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Issue title: Special Section: Fuzzy Logic for Analysis of Clinical Diagnosis and Decision-Making in Health Care
Article type: Research Article
Authors: Song, Depeng; * | Li, Binbing | Qu, Yi | Chen, Yijun
Affiliations: College of Information Engineering, Engineering University of PAP xi’an shanxi, China
Correspondence: [*] Corresponding author. Depeng Song, College of Information Engineering, Engineering University of PAP xi’an shanxi, China. E-mail: wjsdp0801@163.com.
Abstract: The frequency modulated continuous wave circular synthetic aperture radar (FMCW CSAR) is a high resolution imaging radar, which plays an important role in target recognition. However, the traditional wave number domain imaging algorithm has a low resolution for the target far from the scene center, which limits its wide applications in CSAR imaging. In this paper, when the targets are sparse or compressible, a circular convolution algorithm based on compressed sensing is proposed to improve the resolution. In the algorithm, the circular convolution and the Fourier transform is used to reduce computation cost. What’s more, the compressed sensing is applied to improve the imaging resolution for the target far from the scene center, which can effectively avoid the complex calculation of the system kernel function in the traditional wave number domain algorithm. Some simulation results illustrate the effectiveness of the proposed method.
Keywords: FMCW CSAR, compressed sensing, circular convolution, imaging
DOI: 10.3233/JIFS-179393
Journal: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 187-196, 2020
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