Distributed Optimal Spatial–Temporal Cooperative Pursuit Guidance for Multi-UAV Interception

This research focuses on a cooperative guidance scenario involving multiple unmanned aerial vehicles (UAVs). The objective is to achieve a simultaneous interception of a maneuvering target while maintaining strict constraints on the relative geometry. To tackle this challenge, we introduce a distributed optimal spatial–temporal cooperative pursuit strategy. Initially, the impact angles and interception times for each UAV are analytically predicted based on the augmented ideal proportional navigation (AIPN) guidance scheme. Subsequently, we employ an optimal distributed consensus protocol to synchronize the UAVs, ensuring they converge on the target at the same time while preserving a predetermined intercept geometry. The proposed method offers significant advantages in a distributed framework, notably reducing control energy consumption by approximately 63.0% compared to an existing state-of-the-art cooperative guidance law. Comprehensive simulations are conducted to validate the energy efficiency of the approach.