Two-dimensional sparse fractional Fourier transform and its applications

被引:0
|
作者
Wei, Deyun [1 ]
Yang, Jun [1 ]
机构
[1] Xidian Univ, Sch Math & Stat, Xian 710071, Peoples R China
来源
SIGNAL PROCESSING | 2022年 / 201卷
关键词
Two-dimensional fractional Fourier  transform; Discrete fractional Fourier transform; Sparse Fourier transform; Image fusion; LINEAR CANONICAL TRANSFORM; WIGNER DISTRIBUTION; RADAR; TARGET; COMPUTATION; MATRIX;
D O I
10.1016/j.sigpro.2022.108682
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The discrete fractional Fourier transform is an excellent tool in non-stationary signal processing. And an efficient and accurate computation is important for the two-dimensional discrete fractional Fourier trans-form (2D DFRFT). Inspired by the sparse Fourier transform algorithm, we propose a two-dimensional sparse fractional Fourier transform (2D SFRFT) algorithm to estimate the fractional Fourier spectrum effi-ciently. Compared with existing methods, we have achieved the lowest runtime and sample complexity. Moreover, by analyzing the errors due to noises, the 2D SFRFT algorithm is improved to be robust. The applications in image fusion, parameter estimation of multicomponent 2D chirp signal and complex ma-neuvering targets in SAR radar demonstrate the effectiveness of the proposed algorithms.(c) 2022 Published by Elsevier B.V.
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页数:17
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