多傳感器分布式融合白噪聲反卷積濾波器
Multisensor Distributed Fusion White Noise Deconvolution Filter
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摘要: 基于Kalman濾波方法和白噪聲估計(jì)理論，在按矩陣加權(quán)線性最小方差最優(yōu)融合準(zhǔn)則下，提出了帶ARMA有色觀測噪聲系統(tǒng)的多傳感器分布式融合白噪聲反卷積濾波器，其中推導(dǎo)出用Lyapunov方程計(jì)算最優(yōu)加權(quán)的局部估計(jì)誤差互協(xié)方差公式。與單傳感器情形相比，可提高融合估值器精度。它可應(yīng)用于石油地震勘探信號處理。一個(gè)三傳感器分布式融合Bernoulli-Gauss白噪聲反卷積平滑器的仿真例子說明了其有效性。
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關(guān)鍵詞:
- 信息融合;分布式融合;反射地震學(xué);白噪聲估值器;Kalman濾波方法
Abstract: Based on the Kalman filtering method and white noise estimation theory, under the linear minimum variance optimal information fusion criterion weighted by matrices，a multisensor distributed fusion optimal white noise deconvolution filter is presented for systems with ARMA colored measurement noise，where the formulas of computing cross-covariances among local estimation errors by Lyapunov equations are derived，which is applied to compute optimal weights．Compared to the single sensor case， the accuracy of fused estimators is improved． It can be applied to signal processing in oil seismic exploration． A simulation example for three-sensor distributed fusion Bernoulli-Gaussian white noise deconvolution smoother shows its effectiveness． -
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