Multisensor Information Fusion White Noise Deconvolution Filter with Colored Noise

摘要：

Based on the Kalman filtering method and white noise estimation theory, under linear minimum variance information fusion criterion weighted by scalars, a multisensor optimal information fusion white noise deconvolution filter is presented for multisensor systems with system deviation,ARMA colored measurement noise and white noise. The formula of computing cross-covariances among filtering errors of sensors is presented, which can be applied to compute the optimal fused weighting coefficients. Compared to the single sensor case, the accuracy of fused filtering is improved. It can be applied to signal processing in oil seismic exploration. A simulation example for 3- sensor information fusion Bernoulli-Gaussian white noise deconvolution filter shows its effectiveness.

关键词： Kalman filtering white noise estimation information fusion deconvolution colored measurement noise

作者: Xin Wang Qidan Zhu Liqiu Jing Linan Tao

作者单位: Department of Automation Harbin,Heilongjiang Province,150001,China Harbin Engineering University Harbin,Heilongjiang Province,150001,China Heilongjiang University Harbin,Heilongjiang Province,150001,China

会议类型: 国际会议

会议名称: 2010 IEEE信息与自动化国际会议(ICIA 2010)

会议地点: 哈尔滨

会议语种:英文

页码: 1-5

在线出版日期: 2010-06-20（万方平台首次上网日期，不代表论文的发表时间）