 This paper proposes a distributed navigation strategy for UAVs in post-Avalanche search and rescue operations, utilizing formations to increase efficiency and robustness while reducing payload. The proposed algorithm uses the Kalman filter based on consensus and internal transformation theory to improve scalability and dynamic equivalence between global and local models. Tested in two realistic scenarios, the approach shows promising results for detecting victims and maintaining situational awareness while avoiding unsearched areas, offering an alternative to human-intensive SAR missions. This article was authored by Salvatore Rosario-Basalillo, Aguidio D'Amato, Massimiliano Mate, and others.