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The 1D NMR spectrum of large and complex molecules like natural products has complicated splitting patterns and overlapping signals, which can be easily interpreted using 2-dimensional (2D) NMR. Unlike 1D NMR, 2D NMR has two frequency axes that provide the coupling information between the nucleus A and nucleus B in a molecule. The process from which 2D spectra are obtained has four steps.
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Related Experiment Video

Updated: Mar 14, 2026

Clinical Imaging of Microwave Mammography
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FGG-NUFFT-Based Method for Near-Field 3-D Imaging Using Millimeter Waves.

Yingzhi Kan1, Yongfeng Zhu2, Liang Tang3

  • 1College of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China. kanyingzhi@nudt.edu.cn.

Sensors (Basel, Switzerland)
|September 23, 2016
PubMed
Summary

This study introduces a new algorithm for near-field millimeter wave 3-D imaging. The fast Gaussian gridding based nonuniform FFT (FGG-NUFFT) method improves accuracy and reduces artifacts, especially in down-sampled scenarios.

Keywords:
3-D imagingFGG-NUFFTmillimeter wavenear-field

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Area of Science:

  • Electromagnetics and Signal Processing
  • Millimeter Wave Imaging Technology

Background:

  • Concealed target detection remains a challenge in near-field imaging.
  • Traditional 3-D imaging methods struggle with data sampling and artifact reduction.

Purpose of the Study:

  • To develop an accurate and efficient algorithm for near-field millimeter wave 3-D imaging.
  • To address limitations of conventional methods in handling scattered data and spherical wave effects.

Main Methods:

  • Utilizes a two-dimensional (2-D) plane antenna array for data acquisition.
  • Applies 2-D fast Fourier transform (FFT) and phase shift for spherical wave compensation.
  • Employs fast Gaussian gridding based nonuniform FFT (FGG-NUFFT) combined with 2-D inverse FFT (IFFT) for 3-D image reconstruction.

Main Results:

  • The FGG-NUFFT method achieves comparable efficiency and accuracy to conventional methods in fully sampled cases.
  • Demonstrates superior performance in down-sampled cases, yielding images with less clutter and fewer artifacts.
  • Simulation and experimental results validate the enhanced imaging performance.

Conclusions:

  • The proposed FGG-NUFFT based algorithm offers improved 3-D imaging performance for near-field millimeter wave applications.
  • This method is particularly advantageous for practical scenarios with down-sampled measurements.
  • Presents a more robust solution for concealed target detection using advanced imaging techniques.