基于干扰协方差矩阵重构的恒定束宽鲁棒自适应波束形成

Frequency-invariant robust adaptive beamforming based on interference covariance matrix reconstruction

针对宽带波束形成中的恒定束宽波束响应优化设计问题与鲁棒性问题展开研究。首先,提出一种基于相位补偿的恒定束宽全局优化设计方法,通过对阵列流形向量进行相位补偿来设计恒定束宽波束,与现有的一些方法相比,该方法不仅能获得全局最优解,而且物理实现简单。同时,还提出一种基于协方差矩阵重构的鲁棒自适应宽带波束形成算法。该算法采用Capon估计器估计样本数据的空间一频率谱密度函数,然后对期望信号波达方向之外的角度区间进行积分来重构干扰加噪声协方差矩阵,最后利用重构的协方差矩阵设计自适应波束形成器权系数。该波束形成器设计问题被表述成凸优化问题求解。仿真结果表明,在整个输入信噪比范围内,该算法几乎都能获得接近理想值的输出信干噪比。

Consider the problems of frequency-invariant beampattern optimization and robustness in broadband beamforming. Firstly, a global optimization algorithm, which is based on phase compensation of the array manifolds, is used to construct the frequeney-invariant beampattern. Compared to some other methods presented recently, the proposed algorithm is not only available to get the global optimal solution, but also simple for physical realization. Meanwhile, a robust adaptive broadband beamforming algorithm is also derived by reconstructing the covariance matrix. The essence of the proposed algorithm is to estimate the space-frequency spectrum using Capon spectral estimator firstly, then in- tegrate over a region separated from the desired signal direction to reconstruct the interference-plus-noise covariance matrix, and finally calculate the adaptive beamformer weights with the reconstructed matrix. The design of beamformer is reformulated as a convex optimization problem. Simulation results show that the performance of the proposed algorithm is almost always close to the optimal value across a wide range of signal to noise ratios.