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Performance of the space-time AR filter in non-homogeneous clutter airborne radar STAP

机译:时空AR滤波器在非均匀杂波中的性能机载雷达STAP

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The space-time autoregressive (STAR) technique has been proposed for space-time adaptive processing (STAP). This algorithm utilizes the structure inherent in airborne STAP applications (i.e., uniformly spaced pulses) to improve convergence and reduce computation. This paper addresses the performance of the STAR algorithm in the presence of non-homogeneous clutter, particularly in a littoral region. It is shown that lite STAR filter produced a narrower null (and thus a lower minimum detectable velocity) than either the optimized pre-Doppler or post-Doppler algorithms. This is due to file STAR algorithm estimating a joint space-time filter for clutter suppression as well as having a small sample support region. It is also shown that the pre-Doppler algorithm does exhibit some robustness when the radar system is limited by its channel match.
机译:时空自回归(STAR)技术已提出用于时空自适应处理(STAP)。该算法利用机载STAP应用中固有的结构(即均匀间隔的脉冲)来提高收敛性并减少计算量。本文介绍了在非均匀杂波(尤其是在沿海地区)存在的情况下STAR算法的性能。结果表明,与优化的前多普勒算法或后多普勒算法相比,精简STAR滤波器产生的窄零点(因此,最低可检测速度更低)。这是由于文件STAR算法估算了一个用于抑制杂波的联合时空滤波器,并且具有较小的样本支持区域。还表明,当雷达系统受到其信道匹配的限制时,多普勒算法确实表现出一定的鲁棒性。

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