## 5 Conclusions  
In this paper, the observations and position quality of a Sepentrio AsteRx-U geodetic receiver, two u-blox receivers -ZED-F9P and ZED-F9R- and a Xiaomi Mi8 smartphone operating in GPS only and GNSS modes were analysed in relation to the Applanix MMS trajectory results. The study was carried out in urban and non-urban areas and in GNSS favourable measurement conditions. The results obtained in this research lead to the following conclusions, especially in terms of the low-cost used devices:  
* From the comparison of the GPS only and GNSS solutions for geodetic and low-cost receivers, it can be concluded that in terms of the GPS, GNSS processing achieved many more solutions for position determination and determined ambiguities in many more cases with fixed values, even if this is not true in general for the Sepentrio AsteRx-U and in particular in case C: a non-urban area with curves and serpentines characterised by a reduced signal acquisition. Comparing the means and standard deviations of the deviation of the distances from the reference, it can be stated that the variances for the GPS and GNSS solutions were comparable in this case. * There is a significant difference in quality between kinematic positioning with geodetic and low-cost receivers. The geodetic receiver is much more stable in ambiguity solutions, especially when compared to a smartphone. The same is true for solutions where the threshold for positioning quality is set at 30 cm and even more clearly at 10 cm. The differences certainly also relate to the design of the receiving antenna. The geodetic GNSS antenna enables the elimination of some multipath signals and obviously outperforms the small antenna of a smartphone and the patch antenna of the u-bloxes. Therefore, it can be said that caution should be exercised when using low-cost receivers in terrestrial measurements in urban environments, and further studies and research are required in order to eliminate observations that are loaded with effects (these can be multipaths or interferences). * Care should also be taken when moving out of shaded areas that make GNSS positioning impossible, especially with low-cost receivers. In the future, when processing combined GNSS and INS observations in the Kalman filter for low-cost receivers, it would be useful to include the new GNSS resolution obtained from the transient in the final solution, since the solutions--especially for the low-cost receivers--deviated significantly from the Applanix reference solutions immediately after repositioning. * In situations with many curves and manoeuvres on the road, the low-cost receivers also performed worse compared to the geodetic receiver; in these situations, they determined significantly fewer positions than the Sepentrio AsteRx-U receiver. Since this portion of the trajectory may have also been affected by the poor survey conditions due to vegetation, further research is required in order to determine how the receivers respond in curves and turns in the open sky. * In GNSS mode, the Xiaomi Mi8 smartphone performed well in situations with a threshold of less than 1 m, with the percentages varying from 50% for the urban areas to 80% for the non-urban areas, which offers potential in view of future improvements for applications in terrestrial navigation. * The general conclusion is that even low-cost devices, especially u-blox receivers and in particular those operating in GNSS/INS mode, are suitable for kinematic terrestrial positioning; however, their use in problematic positioning areas and in urban environments with obstacles should be treated with greater caution than is the case when using professional geodetic receivers. Future studies will focus on the fusion of GNSS and MEMS (Micro-Electro-Mechanical System) sensors in smartphones and u-bloxes to enable more accurate and continuous positioning using the Kalman filter, especially in problematic environments such as street canyons, dense vegetation and under conditions of intentional interference, namely jamming and spoofing.