Robust Capon Filter Bank based three dimensional structure superresolution algorithm

Jian Wang, Qian Song, Zhimin Zhou
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Abstract

A time domain 3D Rank Deficit Robust Capon Filter Bank (RD-RCFB) is presented. An additional preprocess and postprocess are adopted to transform the time domain model into the frequency domain model. And matrix vectorization is used to reduce the dimension. Optimal implement of the algorithm is discussed by comparing the cascading 1D RD-RCFB, cascading 2D RD-RCFB and 3D RD-RCFB. The algorithm outperforms the 3D Adaptive Sidelobe Reduction (ASR) and the 3D Amplitude and Phase Estimation of a Sinusoid(APES). Simulated planar aperture 3D image processing verified the algorithm.
基于鲁棒Capon滤波器组的三维结构超分辨算法
提出了一种时域三维秩亏鲁棒Capon滤波器组(RD-RCFB)。采用额外的预处理和后处理将时域模型转换为频域模型。采用矩阵矢量化的方法进行降维。通过对比级联一维RD-RCFB、级联二维RD-RCFB和级联三维RD-RCFB,讨论了算法的优化实现。该算法优于三维自适应旁瓣降低(ASR)和正弦信号的三维幅度和相位估计(APES)。仿真平面孔径三维图像处理验证了算法的有效性。
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