## 6 Discussion  
In the discussion of the results, the attention is mainly focused on determining the proposed test method's external reliability. For this purpose, the proposed algorithm was verified in terms of determining positioning accuracy. In the discussion, the aircraft position's obtained results using the PPP method from the RTKLIB program [45; 46] for the weighted average model used were analyzed. Such a check is crucial, because we obtain independent confirmation of the proposed mathematical algorithm's correctness (4-9). In particular, in the proposed research method's external control, the key factor is Equation (9), thanks to which, the position errors can be determined [47]. Therefore, the weighted average model results will be compared to the reference coordinates determined by RTK-OTF. Figures 16-18 show the positioning accuracy between the weighted average model and the RTK technique as a function of the measurements used. The \(DX\) position errors were from +0.157 m to +1.668 m for weights \((P_{g}=\frac{1}{n_{g}};P_{r}=\frac{1}{n_{g}})\). On the other hand, for \((P_{g}=\frac{1}{Cl_{g}^{2}};P_{g}=\frac{1}{Cl_{r}^{2}})\), the \(DX\) position errors were from \(-0.077\) m to +0.883 m. It can be observed that the positioning accuracy along the \(X\)-axis improved by about 45% in the case of using weights \((P_{g}=\frac{1}{Cl_{g}^{2}};P_{g}=\frac{1}{Cl_{r}^{2}})\) in relation to the \(DX\) results determined when weights \((P_{g}=\frac{1}{n_{g}};P_{r}=\frac{1}{n_{g}})\) were used. Figure 16: Position errors along the \(X\)-axis. Figure 17: Position errors along the \(Y\)-axis. The \(DY\) position errors were from \(-0.745\) m to \(+0.812\) m for \((P_{g}=\frac{1}{ns_{g}};P_{r}=\frac{1}{ns_{r}})\) weighing. In turn, for \((P_{g}=\frac{1}{Cl_{g}^{2}};P_{g}=\frac{1}{Cl_{g}^{2}})\), the \(DY\) position errors were from \(-0.081\) m to \(+0.754\) m. It can be observed that the positioning accuracy along the \(Y\)-axis improved by about \(82\%\) in the case of using \((P_{g}=\frac{1}{Cl_{g}^{2}};P_{g}=\frac{1}{Cl_{r}^{2}})\) in relation to the \(DY\) results determined for weights \((P_{g}=\frac{1}{ns_{g}};P_{r}=\frac{1}{ns_{r}})\). The \(DZ\) position errors ranged from \(-2.021\) m to \(-0.228\) m for \((P_{g}=\frac{1}{ns_{g}};P_{r}=\frac{1}{ns_{r}})\). On the other hand, for \((P_{g}=\frac{1}{Cl_{g}^{2}};P_{g}=\frac{1}{Cl_{r}^{2}})\) weighing, the position errors were \(-1.604\) m to \(+0.295\) m. It is worth noting that the positioning accuracy along the \(Z\)-axis improved by over \(59\%\) when \((P_{g}=\frac{1}{Cl_{g}^{2}};P_{g}=\frac{1}{Cl_{r}^{2}})\) weighting was used in relation to the \(DZ\) results determined for the \((P_{g}=\frac{1}{ns_{g}};P_{r}=\frac{1}{ns_{r}})\) weighing process. The aircraft positioning results obtained during the research using the PPP method for the GPS and GLONASS solutions showed the high quality and accuracy of the moving object's determined coordinates. The presented research method significantly improved the accuracy of PPP GPS and PPP GLONASS positioning in relation to the RTK solution. The obtained research results showed that the applied computational scheme of the mathematical model fits well in the modern trend of scientific research on the application of the PPP method in air navigation, as in other works [6; 7; 8; 9; 10; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23; 24; 25; 26; 27; 28; 29; 30; 31; 32; 33; 34]. That is important, because the developed computational algorithm improved the performance of position determination and, at the same time, the accuracy of PPP positioning, as in works [6; 7; 8; 9; 10; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23; 24; 25; 26; 27; 28; 29; 30; 31; 32; 33; 34].