一种稳健自适应波束形成的变量对角加载方法

Roubust Adaptive Beamforming with Variable Diagonal Loading

在设计稳健的自适应波束形成算法来消除阵列流形中的非确定性方面已经投入了很大的努力。这些不确定性可能由波达方向(DOA)的不确定性、阵列结构不理想、远近效应、相互耦合和其他的失配以及建立模型错误造成。提出了一种可供选择实现的包含椭球不确定约束导引矢量的线性约束最小方差(LCMV)的波束形成方法,更详细地说,真实的导引矢量是根据预测导引矢量采用将椭球约束施加到估计的导引矢量的递归最陡下降算法来估计的,对角加载技术必须满足椭球约束,其主要缺点是如何通过对非确定性约束的认识来得到最优的对角加载值不是很明确。通过这个问题的解决证明了该方法的可行性,而且对角加载技术是通过变量加载集成到自适应机制中而不是固定对角加载或Ad Hoc技术。

Significant effort has gone into designing robust adaptive beamforming algorithms to improve robustness against uncertainties in array manifold. These uncertainties may be caused by uncertainty in Direction of Arrival （DOA）, imperfect array calibration, near- far effect, mutual coupling, and other mismatch and modeling errors. An alternative realization of the robust adaptive linearly constraint on the steering vector is proposed. More specifically, the genuine steering vector is estimated from the presumed steering vector using Recursive Steepest Descent（RSD）algorithm with the ellipsoidal constraint imposed on the estimated steering vector. A diagonal loading technique is obligatory to satisfy the ellipsoidal constraint. The main draw- back of the diagonal loading technique is that it is not clear how to get the optimal value of diagonal loading level based on the recognized level of uncertainty constraint. In this paper, this drawback is tackled whereas the diagonal loading technique is integrated into the adaptive update scheme by means of Variable Loading（VL） technique rather than fixed diagonal loading or Ad Hoc technique.