## 5 Basic Results  
To study a simple case numerically, a DL scenario with \(y(x)=0\) was simulated by the suggested algorithm. The essential parameters of this scenario, the flight profile and the radiation pattern characteristics, are listed in Tables 1 and 2, respectively. Figure 3 represents the flight profile of the airborne GNSS receiver. An unintentional _Source_ of interference with an Effective Radiation Power (ERP) of 20 dBW and an isotropic antenna operates at (10, 0, 0.025). The installation/operational height of this transmitter can be selected arbitrarily, but the selected value is nominal for ground-based and mast-installed antennas. The graphical representation of the physical orientation of the radiation pattern of the GNSS antenna in the _XZ_-plane, the DoA and the AoA, are shown in Figure 3. If the _XZ_-plane is associated with the antenna's E-plane, then the H-plane representation would be in the _YZ_-plane. In our case, as the dynamics of the flying platform requires the onboard GNSS receiver to be able to perform direction-independent navigation, the E- and H-plane radiation patterns were assumed to be identical, but they can be set arbitrarily or by using the measured values of real antennas. While Figure 2 simplifies the 3D representation of AoA in two dimensions, it should be noted that the DoA is a vector in a 3D space, and so it can be calculated directly from its _XZ_ and _XY_ (E- and H-plane) components. The calculated AoAs can be associated with their respective antenna gains in perpendicular planes. Also, to preserve the radiation patterns' analytical aspect, any simulated radiation pattern must have identical E- and H-plane maximum values at their extremum points, i.e., at the patterns' main lobe. In this case, these maximum values for the E- and H-planes are set at 7 dBi. The calculated \(P_{RX}\) is shown in Figure 4. The \(P_{RX}\) is higher when the  
as constant, the flight profile can be rotated along the \(z\)-axis at any desired resolution, called the _Angular Resolution_ of the algorithm, and denoted as \(\theta_{R}\). On the other hand, the maximum distance for which the calculation will be performed is divided into sections, denoted as \(\Delta x\). For this case, it was assumed that \(\theta_{R}=0.1^{\circ}\) and \(\Delta x=10\) m. If \(\theta_{Rotation}=n\theta_{R}\), the \(P_{RX}(m\Delta x,\,\theta_{Rotation})\) for various values of \(n\) (covering [0, 2\(\pi\))) and \(m\) (covering [0, 30 km]) were calculated and are illustrated in Figure 5. This plot shows useful and operation-oriented information about the \(P_{RX}\) and its angular dependency and is known as a Spatial Interference Distribution Expression Heat-map (SPIDEH). While a SPIDEH may appear to be complicated, the concept is simple: any horizontal line represents the \(P_{RX}\) for the desired approach direction, and any vertical line relates to the various possible \(P_{RX}\) values at the desired distances. For example, Figures 6 and 7 represent the \(P_{RX}\) (\(x=20\) km, \(\theta_{Rotation}=[0,2\pi]\)) and \(P_{RX}\) (\(x=[0,30\) km), \(\theta_{Rotation}=180^{\circ}\)), respectively. The horizontal axis of the SPIDEH graph, the x parameter, represents the line-of-sight distance of the flying platform from the landing site, or LoS-DILS. The exact location can also be calculated. The SPIDEH graph shows two straight (dashed) lines. The intersection of these two straight lines at (20 km, 180\({}^{\circ}\)) are also represented in Figures 6 and 7. The maximum value of \(P_{RX}\) in Figure 5, \(P_{RX}\) (10), can be represented in the SEPIDEH graph and is associated with \(P_{RX}\) (10, 0\({}^{\circ}\)). This information implies that the curve of the receiver's power in Figure 4 is a row of data at \(\theta_{Rotation}=0^{\circ}\) in a SEPIDEH graph. This type of  
Figure 5: The SPIDEH graph of a landing scenario. \(P_{RX}\)(10, 0, 0.025), the maximum \(P_{RX(\max)}\) is at 10 km and \(\theta_{Rotation}=0^{\circ}\).