Yang T C
Naval Research Laboratory, Washington, DC 20375, USA.
J Acoust Soc Am. 2003 Jan;113(1):245-60. doi: 10.1121/1.1528929.
Large aperture horizontal line arrays have small resolution cells and can be used to separate a target signal from an interference signal by array beamforming. High-resolution adaptive array processing can be used to place a null at the interference signal so that the array gain can be much higher than that of conventional beamforming. But these nice features are significantly degraded by the source motion, which reduces the time period under which the environment can be considered stationary from the array processing point of view. For adaptive array processing, a large number of data samples are generally required to minimize the variance of the cross-spectral density, or the covariance matrix, between the array elements. For a moving source and interference, the penalty of integrating over a large number of samples is the spread of signal and interference energy to more than one or two eigenvalues. The signal and interference are no longer clearly identified by the eigenvectors and, consequently, the ability to suppress the interference suffers. We show in this paper that the effect of source motion can be compensated for the (signal) beam covariance matrix, thus allowing integration over a large number of data samples without loss in the signal beam power. We employ an equivalent of a rotating coordinate frame to track the signal bearing change and use the waveguide invariant theory to compensate the signal range change by frequency shifting.
大孔径水平线阵具有较小的分辨单元，可通过阵列波束形成将目标信号与干扰信号分离。高分辨率自适应阵列处理可用于在干扰信号处形成零陷，从而使阵列增益远高于传统波束形成。但这些优良特性会因源的运动而显著退化，从阵列处理的角度来看，这会缩短可将环境视为静止的时间段。对于自适应阵列处理，通常需要大量数据样本以最小化阵列元素间互谱密度或协方差矩阵的方差。对于运动的源和干扰，对大量样本进行积分的代价是信号和干扰能量扩展到不止一两个特征值。特征向量不再能清晰地识别信号和干扰，因此抑制干扰的能力会受到影响。我们在本文中表明，源运动的影响可通过（信号）波束协方差矩阵得到补偿，从而允许对大量数据样本进行积分而不会损失信号波束功率。我们采用等效的旋转坐标系来跟踪信号方位变化，并利用波导不变性理论通过频移来补偿信号距离变化。
