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水平机扫雷达的副瓣干扰对消算法研究
引用本文:王峰,傅有光,孟兵.水平机扫雷达的副瓣干扰对消算法研究[J].现代雷达,2008,30(8).
作者姓名:王峰  傅有光  孟兵
作者单位:南京电子技术研究所,南京,210013
摘    要:采用采样矩阵逆算法(SMI)对消副瓣干扰,一般抽取部分样本对消整段数据的干扰。当雷达阵面处于旋转扫描状态时,由于角度的变化,该对消性能下降很快。该文提出了采用递归最小二乘算法(RLS)对剩余数据进行跟踪收敛的方法,SMI RLS算法收敛速度快,且逐点样本迭代,能够跟踪干扰相对于阵面角度的变化,从而保证了对消比。同时给出了降低RLS算法计算量的方法。仿真表明,间歇算法在牺牲部分对消性能的前提下,可有效降低计算量。

关 键 词:副瓣干扰对消  递归最小二乘  采样矩阵逆

Sidelobe Jamming Cancellation Technique for Circular Scanning Radar
WANG Feng,FU You-guang,MENG Bing.Sidelobe Jamming Cancellation Technique for Circular Scanning Radar[J].Modern Radar,2008,30(8).
Authors:WANG Feng  FU You-guang  MENG Bing
Abstract:When applying the Sampling Matrix Inversion(SMI) algorithm to the side-lobe cancellation scenarios,only part of the sampling data is used for simplicity.If the radar is working in a kind of circular scanning mode,the cancellation performance will be degraded greatly because of the jammer changing incident angle.The Recursive Least Square(RLS) algorithm is used to track the residual data.By iterating sample by sample,this SMI RLS algorithm can track the changing incident angle,thus the cancellation ratio is guaranteed.In order to simplify the RLS algorithm,a kind of integral spacing iteration method is utilized with only a little performance degradation.The performance is demonstrated by computer simulation.
Keywords:side-lobe jamming cancellation  sampling matrix inversion  recursive least square
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