无人机群状态一致性共识是实现无人机协同作业的重要保障。现有状态一致性共识方法大多应用于分布式数据库、区块链等场景，具有网络拓扑稳定、任务需求简单等特点。然而，无人机群的高动态性导致网络连接脆弱、状态多样并存等问题，现有状态一致性共识方法难以适用。针对上述问题，提出了一种无人机群状态一致性共识架构，为保障无人机群协同作业能力提供了理论支撑。首先，分析无人机群状态一致性在模型、协议、网络三个方面存在的问题，总结并归纳现有研究工作。其次，基于BASE（Basically Available-Soft state-Eventually consistent）和ACID（Atomicity-Consistency-Isolation-Durability）理论，建立软状态与弱一致性的关联关系，设计弱连接下多集群软分叉异步共识协议。最后，在飞行自组网（Flying Ad-hoc Network，FANET）中进行的仿真实验结果表明，该架构能够满足高动态无人机群状态一致性共识需求。

The consensus on the state consistency of unmanned aerial vehicle (UAV) swarms is a crucial guarantee for the collaborative operations. The existing state consistency consensus methods are mostly applied in scenarios such as distributed databases and blockchain, and are characterized by stable network topology and simple task requirements. However, the high dynamics of UAV swarms lead to issues such as fragile network connections and diverse coexisting states, making it difficult for the existing state consistency consensus methods to be applicable. To address these issues, a state consistency consensus architecture for UAV swarms was proposed, providing theoretical support for ensuring the collaborative capabilities of UAV swarms. Firstly, it analyzes the problems existing in the state consistency of UAV swarms were analyzed in terms of models, protocols, and networks, and the existing research was summarized. Secondly, based on the Basically Available-Soft state-Eventually consistent (BASE) and Atomicity-Consistency-Isolation-Durability (ACID) theories, a relationship between soft state and weak consistency was established, and an asynchronous consensus protocol was designed for multi-cluster soft forks under the weak connections. Finally, simulation experiment results conducted in a flying ad-hoc network (FANET) showed that the proposed architecture could meet the state consistency consensus requirements of the high-dynamic UAV swarms.