Improved algorithm of multi-mainlobe interference suppression under uncorrelated and coherent conditions  

非相关/相干环境下多主瓣干扰抑制改进算法

在线阅读下载全文

作  者:CAI Miaohong CHENG Qiang MENG Jinli ZHAO Dehua 蔡苗红;程强;孟晋丽;赵德华(南京电子技术研究所,南京210039;雷达探测感知全国重点实验室,南京210039;江苏省探测感知技术重点实验室,南京210039)

机构地区:[1]Nanjing Research Institute of Electronics Technology,Nanjing 210039,China [2]National Key Laboratory of Radar Detection and Sensing,Nanjing 210039,China [3]Jiangsu Provincial Key Laboratory of Detection and Sensing Technology,Nanjing 210039,China

出  处:《Journal of Southeast University(English Edition)》2025年第1期84-90,共7页东南大学学报(英文版)

基  金:The National Natural Science Foundation of China(No.U19B2031).

摘  要:A new method based on the iterative adaptive algorithm(IAA)and blocking matrix preprocessing(BMP)is proposed to study the suppression of multi-mainlobe interference.The algorithm is applied to precisely estimate the spatial spectrum and the directions of arrival(DOA)of interferences to overcome the drawbacks associated with conventional adaptive beamforming(ABF)methods.The mainlobe interferences are identified by calculating the correlation coefficients between direction steering vectors(SVs)and rejected by the BMP pretreatment.Then,IAA is subsequently employed to reconstruct a sidelobe interference-plus-noise covariance matrix for the preferable ABF and residual interference suppression.Simulation results demonstrate the excellence of the proposed method over normal methods based on BMP and eigen-projection matrix perprocessing(EMP)under both uncorrelated and coherent circumstances.为研究多主瓣干扰抑制,提出了一种基于迭代自适应算法(IAA)与阻塞矩阵预处理(BMP)的新方法。为克服常规自适应波束形成(ABF)方法存在的缺陷,提出了应用IAA进行空间谱的准确估计与干扰源到达方向(DOA)的准确估计,其中主瓣干扰分量主要通过方向导向矢量(SVs)之间相干系数的计算进行识别,并利用阻塞矩阵预处理(BMP)进行剔除。利用IAA进行旁瓣干扰与噪声协方差矩阵重构,从而实现更优ABF与剩余干扰抑制。仿真结果表明,无论在非相关或相干干扰环境下,所提方法与常规基于BMP或特征投影矩阵预处理(EMP)的方法相比均具有更优性能。

关 键 词:mainlobe interference suppression adaptive beamforming spatial spectral estimation iterative adaptive algorithm blocking matrix preprocessing 

分 类 号:TN95[电子电信—信号与信息处理]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象