基于波场互相关的探地雷达快速自聚焦成像

Zhongwei Yang, Conglong Quo, Haoran Sun, Tian Lan, Xiaopeng Yang

科研成果: 期刊稿件文章同行评审

2 引用 (Scopus)

摘要

The traditional migration imaging algorithms for ground penetrating radar have the disadvantages of high computational complexity and low accuracy, and require the accurate value of medium parameters. In this paper, a fast-autofocusing approach for ground penetrating radar imaging, based on correlation of wavefield, was proposed to solve these problems. The spectrum Green's function and fast Fourier transform were employed to formulate the algorithm, which greatly saves the calculation and storage resources and makes it possible to perform real-time and high-resolution imaging for underground targets. Furthermore, by introducing a time phase factor into the imaging formula, a series of images at different focusing time were obtained and then the optimal focused image was stored as the output based on the minimum entropy criterion, which solved the problem of smearing and blurring of the image caused by incorrect estimation of the medium parameters. Simulation results verified that the proposed algorithm can provide high-quality autofocusing image regardless of the estimated value of the medium parameters.

投稿的翻译标题A Fast-Autofocusing Approach for Ground Penetrating Radar Imaging Based on Correlation of Wavefield
源语言繁体中文
页(从-至)1663-1668
页数6
期刊Journal of Signal Processing
37
9
DOI
出版状态已出版 - 9月 2021

关键词

  • autofocusing
  • ground penetrating radar
  • migration imaging
  • spectrum Green's function

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