一种空间色噪声环境下的鲁棒自适应波束

该文提出了一种基于对角加载的鲁棒自适应波束形成算法，以提高空间色噪声环境中自适应波束对方向矢量误差的鲁棒性。该算法首先利用噪声协方差矩阵对阵列相关矩阵进行预白化，同时定义了一个与噪声矩阵相对应的椭圆方向矢量模糊集，然后，通过在该模糊集内进行最坏情况性能优化来确定对角加载因子。和现有的通过迭代求解加载因子的方法不同，该文给出了最优加载因子的近似解析表达式，降低了运算量，揭示了哪些因素可以影响最优加载因子，以及如何影响。仿真结果表明，在空间色噪声环境中，该算法具有很好的鲁棒性，并且，给出的加载因子表达式是其真实最优解的一个准确近似。

Robust Adaptive Beamforming In Spatially Colored Noise Fields

A novel robust adaptive beamforming based on diagonal loading is proposed in this paper, aiming at robustness against steering vector mismatches in spatially colored noise fields. The received data is prewhitened first according to the noise covariance, with a corresponding ellipsoidal steering vector uncertainty set defined at the same time. Then the loading level is determined based on worst-case performance optimization. Other than searching for the optimal loading by iteration, a simple closed-form solution is suggested after some approximations. Besides its low computational cost, the closed-form solution reveals how different factors affect the optimal loading. Numerical examples confirm the excellent performance of the proposed approach as well as the accurate approximation of the closed-form solution to the actual optimal loading.