一种基于特征空间的盲波束形成算法

绝大多数通信信号都具有周期平稳信号特性。利用信号的周期平稳特性可以进行真正的盲自适应波束形成，因而受到了广泛关注。ＣＡＢ类算法就是其中的一种。它的运算量较小，但鲁棒性不够强。本文针对其不足，提出了一种基于特征空间的盲波束形成算法。该算法将估计的导引矢量约束在信号子空间，降低了目标信号含于自相关估计矩阵和有限次快拍相关阵引起的子空间扰动的影响，提高了算法的收敛速度和鲁棒性。同时，目前用于进行子空间分解的新算法层出不穷，运算量不断降低。因此，本文提出的盲算法具有很强的实用性和广阔的应用前景。计算机仿真验证了理论分析。

An Eigenspace-Based Blind Beamforming Algorithm

Most man made communication signals are cyclostationary. Because the blind beamforming algorithms using cyclostationary signal properties are the ge nuine blind algorithms, they attract much attention. CAB algorithm is one of these algorithms. The computation complexity of CAB is simple, but the robustness of which is not enough. To overcome the shortcomings a new eigenspace based blind beamformer is presented. The new algorithm projects the estimation of the steering vector onto the signal plus interference subspace, decreases the disturbance of the signal plus interference and the noise subspace of the sample correlation matrix. Hence, it improves the convergence speed and the robustness. Computer simulations verify the effect of the theoretical analysis.