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This paper studies the event-triggered distributed fusion estimation problemsfor a class of nonlinear networked multisensor fusion systems without noisestatistical characteristics. When considering the limited resource problems oftwo kinds of communication channels (i.e., sensor-to-remote estimator channeland smart sensor-to-fusion center channel), an event-triggered strategy and adimensionality reduction strategy are introduced in a unified networkedframework to lighten the communication burden. Then, two kinds of compensationstrategies in terms of a unified model are designed to restructure theuntransmitted information, and the local/fusion estimators are proposed basedon the compensation information. Furthermore, the linearization errors causedby the Taylor expansion are modeled by the state-dependent matrices withuncertain parameters when establishing estimation error systems, and thendifferent robust recursive optimization problems are constructed to determinethe estimator gains and the fusion criteria. Meanwhile, the stabilityconditions are also proposed such that the square errors of the designednonlinear estimators are bounded. Finally, a vehicle localization system isemployed to demonstrate the effectiveness and advantages of the proposedmethods.

Distributed Event-Triggered Nonlinear Fusion Estimation under Resource Constraints