Optimal multi-sensor Kalman smoothing fusion for discrete multichannel ARMA signals
Shuli SUN
摘要：Based on the multi-sensor optimal information fusion criterion weighted by matrices in the linear minimum variance sense,using white noise estimators,an optimal fusion distributed Kalman smoother is given for discrete multi-channel ARMA (autoregressive moving average) signals.The smoothing error cross-covariance matrices between any two sensors are given for measurement noises.Furthermore,the fusion smoother gives higher precision than any local smoother does.
机标关键词：white noise estimatorsinformation fusionminimum varianceoptimal fusionmoving average
分类号：TP13(自动化基础理论)TL361(核反应堆工程)
资助基金：国家自然科学基金(60374026)黑龙江省杰出青年科学基金(QC04A01)Science and Technology Foundation of education office of Heilongjiang Province(10541174)黑龙江大学校科研和教改项目(JC200404)
论文发表日期：2005-01-01
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：5( 168-172 )
英文信息