多传感器全局最优观测融合白噪声反卷积滤波器

白噪声反卷积问题在石油地震勘探中具有重要的应用背景。利用Kalman滤波方法提出了多传感器最优观测加权融合白噪声反卷积Wiener滤波器。同集中式和分布式融合方法相比,不仅可得到全局最优白噪声融合估值器,而且可显著地减小计算负担,便于实时应用。一个四传感器Bernoulli-Gaussian白噪声加权观测融合估值器的仿真例子说明了其有效性。

Multisensor Globally Optimal Measurement Fusion White Noise Deconvolution Filter

The white noise deconvolution problem has important application background in oil seismic exploration. The multisensor optimal weighted measurement fusion white noise deconvolution Wiener filter is presented by using the Kalman filtering method. Compared with centralized and decentralized fusion methods, not only it give the globally optimal white noise fusion estimator, but also it can obviously reduce the computational burden, so that it is suitable for real time applications. A simulation example of weighted measurement fusion estimator for a Bernoulli-Gaussian white noise with four-sensor shows its effectiveness.