In this chapter we consider in detail how one can compensate errors in GNSS observables. GNSS observables can be constructed from code and carrier measurements made on different frequencies in various ways. Some of these observables are less affected by particular errors than others. We also consider how the usage of measurements from other receivers located at known positions allows elimination of some errors (Figure 8.1).

Error budget of GNSS observables

As explained in previous chapters, we can describe GNSS errors in the form of an error budget. The budget consists of the following errors:

• DOP arising from geometrical properties of the satellite constellation (see Chapter 1);

• Satellite-related errors, including satellite clock error, satellite orbit errors, satellite transmitter errors, including biases (see Chapter 3);

• Propagation errors in a dispersive medium due to the ionosphere (see Chapter 4);

• Propagation errors in a non-dispersive medium due to the troposphere (see Chapter 4);

• Receiver-related errors including noise and hardware biases (see Chapter 5);

• Multipath (see Chapter 7).

We have described the errors related to signal propagation in the atmosphere in Chapter 4. Some R&D tasks may require more specific models to be implemented, especially where development of new algorithms is concerned. One example is spatially correlated ionospheric errors. Algorithm development related to a virtual reference station (VRS), network RTK, or ionospheric research may require an ability to generate a spatially correlated ionospheric model. In that case the signal is generated for more than one receiver and ionospheric errors are properly correlated. The specific fluctuations of TEC distribution can be added on top of nominal TEC distribution. These nominal TEC distribution values come from true Klobuchar, NeQuick, or IGS models. The other example is to specify an anomalous ionospheric gradient with parameters in accordance, for example, with WAAS Super Truth data analysis and simulate a moving slope for the ionospheric gradient. For details of the Threat Model of an anomalous ionosphere gradient see [1]. In this case some specific fluctuations or slope can be implemented on top of the regular total electron count (TEC) distribution model.