et al. (2008) are currently researching PPP ambiguity resolution to determine how plausible real-time PPP is for seismic monitoring. Based on PPP’s performance, it may be extended to other scientific applications such as ionospheric delay estimation, pseudorange multipath estimation, satellite pseudorange bias and satellite clock error estimation (Leandro,2009).

In PPP, when the number of tracked satellites is less than the minimum number of satellites required, filter re-initialization occurs and can result in tens of minutes of greater than decimetre resolution positioning, until filter re-convergence and similarity for the initial convergence (Bisnath and Gao, 2008). The solution convergence depends on several factors including: the number and geometry of visible satellites, observation quality, user environment and dynamics, and sampling rate. As these different factors interplay, the period of time (from session start) required for the solution to reach a pre-defined precision level will vary (Héroux et al.,2004).

One of the remaining unmodelled residual terms in PPP is (1) the pseudorange multipath and (2) noise, which, if efficiently accounted for, may provide improvement in the rate of convergence. Multipath occurs when signals travelling from a transmitter to a receiver propagate via multiple paths due to reflection and diffraction (Bisnath and Langley, 2001). The multipath effect introduces errors in both pseudorange and carrier-phase measurements. The magnitude of range error can reach up to 10 to 20 m for the pseudorange measurements and up to 5 cm for the carrier-phase measurements (Wells et al.,1999). The pseudorange noise comes from the receiver electronics itself or is picked up by receiver’s antenna.

Since PPP uses only a single GPS receiver, no data differencing between two receivers can be used to eliminate satellite specific errors such as the clock and orbital errors and atmospheric errors. It is therefore necessary to use the most precise satellite and clock corrections and satellite orbits and estimate the atmospheric errors. In the figure on the left illustrates the precision of the International GNSS Service (IGS) Final GPS orbits over the past 15 years. The precise orbit product has been improved from an accuracy of 30 cm to approximately 1-2 cm, with a similar improvement in the IGS Final combined orbit product. The GPS satellite clock estimates that are included in the IGS orbit products since 1995 are now within the standard deviation range of 0.02 - 0.06 ns or 1 - 2 cm, which is consistent with the orbit precision (Kouba,2009).

Source: Seepersad (2012)

References

Bisnath S, and Gao Y (2008) "Current State of Precise Point Positioning and Future Prospects and Limitations." International Association of Geodesy Symposia – "Observing our Changing Earth", Vol.133, pp. 615-623.

Bisnath S, and Langley R (2001) "Pseudorange Multipath Mitigation by Means of Multipath Monitoring and De-Weighting." Proceedings of the International Symposium on Kinematic Systems in Geodesy, Geomatics and Navigation, pp. 392-400.

Collins P (2008) "Isolating and Estimating Undifferenced GPS Integer Ambiguities." Proc. ION NTM, pp. 720-732.

Héroux P, Gao Y, Kouba J, Lahaye F, Mireault Y, Collins P, Macleod K, Tetreault P, and Chen K (2004) "Products and Applications for Precise Point Positioning - Moving Towards Real-Time." Proceedings of the 17th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2004), Long Beach, CA, pp. 1832-1843.

Kouba, J (2009) "A guide to using International GNSS Service (IGS) products." http://igscb.jpl.nasa.gov/igscb/resource/pubs/UsingIGSProductsVer21.pdf Accessed: 2013.

Kouba J, and Héroux P (2001) "Precise Point Positioning using IGS Orbit and Clock Products." GPS solutions, Vol. 5, No. 2, pp. 12-28.

Leandro, RF (2009) "Precise Point Positioning with GPS: A New Approach for Positioning, Atmospheric Studies, and Signal Analysis." Ph. D. dissertation,University of New Brunswick (Canada), 458 p.

Wells DE, Beck N, Delikaraoglou D, Kleusberg A, Krakiwsky E, Lachapelle G, Langley R, Nakiboglu M, Schwarz K, and Tranquilla J (1999) Guide to GPS Positioning, Department of Geodesy and Geomatics Engineering,Lecture Note No. 58, University of New Brunswick, NB, Canada, 601 p.

Zumberge J, Heflin M, Jefferson D, Watkins M, and Webb F (1997) "Precise Point Positioning for the Efficient and Robust Analysis of GPS Data from Large Networks." Journal of Geophysical Research, Vol. 102, No. B3, pp. 5005-17.

Source: Seepersad (2012)

References

Bisnath S, and Gao Y (2008) "Current State of Precise Point Positioning and Future Prospects and Limitations." International Association of Geodesy Symposia – "Observing our Changing Earth", Vol.133, pp. 615-623.

Bisnath S, and Langley R (2001) "Pseudorange Multipath Mitigation by Means of Multipath Monitoring and De-Weighting." Proceedings of the International Symposium on Kinematic Systems in Geodesy, Geomatics and Navigation, pp. 392-400.

Collins P (2008) "Isolating and Estimating Undifferenced GPS Integer Ambiguities." Proc. ION NTM, pp. 720-732.

Héroux P, Gao Y, Kouba J, Lahaye F, Mireault Y, Collins P, Macleod K, Tetreault P, and Chen K (2004) "Products and Applications for Precise Point Positioning - Moving Towards Real-Time." Proceedings of the 17th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2004), Long Beach, CA, pp. 1832-1843.

Kouba, J (2009) "A guide to using International GNSS Service (IGS) products." http://igscb.jpl.nasa.gov/igscb/resource/pubs/UsingIGSProductsVer21.pdf Accessed: 2013.

Kouba J, and Héroux P (2001) "Precise Point Positioning using IGS Orbit and Clock Products." GPS solutions, Vol. 5, No. 2, pp. 12-28.

Leandro, RF (2009) "Precise Point Positioning with GPS: A New Approach for Positioning, Atmospheric Studies, and Signal Analysis." Ph. D. dissertation,University of New Brunswick (Canada), 458 p.

Wells DE, Beck N, Delikaraoglou D, Kleusberg A, Krakiwsky E, Lachapelle G, Langley R, Nakiboglu M, Schwarz K, and Tranquilla J (1999) Guide to GPS Positioning, Department of Geodesy and Geomatics Engineering,Lecture Note No. 58, University of New Brunswick, NB, Canada, 601 p.

Zumberge J, Heflin M, Jefferson D, Watkins M, and Webb F (1997) "Precise Point Positioning for the Efficient and Robust Analysis of GPS Data from Large Networks." Journal of Geophysical Research, Vol. 102, No. B3, pp. 5005-17.