基于最小均方误差估计的方位模糊抑制

Youming Wu, Ze Yu, Peng Xiao, Chunsheng Li
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引用次数: 6

摘要

提出了一种抑制单视复杂合成孔径雷达(SLC)图像中强方位模糊的创新算法。其基本思想是构造一个模糊度低的子空间,并将原始图像投影到上述子空间中,通过最小均方误差估计(MMSE)抑制方位角模糊。与大多数传统方法相比,该方法适用于任何分布式场景和任何采集模式。此外,所提出的方法似乎使分辨率保持在合理的水平,而不是过分依赖系统参数。利用TerraSAR-X卫星的原始数据验证了新方法抑制方位角模糊的效果。
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Azimuth ambiguity suppression based on minimum mean square error estimation
An innovative algorithm to suppress the strong azimuth ambiguity in single-look complex (SLC) synthetic aperture radar (SAR) images is presented. The basic idea is to construct a subspace with low ambiguous power and project the original image to the aforementioned subspace to suppress the azimuth ambiguity by the minimum mean square error estimation (MMSE). Compared with most traditional approaches, the proposed one is suitable for any distributed scene and any acquisition mode. Moreover, the proposed approach seems to keep the resolution in a reasonable level and not rely on the system parameters extremely. Raw data from the TerraSAR-X have been used to validate the effect of the azimuth ambiguity suppression by using the new approach.
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