论文标题
通过事件触发的通信分布式Kalman过滤：一种强大的方法
Distributed Kalman filtering with event-triggered communication: a robust approach
论文作者
论文摘要
在情况下，我们考虑了传感器网络的分布式Kalman过滤的问题，数据传输有限制，并且存在模型不确定性。更确切地说，我们提出了一种分布式过滤策略，并通过事件触发的通信，其中根据最不利的模型计算状态估计器。后者属于关于名义模型的球（在Kullback-Leibler拓扑中）。我们还提出了一个初步的数值示例，以测试提出的策略的性能。
We consider the problem of distributed Kalman filtering for sensor networks in the case there is a limit in data transmission and there is model uncertainty. More precisely, we propose a distributed filtering strategy with event-triggered communication in which the state estimators are computed according to the least favorable model. The latter belongs to a ball (in Kullback-Leibler topology) about the nominal model. We also present a preliminary numerical example in order to test the performance of the proposed strategy.
