Consensus-based distributed filtering with fusion step analysis

For consensus on measurement-based distributed filtering (CMDF), through infinite fusion operations during each sampling interval, node in the sensor network can achieve optimal performance with centralized filtering. However, due to limited communication resources physical systems, number of steps cannot be infinite. To deal this issue, present paper analyzes CMDF finite operations. First, by introducing a modified discrete-time algebraic Riccati equation and several novel techniques, convergence estimation error covariance matrix is guaranteed under collective observability condition. In particular, steady-state simplified as solution Lyapunov equation. Moreover, degradation induced reduced frequency obtained closed form, which establishes an analytical relation between that Meanwhile, it provides trade-off cost. Furthermore, shown exponentially converges tending infinity interval. Finally, theoretical results are verified illustrative numerical experiments.