### Simulation Test #5, a Post-Avalanche Scenario  
The primary objective of this section is to prove the effectiveness of the proposed navigation algorithm in a SAR mission for locating a missing skier. An illustrative example is shown in Figure 15, where a swarm of UAVs identifies the missing individual, points towards the target and subsequently awaits the rescue phase by hovering over the skier. To address this issue, consider a swarm of \(N\) UAVs flying at a fixed altitude whose guidance algorithm is based on the DTG-based approach [47]. This approach ensures that the the swarm remains distributed and scalable, without a leader-follower architecture, while maintaining a local triangular topology that is highly efficient in terms of the packing problem. The integrated GNC scheme is depicted in Figure 16, which provides an overview of the overall architecture and the information flow between the high-level DTG-based guidance and control and the consensus-based navigation modules. Figure 14: **(a–c)** Simulation Test #4—Comparison of the estimates of the target position considering three different communication delays. \(X_{t}\), \(Y_{t}\) and \(Z_{t}\) represents the real \(X\), \(Y\) and \(Z\) coordinates of the target, while \(\hat{X}_{t}^{1}\), \(\hat{Y}_{t}^{1}\) and \(\hat{Z}_{t}^{1}\) are the estimates made by \(UAV_{1}\). The subscripts \(d1\), \(d2\) and \(d5\) represent, respectively, communication delays of \(t_{d1}=0.1\) s, \(t_{d2}=0.2\) s and \(t_{d5}=0.5\) s.  
The proposed scenario represents a simplified environment with no disturbances, such as wind. It is also assumed that the swarm is homogeneous, consisting of the same type of quadrotors. We have assumed perfect conditions for communication and reconnaissance of the search area. Therefore, no communication delays and no loss of precision over greater distances are considered. Furthermore, the take off and landing of UAVs are not modeled; it is assumed that all UAVs have already been launched at the beginning of the scenario and are flying at a fixed altitude. Battery consumption is not included in the model. The case study takes into account real research techniques in post avalanche scenarios. The most known search strategies are the parallel track and creeping line search. They involve maintaining parallel tracks, with the former being parallel to the major axes and the latter parallel to the minor axes. These strategies are suitable for uncertain target locations and flat terrain, ensuring uniform coverage. The typical post-avalanche zones to be surveyed are usually small [48]; in this section, the operational scenarios are defined over an area of \([200\times 100]\) m. Two scenarios are provided, with the same area and different positions of the skier, as summarized in Table 8.  
Given the search area, a formation of 5 UAVs was deployed, flying at a fixed altitude of 5 m and cruising at a speed of 3 m/s. To cover the selected search area, two coverage techniques were explored, as they are the most suitable for this type of mission: the parallel track technique was used in  
Figure 16: Proposed GNC algorithm architecture and information flow between the high-level modules. \begin{table}
\begin{tabular}{c c} \hline \hline
**Scenario ID** & **Skier Position (m)** \\ \hline
1 & \(S_{s}=[100,180,0]^{T}\) \\
2 & \(S_{s}=[140,50,0]^{T}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Real position of the Skier. Figure 15: Simulation Test #5—Representative example of a SAR activity for a missing skier equipped with ARTVA device. The red arrows indicate the communication link between the UAVs. scenario #1 (Figure 17) and the creeping line in scenario #2 (Figure 18). Both search paths have the same length and guarantee complete surveillance of the defined area. UAV starting positions for both operational scenarios are given in Table 9.  
The ARTVA receiver is the device responsible for detecting the presence of the skier under the snow. Its operational range is currently about 60 m [49].