RTK Fundamentals

Fundamentals
Title	RTK Fundamentals
Author(s)	See Credits section
Level	Basic
Year of Publication	2011

Real Time Kinematic (RTK) satellite navigation is a DGNSS technique used in land survey and in hydrographic survey based on the use of carrier phase measurements of the GNSS signals where a single reference station provides the real-time corrections, providing up to centimeter-level accuracy. When referring to GPS in particular, the system is also commonly referred to as Carrier-Phase Enhancement, CPGPS.

RTK Technique

The RTK technique follows the same general principle as classical DGNSS, but instead of using corrections to C/A code pseudoranges, it uses the carrier phase as its signal.

The RTK technique consists on a rover user that applies real-time corrections provided by a base station. In the classical DGNSS Technique, there are also 2 receivers, one at a known location (base station) and one at an unknown position, that see the same GNSS satellites in common. By fixing the location of the base station, the other location may be found either by computing corrections to the position of the unknown receiver or by computing corrections to the pseudoranges. In the classical DGNSS technology, only corrections to C/A code pseudoranges are being transmitted, which brings rover positional errors down to values about 1 m for distances between rover and base station of a few tens of kilometers.

When using carrier phase signals sent by the same satellites the accuracy can improved to about 30 cm. The difficulty of the use of carrier phase data comes at a cost in terms of overall system complexity because the measurements are ambiguous by an integer (i.e. every cycle of the carrier is similar to every other). Therefore, the key of the RTK technique is the "Ambiguity Resolution".

RTK Algorithm

The difficulty in making an RTK system is properly aligning the signals. As stated in Septentrio homepage, the carrier phase measurements are extremely precise (down to the fractions of millimeter), but they contain an unknown integer initialization constant, the so-called “phase ambiguity”. Therefore RTK positioning has to resolve integer ambiguities to achieve the high level of precision.

The RTK Algorithm is based on double differenced observables that can eliminate selective availability effects as well as other biases. The highlights of the algorithm are described next. At a given epoch, and for a given satellite, the simplified carrier phase observation equation is the following:

[math]\displaystyle{ \qquad \phi =\rho-I+Tr+c(b_{Rx}-b_{Sat} )+〖N\lambda+\varepsilon〗_\phi \qquad \mbox{(1)} }[/math]

Where:

[math]\displaystyle{ I }[/math] is the signal path delay due to the ionosphere;

[math]\displaystyle{ Tr }[/math] is the signal path delay due to the troposphere;

[math]\displaystyle{ b_{Rx} }[/math] is the receiver clock offset from the reference (GPS) time;

[math]\displaystyle{ b_{Sat} }[/math] is the satellite clock offset from the reference (GPS) time;

[math]\displaystyle{ c }[/math] is the vacuum speed of light;

[math]\displaystyle{ \lambda }[/math] is the carrier nominal wavelength;

[math]\displaystyle{ N }[/math] is the ambiguity of the carrier-phase (integer number);

[math]\displaystyle{ \varepsilon_\phi }[/math] are the measurement noise components, including multipath and other effects;

[math]\displaystyle{ \rho }[/math] is the geometrical range between the satellite and the receiver, computed as a function of the satellite [math]\displaystyle{ (x_{Sat}, y_{Sat},z_{Sat}) }[/math] and receiver [math]\displaystyle{ (x_{Rx}, y_{Rx},z_{Rx}) }[/math] coordinates as:

[math]\displaystyle{ \qquad \rho=\sqrt{〖(x_{Sat}-x_{Rx})〗^2+〖(y_{Sat}-y_{Rx})〗^2+〖(z_{Sat}-z_{Rx})〗^2 } \qquad \mbox{(2)} }[/math].

