【摘要】 应用Kalman滤波方法 ,基于Riccati方程 ,在线性最小方差最优信息融合准则下 ,提出了两传感器最优信息融合白噪声反卷积滤波器。同单传感器情形相比 ,可提高滤波精度。它可应用于石油地震勘探信号处理。一个信息融合Bernoulli Gaussian白噪声反卷积滤波器的仿真例子说明了其有效性更多还原

【Abstract】 Using the Kalman filtering method, under the linear minimum variance optimal information fusion criterion, the two-sensor information fusion white noise deconvolution filter is presented based on Riccati equation. Compared with the single sensor case, the accuracy of the estimators is improved. It can be applied to signal processing in oil seismic exploration. A simulation example for Bernoulli-Gaussian white noise shows its effectiveness?更多还原