An efficient subband decomposition based on the Hilbert transform for high-resolution spectral estimation

S. Rouquette, Y. Berthoumieu, M. Najim
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引用次数: 5

Abstract

This paper deals with high-resolution frequency estimation for narrow-band plane waves. We propose an approach based on subband decomposition in the spectral domain to improve the performance of high-resolution analysis. This decomposition is based on the Hilbert transform for one and two-dimensional signals. This improvement is tested on ESPRIT and MEMP techniques. We first present the subband decomposition based on the Hilbert transform (SDBHT) for one-dimensional (1D) signals. Secondly the SDBHT method is extended to the two-dimensional (2D) case. Finally the advantages of such a method are illustrated with simulation examples.
基于希尔伯特变换的高效子带分解用于高分辨率光谱估计
本文研究窄带平面波的高分辨率频率估计问题。为了提高高分辨率分析的性能,我们提出了一种基于谱域子带分解的方法。这种分解是基于一维和二维信号的希尔伯特变换。这种改进在ESPRIT和MEMP技术上进行了测试。我们首先提出了基于希尔伯特变换(SDBHT)的一维(1D)信号子带分解。其次,将SDBHT方法推广到二维(2D)情况。最后通过仿真实例说明了该方法的优点。
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