For two receivers a and b making simultaneous measurements at the same nominal time to satellites 1 and 2, the double difference observable is:

[math]\displaystyle{ \qquad \phi_a^{12} - \phi_b^{12} =\rho_a^{12}-\rho_b^{12}-I_a^{12}+I_b^{12}+Tr_a^{12}-Tr_b^{12}+\lambda(N_a^{12}-N_b^{12})+\varepsilon_a^{12}- \varepsilon_b^{12} \qquad \mbox{(3)} }[/math]

In the above equation receiver and satellite clock offsets and hardware biases cancel, since double differencing is effectively differencing between satellites and between receivers. The single difference ambiguities difference [math]\displaystyle{ N_a^{12}-N_b^{12} }[/math] is commonly parameterized as a new ambiguity parameter [math]\displaystyle{ N_a^{12} }[/math]. The advantage of double differencing is that the new ambiguity parameter [math]\displaystyle{ N_a^{12} }[/math] is an integer because the non-integer terms in the GPS carrier phase observation, due to clock and hardware delays in the transmitter and receiver, are eliminated.

Among the different challenges to achieve high-level precision, i.e. cm-level positioning, there is the Integer Ambiguity Resolution, as the method used to solve the unknown integer ambiguities of the double-differenced carrier phase observables, that is the key in RTK algorithm.

Ambiguity Resolution

As it was said above the ambiguity resolution is the key of positioning precision in RTK Technique. It can be divided in mainly three steps, as shown in the figure.

The first step is an "ordinary" least-squares, that can be done either in a batch implementation or a Kalman filter. In this process the integer nature of the ambiguities is not considered, and therefore, the solution of the process are real-valued estimates; the so-called 'float' solution, that includes baseline coordinates, differential atmospheric delays and carrier phase ambiguities.

The second step is the LAMBDA method itself , developed by Delft University of Technology. It consists mainly in the decorrelation of the ambiguities, taking into account their integer nature. This decorrelation gives a fast and efficiently integer least-squares computation.

Finally, in the last step, the solution of the remaining parameters, i.e. the baseline coordinates and additional parameters such as atmospheric delays, is computed keeping the ambiguities fixed to the integer values obtained in second step. This final solution is known as the 'fixed' solution and the obtained values generally have centimeter level precision or less.

As it was stated in the article Real-Time Kinematic in the Light of GPS Modernization and Galileo : The LAMBDA method has been demonstrated to be optimal. The integer least-squares estimator is best in the sense of maximizing the probability of correct integer estimation, i.e. in maximizing the ambiguity success-rate.

The LAMBDA method can be used as a separate, generally applicable module for integer estimation. The TU Delft University can provide Matlab and Fortran 77 source code of the subroutines for the LAMBDA method . The subroutine is flexible in terms of output and number of candidates; it does not matter the number of GNSS frequencies or the absence of pseudorange code measurements on a particular frequency or incidentally missing measurements for some of the satellites.

Network RTK

Once the ambiguity fixing is solved by LAMBDA Method explained above, the problem comes when baseline distance is larger than a few tens of kms. In this case, the compensation of atmospheric effects is not complete and the ambiguity fixing is less reliable due to error decorrelation, which increases proportionately with baseline distance. To solve this issue, information from a network of base stations is used, this is known as Network RTK techniques.

Network RTK has been established in several countries during the last years. The first-generation of Network RTK systems is consolidated, and the objectives of the International Association of Geodesy Commission 4: Positioning & Applications to develop the next generation RTK are mainly:

• investigation on important technical issues for next generation RTK system development: e.g. the improvement of algorithms for the prediction of atmospheric corrections or the mitigation of station-dependent errors (mainly multipath) at the reference stations
• development of data standards and operational procedures, including the communication protocols and message formats.
• establishment of strong collaborations with other international organizations, such as IGS, and also with the industry sector.

Credits

Edited by GMV. The text in the introduction and the section RTK Technique is mostly taken from Wikipedia with minor adaptation, provided under Creative Commons Attribution-ShareAlike License.

The section Ambiguity Resolution has been taken from the article Real-Time Kinematic in the Light of GPS Modernization and Galileo and TU Delft University web-page dedicated to the LAMBDA Method .

The section RTK on-going Research has been taken from the article Introduction to Network RTK and the International Association of Geodesy Commission 4 (Positioning & Applications) web-page.