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Abstract
The multi-GNSS era is attracting more attention with the declaration of full operational capability of the Russian Federation's GLONASS, with 24 satellites being declared ‘healthy’ on December 8th 2011. This brings benefits for GNSS users in areas where the number of visible satellites is limited because of shadowing effects (e.g. ‘urban canyon’ environments or in deep open cut mines). In such areas adding more functioning satellites, which is one possible aiding solutions, becomes an attractive option.
The inclusion of GLONASS observations in positioning solutions will increase the available number of satellites and thus positioning accuracy may improve as a result of enhanced overall satellite geometry. However, adding GLONASS observations to GPS solutions is not a straight forward process. This is attributable to differences in signal structures. One of the challenges is that relative receiver clock errors cannot cancel as in the case of GPS-only observation modelling. Several approaches have been suggested to address this challenge, which can be grouped into two main classes: receiver clock error estimation or receiver clock error elimination. Approaches used to address the relative receiver clock error modelling challenge for high accuracy users in static and kinematic modes have been compared and evaluated. Several data quality measures were used to compare the different processing strategies. The influence of system selection on ambiguity resolution was assessed using some of the commonly used measures for ambiguity validation.
A user of heterogeneous GPS and GLONASS receiver pairs in differential positioning mode will experience ambiguity fixing challenges due to the presence of inter-channel biases. These biases cannot be cancelled by differencing GLONASS observations, either pseudorange or carrier phase measurements. Fortunately, pre-calibration of GLONASS pseudorange and carrier phase observations can make ambiguity fixing for integrated GPS/GLONASS positioning much easier. An effective algorithm which transforms an RTK (real-time kinematic) solution in a mixed receiver baseline from a ‘float’ to a ‘fixed’ ambiguity solution has been proposed.
Another challenge for high precision GPS and GLONASS surveying and navigation techniques is that the baseline between two receivers (distance between the reference station, known coordinates, and the user station, required coordinates) is typically constrained to short ranges (<10-20km). This adversely impacts on RTK productivity. Fortunately this limitation has been addressed by the so-called Network-based RTK (NRTK) techniques. Comprehensive investigation of several approaches to implementing NRTK techniques, which requires the estimation of atmospheric corrections on an epoch-by-epoch basis,, has been carried out in order to identify the optimal method for mitigating atmospheric effects for real-time kinematic applications for different network geometries.
Most networks of continuously operating reference stations (CORS) are now equipped with receivers that can track both GPS and GLONASS satellites and, therefore, it is common for a CORS network having to support heterogeneous user receivers. As a result, users of such networks will face ambiguity fixing challenges in mixed receiver scenarios when both GNSS systems are used for positioning. In this study, data from the CORSnet-NSW network located in the Sydney region, Australia, were used to examine and validate the proposed GPS and GLONASS Network RTK algorithm for mixed baselines. It has been demonstrated that the pre-calibration of both GLONASS carrier phase and pseudorange observations can assist NRTK users seeking cm-level positioning accuracy by improving the success rate of GPS/GLONASS ambiguity fixing.