Steady-state Optimal Measurement Fusion White Noise Deconvolution Estimators
会议名称：《2009中国控制与决策会议》
会议日期：2009年
学科分类：11[军事学] 0810[工学-信息与通信工程] 1105[军事学-军队指挥学] 08[工学] 081002[工学-信号与信息处理] 110503[军事学-军事通信学]
基 金：supported by National Nature Science Foundation of China under Grant 60874063
关 键 词：Multisensor Information Fusion Weighted Measurement Fusion White Noise Deconvolution Global Optimality Kalman Filtering
摘 要：White noise deconvolution or input white noise estimation has a wide range of applications including oil seismic exploration,communication,signal processing,and state *** the multisensor linear discrete time-invariant stochastic systems with correlated measurement noises,a steady-state measurement fusion system is obtained by the weighted least square(WLS) method.A steady-state optimal weighted measurement fusion white noise deconvolution estimator is presented using the Kalman filtering *** a new derivation method,it is rigorously proved that the steady-state white noise deconvolution fuser is numerically identical to the centralized steady-state white noise deconvolution fuser,*** has the asymptotically global *** can reduce the computational burden because of the lower dimension of the measurement vector.A simulation example for the Bernoulli-Gaussian input white noise shows the effectiveness of the proposed results.