Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 11
3496-3502

Millimeter wave sparse imaging algorithm based on depth expansion model

Che Lia,b
Wu Yongmanb,c
Jiang Liubinga,b
Mou Yujieb,c
a. School of Information & Communication, b. Key Laboratory of Wireless Broadband Communication & Signal Processing in Guangxi, c. School of Computer & Information Security, Guilin University of Electronic Technology, Guilin Guangxi 541004, China
DOI: 10.19734/j.issn.1001-3695.2023.03.0121

Abstract

Aiming at the high computational cost of traditional compressed sensing algorithms, this paper proposed a sparse imaging algorithm based on depth expansion model from the perspective of sparse signal recovery. Firstly, it constructed a complex sparse reconstruction network VAMP-Net. In VAMP-Net, it divided complex regressive echo signal into real part and imaginary part as input. Secondly, it substituted the input into the iterative block based on VAMP algorithm. Finally, it carried out the optimal nonlinear sparse transformation by convolutional neural module to obtain the recovered real part and imaginary part signals, and then merged them to obtain the restored target image. As for the proposed algorithm, this paper used artificial data sets to conduct simulation experiments under different target density, iteration times and noise environment, and compared with the traditional iterative shrinkage threshold algorithm and deep learning reconstruction algorithm. Then it used the measured data with different sparsity for field measurement verification. Experimental results show that the image reconstructed by this algorithm has better performance in NMSE, TBR, reconstruction speed and memory usage.

Foundation Support

广西创新驱动发展专项(桂科AA21077008)
广西无线宽带通信与信号处理重点实验室主任基金资助项目(GXKL06220102,GXKL06220108)
广西高等教育本科教学改革工程项目(2022JGB196)
桂林电子科技大学研究生教育创新计划资助项目(2023YCXS047)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.03.0121
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 11
Section: Technology of Graphic & Image
Pages: 3496-3502
Serial Number: 1001-3695(2023)11-046-3496-07

Publish History

[2023-06-01] Accepted Paper
[2023-11-05] Printed Article

Cite This Article

车俐, 吴永满, 蒋留兵, 等. 基于深度展开模型的毫米波稀疏成像算法 [J]. 计算机应用研究, 2023, 40 (11): 3496-3502. (Che Li, Wu Yongman, Jiang Liubing, et al. Millimeter wave sparse imaging algorithm based on depth expansion model [J]. Application Research of Computers, 2023, 40 (11): 3496-3502. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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