RFI suppression in UWB-SAR based on TH neural network

被引：0
|
作者：
Huang, Xiaotao [1 ]
Liang, Diannong [1 ]
Zhou, Zhimin [1 ]
机构：
[1] Natl Univ of Defence Technology, Changsha, China
来源：
Tien Tzu Hsueh Pao/Acta Electronica Sinica | 2000年 / 28卷 / 09期
关键词：
Adaptive filtering - Image processing - Interference suppression - Neural networks - Radio interference - Signal filtering and prediction - Simulation;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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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页码：23 / 26
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