Surround and Tracking: An Innovative Multi-UAV Collaborative Search Approach for Maritime Rescue Under Imperfect Information

Collaborative search of multiple uncrewed aerial vehicles (UAVs) is a critical technology for maritime rescue operations. To address the challenge posed by an unknown target motion direction, we present an innovative framework, “Dynamic Response-Intelligent Coverage,” and develop a multi-UAV collaborative search model. This study employs a hybrid methodology combining theoretical analysis and simulation optimization. By leveraging the geometric properties of logarithmic spiral (LS) curves, rigorous kinematic modeling and mathematical derivations were conducted to obtain the theoretically optimal solutions for single- and dual-UAV collaborative search. Furthermore, to address the traditional analytical methods’ “curse of dimensionality” issue through a strategy space search and adaptive adjustment mechanism, the genetic-optimization-based multi-UAV collaborative search strategy optimization algorithm (GA-MCSSO) is developed for scenarios involving three or more UAVs. Simulation results demonstrate that: (1) In the dual-UAV search scenario, the simulation optimization results closely align with the theoretically optimal solutions, with highly consistent convergence trajectories; (2) In multi-UAV search scenarios, Compared with SSB and GA-MCSSO-Seq, GA-MCSSO reduces the total coverage time by approximately 32% and improves the cumulative detection probability by approximately 18% under idealized spiral planning conditions. When evaluated under realistic constraints, the absolute improvement in total coverage time averages 0.1–0.2 s, with a maximum gain of nearly 1 s. The theoretical-simulation complementary framework established in this study provides a systematic solution for collaborative search from single UAV to multi-UAV scenarios. The methodology offers technical insights for multi-agent dynamic optimization problems and provides significant theoretical support for practical search operations.