面向多弹拦截的分布式非均衡一致性目标分配算法

A distributed unbalanced consensus target assignment algorithm is proposed to address the multi-to-one assignment problem in a distributed self-organizing missile swarm for intercepting airborne targets. Taking into account the bidirectional communication and characteristics of distributed task allocation within a limited neighborhood，we have developed a distributed target assignment model and a multi-step consensus auction algorithm based on dynamic situational awareness. By decomposing the remaining target value over multiple steps，this approach facilitates unbalanced auction selection for multiple missiles targeting a single Unmanned Aerial Vehicle. Furthermore，an extended multi-step consensus conflict resolution rule has been formulated by enhancing the consensus rules of the consensus-based bundle algorithm，thereby ensuring consistency in the results of distributed unbalanced auctions. Simulation results demonstrate that this method can be effectively applied to online adjustments of unbalanced target allocations for distributed missile swarms，significantly improving interception efficiency against multiple airborne maneuvering targets. In comparison with centralized allocation algorithms， this approach achieves globally suboptimal solutions under optimized temporal conditions.