基于稀疏约束和CLEAN处理的毫米波SAR三维超高分辨率成像

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基于稀疏约束和CLEAN处理的毫米波SAR三维超高分辨率成像

更新时间：2026-03-03

- 基于稀疏约束和CLEAN处理的毫米波SAR三维超高分辨率成像
- Millimeter SAR super high resolution 3D imaging based on the Sparse constraint and clean operation
- 物联网学报 2026年
- 作者机构：
- 作者简介：
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  中图分类号： TN975
- 收稿：2025-06-17，
  
  修回：2025-11-08，
  
  录用：2026-02-09，
- 稿件说明：
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基于稀疏约束和CLEAN处理的毫米波SAR三维超高分辨率成像[J/OL]. 物联网学报, 2026.

Millimeter SAR super high resolution 3D imaging based on the Sparse constraint and clean operation[J/OL]. Chinese Journal on Internet of Things, 2026.
基于稀疏约束和CLEAN处理的毫米波SAR三维超高分辨率成像[J/OL]. 物联网学报, 2026. DOI：

Millimeter SAR super high resolution 3D imaging based on the Sparse constraint and clean operation[J/OL]. Chinese Journal on Internet of Things, 2026. DOI：

摘要

基于二维扫描的毫米波合成孔径雷达(Synthetic Aperture Radar

SAR)可以进行三维成像处理，成为近年来雷达信号处理领域的重要研究方向之一。然而，该系统三维重建性能严格受发射信号带宽以及孔径长度限制，距离向分辨率常远小于方位向合成孔径后分辨性能，多目标场景成像处理时旁瓣干扰会显著降低成像质量。针对该问题，本文提出了联合稀疏约束和Clean处理的超高分辨率三维成像处理。其中，三维联合稀疏约束可以实现目标旁瓣能量抑制，改善重建分辨性能。Clean处理中应用数据域投影对消和幅度校正实现不同散射目标能量的分离。最后，通过实测数据验证该方法能有效改善三维成像重建性能，抑制多目标旁瓣干扰，显著提升成像质量。该研究为毫米波三维成像技术在复杂场景中的应用提供了更优的解决方案，具有重要的工程应用价值。

Abstract

Millimeter-wave Synthetic Aperture Radar (SAR) capable of three-dimensional (3D) imaging

achieved through two-dimensional scanning

has become a significant research direction in radar signal processing. However

3D reconstruction performance is often limited by the transmitted signal bandwidth and aperture length

resulting in a range resolution significantly lower than the azimuth resolution. In multi-target scenarios

this disparity leads to severe image degradation from sidelobe interference. To address these limitations

this paper proposes a super-resolution 3D imaging method that combines a joint sparse constraint with the CLEAN algorithm. Within this framework

the 3D joint sparse constraint suppresses sidelobe energy and enhances reconstruction resolution

while the CLEAN process effectively separates signals from distinct scatterers using data-domain projection cancellation and amplitude correction. Validation with measured data shows that the proposed method substantially improves 3D image reconstruction

mitigates multi-target sidelobe interference

and enhances overall image quality. This work provides an effective solution for applying millimeter-wave 3D imaging in complex scenarios and shows considerable promise for practical engineering applications

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references

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