Event-Triggered Distributed Fusion for Multirate Multisensor Systems With Heavy-Tailed Noises
针对多速率多传感器系统在数据包丢失和重尾噪声下的分布式融合问题，提出事件触发局部估计器和基于顺序快速协方差交叉的分布式融合算法，并给出误差有界条件。
In this article, event-triggered distributed fusion is investigated for a multirate multisensor system subject to heavy-tailed noises under packet dropout. The heavy-tailed noises are modeled by a multivariate <inline-formula> <tex-math notation="LaTeX">$t$ </tex-math></inline-formula>-distribution for the multirate multisensor system. An event-triggered local estimator is designed to gain local estimates with packet dropout in communication networks. An event-triggered distributed fusion algorithm is proposed by sequential fast covariance intersection (SFCI) fusion technology. Sufficient conditions on the boundedness of the estimation error scale matrices are given for the event-triggered local estimator and distributed fusion. Finally, numerical simulation is put forward to indicate validity of the presented event-triggered local estimator and distributed fusion.