多传感器信息融合是信息处理领域的研究热点之一。分布式传感网络节点估计值间互协方差参数未知，使许多信息融合策略及求解方法不再有效。本课题考虑节点间传输能力受限、有限时间一致性、多传感器精度选型准则以及算法复杂度等多种因素，采用协方差交叉、事件触发机制、线性矩阵不等式和粒子群优化等方法，研究与互协方差参数及融合顺序无关的快速分布式鲁棒融合策略和求解方法、互协方差未知情形下基于事件触发机制的有限时间一致递推估计算法以及误差方差精度指标约束条件下的多传感器精度选型准则。本项目的完成，将进一步丰富多传感器信息融合领域的研究成果，具有重要的理论研究意义和工程应用前景。

Multi-sensor information fusion is one of the hot topics in the field of information processing. The parameters of cross-covariance between nodes in distributed sensor networks are unknown, which makes many information fusion strategies and solution methods no longer valid. Limited transmission capacity in channel, finite-time consistency, accuracy selection criteria in multi-sensor and computational complexity are considered in this project, by means of covariance intersection, event-triggered mechanism, linear matrix inequality and particle swarm optimization and other methods, the fast distributed robust fusion strategy and solving method, which is insensitive to the cross-covariance parameters and the fusion order, is studied. The recursive algorithm based on the event-triggered mechanism with finite-time consistency is proposed and the criterion of multi-sensor accuracy selection under the constraint of variance precision index is also presented. The completion of this project will further enrich the research results in the field of multi-sensor information fusion, which has important theoretical research significance and engineering application prospects.