Globally optimal distributed fusion white noise deconvolution estimator

In this paper, a distributed fusion white noise deconvolution estimator is presented for the multisensor linear discrete systems with different measurement matrices and correlated measurement noises. It is globally optimal because it is derived from the centralized fusion white noise deconvolution estimator and is identical to the centralized fuser. The proposed white noise fuser is obtained based on the local Kalman predictors. Compared with the existing globally suboptimal distributed fusion white noise estimators, the computation of complex covariance matrices is avoided. The effectiveness of the proposed results is shown by a Monte Carlo simulation for the Bernoulli-Gaussian input white noise.