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 .
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.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2000年第9期23-26,共4页
Acta Electronica Sinica
基金
国防预研重点项目基金!(No .7.5 .3 .2 )
关键词
超宽带合成孔径雷达
射频干扰
神经网络
ultra wideband synthetic aperture radar (UWB SAR)
radio frequency interference (RFI)
AR model
Tank Hopfield (TH) neural network
