3-dimensional STAP performance analysis using the cross-spectral metric

P. Corbell, T. Hale
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引用次数: 14

Abstract

Research done in recent years has clearly demonstrated large improvements in clutter suppression and target detection by including elevation adaptivity, otherwise described as 3-dimensional (3D) STAP. The paper further quantifies the performance gains garnered by 3D STAP by fixing the degrees of freedom (DOF) and varying the array dimensions to include the equivalently sized linear array. The focus is placed on performance bounds established by matched filter and 3D cross-spectral metric (CSM) SINR curves generated with known covariances. The mathematical extension of the CSM from 2D to 3D is shown to be straightforward, thus allowing the CSM to serve as a partially adaptive performance bound for eigenvalue-selection based 3D STAP algorithms.
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使用交叉光谱度量的三维STAP性能分析
近年来的研究已经清楚地表明,在杂波抑制和目标检测方面,加入高度自适应(也称为三维STAP)有很大的改进。本文通过固定自由度(DOF)和改变阵列尺寸以包括同等大小的线性阵列,进一步量化了3D STAP所获得的性能增益。重点是通过匹配滤波器和已知协方差生成的3D交叉光谱度量(CSM) SINR曲线建立的性能界限。CSM从2D到3D的数学扩展被证明是直接的,从而允许CSM作为基于特征值选择的3D STAP算法的部分自适应性能边界。
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