Colored loading for robust adaptive beamforming with low sample support

Huixia He, S. Kraut
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Abstract

Classical robust adaptive beamforming makes use of diagonal loading to prevent high sidelobes and distorted main beams caused by the inaccurate estimation of the covariance ma- trix, signal mismatch and non-stationary interference. This paper develops a general loading technique, called colored loading (CL), by which the estimated covariance matrix is loaded by a scaled version of a Hermitian matrix, usually a Toeplitz matrix for linear equispaced sensors, as opposed to using the identity matrix as in diagonal loading. The colored loading retains the simplicity of implementation of diagonal loading. Numerical examples show that colored loading is superior to diagonal loading in terms of the optimal output signal-to-interference plus noise ratio (SINR), in the snapshot deficient scenario.
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低样本支持下的彩色加载鲁棒自适应波束形成
传统的鲁棒自适应波束形成是利用对角加载来防止因协方差矩阵估计不准确、信号失配和非平稳干扰而导致的高旁瓣和主波束畸变。本文发展了一种通用的加载技术,称为彩色加载(CL),通过该技术,估计的协方差矩阵由厄米矩阵的缩放版本加载,通常是线性等距传感器的Toeplitz矩阵,而不是使用对角加载中的单位矩阵。彩色加载保留了对角加载实现的简单性。数值算例表明,在缺乏快照的情况下,彩色加载优于对角加载,其输出信噪比(SINR)最佳。
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