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Networked Filtering With Self Triggered Communication
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AI
DOI：10.1109/LSP.2026.3658225.png)
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Abstract
En 中文
In practical applications, the topology of a sensor network is commonly time-varying and even unknown, but almost all existing networked filtering methods rely on this unavailable topology information. In view of this, we investigate a topology ignorant communication scheme that does not need to know the topology of the network, where nodes use only neighboring information to trigger their activations. The triggering condition considers the estimation accuracy which benefits the purpose of networked filtering (i.e., distributed filtering in sensor network). With this communication mode, we propose a filter: self triggered activation based distributed filter (STA-DF). Its convergence to the centralized estimation along with iteration length and stability are analyzed. Simulation results are provided to verify its superiority to existing methods.
Keywords:
Sensor networks
dynamic systems
networked filtering
diffusion
gossip
Journal
I
IF:
3.9
Papers:
610
Citations:
0