Sliding 2D Discrete Fractional Fourier Transform

Yu Liu, Hongxia Miao, Feng Zhang*, Ran Tao

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

17 引用 (Scopus)

摘要

The two-dimensional discrete fractional Fourier transform (2D DFrFT) has been shown to be a powerful tool for 2D signal processing. However, the existing discrete algorithms aren't the optimal for real-time applications, where the input signals are stream data arriving in a sequential manner. In this letter, a new sliding algorithm is proposed to solve this problem, termed as the 2D sliding DFrFT (2D SDFrFT). The proposed 2D SDFrFT algorithm directly computes the 2D DFrFT in current window using the results of previous window, which greatly reduces the computations. During the derivation, we find that the (m+δn)th DFrFT bin in previous window is needed for computing the (m,n)th DFrFT bin in current window, where the increment δ isn't always an integer. Further, a method is proposed to convert the increment δ to a certain integer by determining appropriate sampling interval. The theoretical analysis demonstrates that when compute the new 2D DFrFT in a shifted window in sliding process, our proposed algorithm has the lowest computational cost among existing 2D DFrFT algorithms.

源语言英语
文章编号8854972
页(从-至)1733-1737
页数5
期刊IEEE Signal Processing Letters
26
12
DOI
出版状态已出版 - 12月 2019

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