利用协方差矩阵拟合的阵列孔径扩展方法

Array aperture extension method using covariance matrix fitting

提出了一种协方差矩阵拟合的阵列孔径扩展方法来提高小孔径均匀直线阵的分辨力。该方法分析了具有不同阵元个数的阵列采集信号协方差矩阵之间的关系,并根据该关系构建阵列扩展的优化算法,利用小孔径实际阵列协方差矩阵拟合得到大孔径虚拟阵列的协方差矩阵。仿真分析与湖试数据处理结果表明,将拟合协方差矩阵用于现有方位估计方法中能够降低波束宽度,提高分辨力,并且随着虚拟阵元个数增加,目标分辨概率同步提高。当阵列孔径较小或环境信噪比较低时,本文方法可用于提高方位估计性能。

An array aperture extension method based on covariance matrix fitting is proposed to improve the resolution of uniform linear array with small aperture.The relationship between the covariance matrices of signals received by arrays with different number of array elements is analyzed.According to this relationship,an array extension optimization algorithm is constructed to fit the covariance matrix of a large aperture virtual array by using the covariance matrix of a small aperture actual array.Simulation and lake experiment results show that using the fitted covariance matrix in existing DOA estimation methods can reduce the beamwidth and improve the resolution.As the number of virtual array elements increases,the resolution synchronously improves.This method can be used to improve the DOA estimation performance when the array aperture is insufficient or the signal-to-noise ratio is reduced.