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Array Radar Three-Dimensional Forward-Looking Imaging Algorithm Based on Two-Dimensional Super-Resolution

delete2024-11-18
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Jinke Dai
W
Weijie Sun
X
Xinrui Jiang
D
Di Wu *
DOI:10.3390/s24227356delete
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摘要

摘要

En 中文
Radar imaging is a technology that uses radar systems to generate target images. It transmits radio waves, receives the signal reflected back by the target, and realizes imaging by analyzing the target's position, shape, and motion information. The three-dimensional (3D) forward-looking imaging of missile-borne radar is a branch of radar imaging. However, owing to the limitation of antenna aperture, the imaging resolution of real aperture radar is restricted. By implementing the super-resolution techniques in array signal processing into missile-borne radar 3D forward-looking imaging, the resolution can be further improved. In this paper, a 3D forward-looking imaging algorithm based on the two-dimensional (2D) super-resolution algorithm is proposed for missile-borne planar array radars. In the proposed algorithm, a forward-looking planar array with scanning beams is considered, and each range-pulse cell in the received data is processed one by one using a 2D super-resolution method with the error function constructed according to the weighted least squares (WLS) criterion to generate a group of 2D spectra in the azimuth-pitch domain. Considering the lack of training samples, the super-resolution spectrum of each range-pulse cell is estimated via adaptive iteration processing only with one sample, i.e., the cell under process. After that, all the 2D super-resolution spectra in azimuth-pitch are accumulated according to the changes in instantaneous beam centers of the beam scanning. As is verified by simulation results, the proposed algorithm outperforms the real aperture imaging method in terms of azimuth-pitch resolution and can obtain 3D forward-looking images that are of a higher quality.
Keyword:
array radar
forward-looking
super-resolution technique
three-dimensional imaging
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Sensors 封面图
Sensors
IF:
3.5
论文数:
7.2W
被引数:
20.9W

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