宽带子阵域特征空间稳健对角减载波束形成

针对宽带子阵域自适应波束形成器在实际使用中稳健性下降、对弱信号的检测能力受信噪比限制的问题，提出了一种宽带子阵域特征空间稳健对角减载自适应波束形成方法.首先提出利用子阵域特征空间投影法修正导引向量并得到球形不确定集的估计，再利用RCB（Robust Capon Beamformer）算法得到约束条件下的最优权值.另一方面，利用子阵域互谱密度矩阵的最小特征值作为子阵域非相关噪声功率的估计并进行对角减载，以最优权值对减载矩阵波束形成得到子带波束输出，对每个窄子带重复上述处理，再将结果非相干叠加即可得到本文方法的最终结果.理论及实验分析表明方法能提高自适应波束形成器的稳健性及输出信噪比.

Broadband Robust Diagonal Reducing Adaptive Beamforming Based on Subarray Subspace

The robustness of broadband adaptive beamformer decreases in practice and the detection ability of weak signal is limited by signal noise ratio (SNR).To solve those problems,a broadband robust diagonal reducing adaptive beamforming based on subarray subspace is proposed.Firstly,the subarray subspace projection method is used to correct signal steering vector,and a spherical uncertainty set is designed to get subarray robust capon beamformer (RCB) weight vector.On the other hand,the least eigenvalue of subarray cross spectral density matrix is proposed as the estimation of non-correlated noise power,and the main diagonal of subarray cross spectral density matrix is subtracted from the noise power and processed by the proposed beamformer.The above process is repeated for each sub-band and all outputs are incoherently summed to obtain the final result of the proposed method.Theoretical and experimental analysis shows that the proposed algorithm can improve the robustness and the output SNR of the adaptive beamformer.