Event-triggered sequential fusion filters for multi-sensor systems with multiplicative noises

This paper combines an event-triggered mechanism with a multiplicative noise system to reduce the communication congestion and the calculation workload of the networked fusion center, and proposes an event-triggered Sequence Covariance Intersection and Sequence Inverse Covariance Intersection fusion algorithm based on the above system. It is mentioned that the event-triggered fusion algorithms are robust with respect to the unknown cross-covariances, and have higher fault tolerance and stability than the previous fusers. Validity of the proposed algorithm is demonstrated by studying arithmetic examples.