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Mitigation of Ground Clutter in Airborne Bistatic Radar Systems

机译:减轻机载双基地雷达系统中的地面杂波

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Space-Time Adaptive Processing is a commonly used technique to mitigate ground clutter reflections from an airborne radar system. It estimates a covariance matrix based on spatial and temporal information, and the estimate is thereafter used to suppress the ground clutter. In a side-looking monostatic radar system, the estimate is rather straight forward based on radar observations. However, in this paper, we consider bistatic systems where the power of adaptivity is limited due to nonstationarity of the ground clutter reflections over the range dimension. To overcome this, scenario dependent transformations are commonly used when forming the sample covariance matrix. In this contribution we instead investigate a detector where the clutter covariance matrix is determined from the geometry of the bistatic scenario. Using a Monte-Carlo simulation, we investigate how sensitive the detector is to errors in the assumed geometry, and compare this with state-of-the-art adaptive methods. The results indicates that a good clutter rejection is obtained for errors of order 103 m for assumed transmitter position and 100 km/h for assumed transmitter velocity.
机译:时空自适应处理是减轻机载雷达系统地面杂波反射的常用技术。它根据空间和时间信息来估计协方差矩阵,然后将该估计值用于抑制地面杂波。在侧视单基地雷达系统中,基于雷达观测值的估算相当简单。但是,在本文中,我们考虑了双基地系统,由于地面杂波反射在整个范围范围内的非平稳性,自适应能力受到限制。为了克服这个问题,在形成样本协方差矩阵时通常使用与场景相关的变换。在本文中,我们改为研究一种检测器,在该检测器中,从双基地方案的几何结构确定杂波协方差矩阵。使用蒙特卡洛模拟,我们研究了检测器对假定几何形状中的误差的敏感程度,并将其与最新的自适应方法进行了比较。结果表明,对于阶数为10的误差,可以获得良好的杂波抑制 3 m为假定的发射机位置和10 0 km / h(假定发射机速度)。

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