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Range recursive and Taylor series based space-time adaptive processing for range dependent clutter rejection

机译:基于范围递归和基于泰勒级数的时空自适应处理,用于范围相关的杂波抑制

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This paper presents a new space time adaptive processing (STAP) for the rejection of range dependent ground clutter in order to detect slow moving targets with an airborne radar. STAP usually requires the estimation of the clutter plus noise covariance matrix from secondary data neighboring the cell under test. However, in most radar antenna array architectures and/or configurations which are different from the conventional uniform linear antenna array and side-looking configuration the clutter is range dependent. We recently proposed the use of a Taylor series expansion of the clutter plus noise subspace in conjunction with the eigencanceler-based (EC) STAP in order to mitigate the range non-stationarity of the clutter. In this paper, the computationally costly EC is replaced by a range-recursive algorithm which is capable of tracking non stationarities with a reduced complexity compared to the EC. The performance of the proposed algorithm is satisfactorily tested and compared to other algorithms in the case of a bistatic configuration.
机译:本文提出了一种新的时空自适应处理(STAP),用于抑制距离相关的地面杂波,以便利用机载雷达检测慢速移动的目标。 STAP通常需要根据被测小区附近的辅助数据估算杂波加噪声协方差矩阵。然而,在与常规的均匀线性天线阵列和侧视配置不同的大多数雷达天线阵列架构和/或配置中,杂波取决于范围。我们最近提出了将杂波加噪声子空间的泰勒级数展开与基于特征本征的(EC)STAP结合使用的方法,以减轻杂波的范围非平稳性。在本文中,计算上昂贵的EC被范围递归算法所取代,该算法能够以比EC更低的复杂度跟踪非平稳性。在双基地配置的情况下,该算法的性能得到了令人满意的测试,并与其他算法进行了比较。

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