| 基于TH神经网络的UWB-SAR抑制RFI方法 |
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| 引用本文： | 黄晓涛,梁甸农,周智敏.基于TH神经网络的UWB-SAR抑制RFI方法[J].电子学报,2000,28(9):23-26. |
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| 作者姓名： | 黄晓涛 梁甸农 周智敏 |
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| 作者单位： | 国防科技大学电子科学与工程学院,长沙 410073 |
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| 基金项目： | 国防预研重点项目基金!(No .7.5 .3 .2 ) |
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| 摘 要： | 在超宽带合成孔径雷达(UWB-SAR)系统中,若将接收信号先通过一个自适应预测误差滤波器,然后再进行成像处理运算,能极大改善其抑制射频干扰(RFI)能力.本文提出了一种迅速、有效的抑制RFI方法,它利用谱峰判阶并结合Tank-Hopfield(TH)神经网络计算滤波器权系数,在保持足够的抑制RFI能力的同时,大大提高了运算效率.
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| 关 键 词： | 超宽带合成孔径雷达(UWB-SAR) 射频干扰(RFI) AR模型 Tank-Hopfield(TH)神经网络 |
| 收稿时间： | 1999-01-25 |
RFI Suppression in UWB-SAR Based on TH Neural Network |
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| HUANG Xiao-tao,LIANG Dian-nong,ZHOU Zhi-min.RFI Suppression in UWB-SAR Based on TH Neural Network[J].Acta Electronica Sinica,2000,28(9):23-26. |
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| Authors: | HUANG Xiao-tao LIANG Dian-nong ZHOU Zhi-min |
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| Affiliation: | Institute of Electronic Science and Engineering,National University of Defence Technology,Changsha 410073,China |
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| Abstract: | In ultra wideband synthetic aperture radar (UWB SAR),the radio frequency interference (RFI) suppression capacity can be greatly improved by putting an adaptive predictive error filter before the process of image formation.This paper proposes a fast and efficient method for RFI suppression,which gives the model order by spectral peaks and uses the Tank Hopfield (TH) neural network to compute the coefficients of the filter.The method obtains higher computing efficiency with satisfactory results on interference suppression. |
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| Keywords: | ultra wideband synthetic aperture radar (UWB SAR) radio frequency interference (RFI) AR model Tank Hopfield (TH) neural network |
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