Enhancing GMTI Performance in Non-Stationary Clutter Using 3D STAP
Enhancing GMTI Performance in Non-Stationary Clutter Using 3D STAP
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DOI：
10.1109/radar.2007.374295
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发表时间：
2007-04
期刊：
影响因子：
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通讯作者：
P. Corbell;J. J. Perez-J.;M. Rangaswamy
中科院分区：
文献类型：
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作者：
P. Corbell;J. J. Perez-J.;M. Rangaswamy
在侧视地面移动目标指示 (GMTI) 雷达中，二维 (2D) 时空（方位多普勒）域可以充分定义对所有距离门都准确的杂波频谱。然而，在阵列视轴不垂直于速度矢量的应用中（例如前视雷达），方位多普勒杂波频谱表现出对到达仰角的依赖性，从而产生范围变化（但依赖于高度）的杂波统计数据或非平稳杂波。经典时空自适应处理 (STAP) 算法在非平稳杂波中会遭受严重的性能损失，因为经典 STAP 假设杂波沿范围（训练）维度是平稳的。平面阵列本质上能够观察作为仰角函数的方位多普勒杂波频谱，这是线性阵列所缺乏的能力。将平面阵列的垂直尺寸合并到联合方位角-多普勒 (2D) STAP 域中之前已经产生了 3D STAP。本文展示了 3D STAP 通过考虑 3D 协方差矩阵中与海拔相关的杂波统计来解决非平稳杂波问题的能力。前视阵列用于提供非平稳杂波，并且自适应匹配滤波器 (AMF) 和联合域局部化 (JDL) 的 2D 和 3D 版本的性能用于近距离传感范例。结果显示，使用 3D STAP 算法代替应用于相同（子阵列）数据的 2D STAP 算法，杂波零点附近的输出 SINR 提高了 >55 dB。
In side-looking ground moving target indication (GMTI) radar, the 2-dimensional (2D) space time (azimuth-Doppler) domain can adequately define a clutter spectrum which is accurate for all range gates. However, in applications where the array boresight is not perpendicular to the velocity vector (e.g. forward-looking radar), the azimuth-Doppler clutter spectrum exhibits a dependence on elevation angle-of-arrival, creating range-varying (but elevation-dependent) clutter statistics, or non-stationary clutter. Classical space time adaptive processing (STAP) algorithms suffer substantial performance losses in non-stationary clutter since classical STAP assumes clutter stationary along the range (training) dimension. Planar arrays are inherently able to observe the azimuth-Doppler clutter spectrum as a function of the elevation angle, a capability which linear arrays lack. The incorporation of the planar array's vertical dimension into the joint azimuth-Doppler (2D) STAP domain has previously resulted in 3D STAP. This paper demonstrates the ability of 3D STAP to solve the non-stationary clutter problem by accounting for the elevation-dependent clutter statistics in a 3D covariance matrix. A forward-looking array is used to provide non-stationary clutter, and the performance of 2D and 3D versions of the adaptive matched filter (AMF) and joint domain localized (JDL) are used in a close-in sensing paradigm. The results show a >55 dB improvement in output SINR near the clutter null using 3D STAP algorithms in lieu of 2D STAP algorithms applied to the same (subarrayed) data.