基于子空间特征分析的算法进展:从一维到三维超分辨率技术

O.A. Dobre, E. Radoi
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引用次数: 6

摘要

首先概述了两种用于ID情况的超分辨率方法MUSIC和ESPRIT。然后,将这些算法推广到三维情况。给出了新的信号模型、数据重采样、空间平滑方法和估计表达式。虽然在雷达和无线通信领域可以考虑许多应用,但其中只有一个是详细的:高分辨率雷达目标成像。本文最后部分的结论得到了对合成信号的仿真结果的支持,并将所提出的方法与利用傅里叶变换提取散射中心技术进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advances in subspace eigenanalysis based algorithms: from 1D toward 3D superresolution techniques
An overview of two superresolution methods, MUSIC and ESPRIT, for the ID case is firstly given. Afterwards, an extension of these algorithms to the three-dimensional case is proposed. New formulations for the signal model, data resampling, spatial smoothing method and estimate expression are provided. Although many applications can be considered in the areas of radar and wireless communications, only one of them is detailed: high-resolution radar target imaging. The concluding remarks drawn in the final part of the paper are supported by simulation results performed on synthetic signals and by comparing the proposed methods to the scattering center extraction technique using the Fourier transform.
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