基于经验模态分解的有限阵元宽带自适应阵列DBF方法

针对有限阵元条件下宽带自适应阵列自由度不够和抗干扰性能下降的问题,提出一种基于经验模态分解(Empirical mode decomposition,EMD)的宽带自适应阵列数字波束形成(Digital beamforming,DBF)方法。该方法首先对阵元接收的快拍数据进行EMD处理,然后对各个模态函数矩阵应用线性约束最小方差(Linearlyconstrained minimum variance,LCMV)波束形成算法求解自适应权矢量,最后对信号进行重构。与传统的基于快速傅里叶变换(Fast Fourier transform,FFT)子带自适应阵列方法相比,该方法具有以下优势:适用于阵元数目受限的宽带自适应阵列,无需事先指定模态函数划分的频段,可以提高阵列处理的自由度。仿真验证了所提方法的有效性。

Limited Elements Wideband Adaptive Array DBF Method Based on Empirical Mode Decomposition

To solve the problem of anti-jamming degradation and insufficient freedom for wideband adaptive array with limited array elements,a new wideband digital beamforming(DBF) method based on empirical mode decomposition(EMD) is proposed.Firstly,the received snapshot data of each array element are decomposed by using EMD,and then linearly constrained minimum variance(LCMV) beamforming algorithm is applied on each intrinsic mode function(IMF) matrix to optimize adaptive weight vector.Finally,the signal is reconstr...