## 3 Air-Ground NLOS Identification Method Aided by 3D Terrain Modelling  
### Air-Ground Member-Ray Terrain Intersection Detection Methods  
To suppress the NLOS effect and improve the positioning accuracy in GNSS, the relative orientation and elevation angle of the user and the satellite can be compared with the terrain contour in the 3D digital map, i.e., analyzing the terrain cover angle to judge the satellite visibility and separating the NLOS information [15; 16; 17]. If the satellite is visible to the user, the signal is an LOS signal; otherwise, it is an NLOS signal with NLOS errors and should be separated. As shown in Figure 2, the user receives signals from both Satellite 1 and Satellite 2 in the direction of the azimuthal angle \(\alpha\) of the user's location; Satellite 1's elevation angle \(\beta_{1}\) is larger than the terrain cover angle \(\beta_{terrain}\), thus Satellite 1 is assumed to be visible and the signal is not affected by NLOS effects. On the other hand, the elevation angle \(\beta_{2}\) of Satellite 2 is lower than the terrain cover angle \(\beta_{terrain}\), thus Satellite 2 is assumed to be invisible and its signal should be excluded from the position calculation. The traditional 3D terrain modelling visibility prediction method based on angles is effective in mitigating NLOS errors in GNSS-only systems. By calculating the angle between the vehicle and the satellite signal or building, it is possible to identify and separate NLOS-affected signals, thus improving the accuracy and reliability of positioning. However, in cooperative navigation systems, the GNSS-UAV cooperative navigation system can be used as an example. The nearby LOS signal could be mistakenly removed, as shown in Figure 3. When the anchor UAV is between the user and high terrain, although the user and UAV are visible to each other, since the UAV's elevation angle is lower than the terrain cover angle, the visibility prediction algorithm mistakenly assumes that the UAV is invisible and excludes its signal. This mistake weakens the cooperative position geometry and accuracy. Compared with the traditional angle-based method, the visible vector masking method combined with the 3D terrain has different intersections with the building terrain at different distances for the same angle, and other intersections can be effectively ruled out after fixing the distance, and the NLOS can be distinguished using the traditional angle-based method by focusing only on the building's silhouette. Figure 2: Traditional visibility prediction method. In complex terrain environments, NLOS signals are propagated by terrain reflection, and normal LOS signals are propagated along straight lines. The NLOS signals can be identified and separated by determining whether the light vector between the cooperative navigation signal source and the navigation signal receiver intersects the octree 3D terrain modelling. LOS intersection detection (ray-tracing) algorithms are employed to find the earliest target hit by a given vector of light rays passing through a scene consisting of polygons or other objects while tracking that ray. Ray tracing also has important applications in the field of wireless communications to generate realistic channel data. Ray-tracing simulators can be used to evaluate beamforming techniques to optimize the directionality and coverage of antenna arrays by simulating the propagation paths of signals in space [18]. Ray tracing simulates the propagation paths of wireless signals in complex environments, thus improving the accuracy of positioning techniques, especially in environments with significant multipath effects. Suppressing NLOS errors by constructing 3D digital terrains and predicting the visibility of GNSS satellites or cooperative navigation information sources in complex terrain environments was the subject of many studies [19; 20; 21; 22; 23]. The octree structure is a tree data structure based on recursive partitioning, which is mainly used for searching and storing in 3D space [24; 25; 26; 27].