Implementation of sparse recovery method with high‐resolution time‐frequency energy distributions for helicopter. (13th March 2020)

• Record Type: Journal Article
• Authors: Wang, Yanqing; Yang, Shuhui; Yin, Hongcheng; Huo, Chaoying
• Other Names: De Gersem Herbert guestEditor.; Kurz Stefan guestEditor.; Schöps Sebastian guestEditor.; Geuzaine Christophe guestEditor.
• Is Part Of: International journal of numerical modelling. Volume 33:Number 5(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-03-13
• Subjects: helicopter -- sparse recovery -- sparse WVD -- time‐frequency analysis; Electric networks -- Mathematical models -- Periodicals; Electronics -- Mathematical models -- Periodicals; 621.3011
• DOI: 10.1002/jnm.2741
• Languages: English
• ISSNs: 0894-3370

Abstract

Abstract: In this paper, an algorithm named the sparse Wigner‐Ville distribution (WVD) is applied for the time‐frequency analysis of signals. In this algorithm, the sampling for ambiguity function (AF) is regarded as a sparsity measurement of the WVD, and the Fourier transform matrix is treated as a sparsity redundant dictionary. The effectiveness of the algorithm is verified by using the liner frequency modulation and sinusoidal frequency modulation signals. Then the algorithm is employed to deal with the time‐frequency analysis of helicopters. The experiment results show that the time‐frequency images of helicopters obtained by utilizing this algorithm exhibit higher resolution without cross‐interference terms compared with that by WVD.