多通道ARMA信號信息融合Wiener濾波器
Multichannel ARMA Signal Information Fusion Wiener Filter
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摘要: 應(yīng)用Kalman濾波方法,基于白噪聲估計(jì)理論,在線性最小方差最優(yōu)信息融合準(zhǔn)則下,提出了多通道ARMA信號的兩傳感器信息融合穩(wěn)態(tài)最優(yōu)Wiener濾波器、平滑器和預(yù)報(bào)器;給出了最優(yōu)加權(quán)陣和最小融合誤差方差陣.與單傳感器情形相比,可提高濾波精度.一個(gè)雷達(dá)跟蹤系統(tǒng)的仿真例子說明了其有效性.Abstract: Using the Kalman filtering method, based on white noise estimation theory, under the linear minimum variance information fusion criterion, two-sensor information fusion steady-state optimal Wiener filter, smoother and predictor are presented for the multichannel Auto-Regressive Moving Average（ARMA） signals, where the optimal weighting matrices and minimum fused error variance matrix are given. Compared with the single sensor case, the accuracy of the filter is improved. A simulation example of a radar tracking system shows its effectiveness.
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何友,王國宏,陸大金,彭應(yīng)寧.多傳感器信息融合及其應(yīng)用.北京:電子工業(yè)出版社,2000:1-11.[2]鄧自立.自校正濾波理論及其應(yīng)用--現(xiàn)代時(shí)間序列分析方法.哈爾濱:哈爾濱工業(yè)大學(xué)出版社,2003:1-375.[3]鄧自立.卡爾曼濾波與維納濾波--現(xiàn)代時(shí)間序列分析方法.哈爾濱:哈爾濱工業(yè)大學(xué)出版社,2001:279-390.[4]鄧自立.最優(yōu)濾波理論及其應(yīng)用--現(xiàn)代時(shí)間序列分析方法.哈爾濱:哈爾濱工業(yè)大學(xué)出版社,2000. -
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