Polarimetric super-resolution algorithm for radar range imaging via spatial smoothing processing

Zhang Feng Li; Guo Qiang Zhao; Shi Yong Li; Fang Liu; Hou Jun Sun; Ran Tao

doi:10.15918/j.jbit1004-0579.201625.0313

Polarimetric super-resolution algorithm for radar range imaging via spatial smoothing processing

Zhang Feng Li^*, Guo Qiang Zhao, Shi Yong Li, Fang Liu, Hou Jun Sun, Ran Tao

^*Corresponding author for this work

Beijing Institute of Technology

Research output: Contribution to journal › Article › peer-review

Abstract

A full-polarimetric super-resolution algorithm with spatial smoothing processing is presented for one-dimensional (1-D) radar imaging. The coherence between scattering centers is minimized by using spatial smoothing processing (SSP). Then the range and polarimetric scattering matrix of the scattering centers are estimated. The impact of different lengths of the smoothing window on the imaging quality is mainly analyzed with different signal-to-noise ratios (SNR). Simulation and experimental results show that an improved radar super-resolution range profile and more precise estimation can be obtained by adjusting the length of the smoothing window under different SNR conditions.

Original language	English
Pages (from-to)	397-402
Number of pages	6
Journal	Journal of Beijing Institute of Technology (English Edition)
Volume	25
Issue number	3
DOIs	https://doi.org/10.15918/j.jbit1004-0579.201625.0313
Publication status	Published - 1 Sept 2016

Keywords

MUSIC imaging
Polarimetric radar
Signal-to-noise ratio(SNR)
Spatial smoothing processing(SSP)
Super-resolution imaging

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10.15918/j.jbit1004-0579.201625.0313

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title = "Polarimetric super-resolution algorithm for radar range imaging via spatial smoothing processing",

abstract = "A full-polarimetric super-resolution algorithm with spatial smoothing processing is presented for one-dimensional (1-D) radar imaging. The coherence between scattering centers is minimized by using spatial smoothing processing (SSP). Then the range and polarimetric scattering matrix of the scattering centers are estimated. The impact of different lengths of the smoothing window on the imaging quality is mainly analyzed with different signal-to-noise ratios (SNR). Simulation and experimental results show that an improved radar super-resolution range profile and more precise estimation can be obtained by adjusting the length of the smoothing window under different SNR conditions.",

keywords = "MUSIC imaging, Polarimetric radar, Signal-to-noise ratio(SNR), Spatial smoothing processing(SSP), Super-resolution imaging",

author = "Li, {Zhang Feng} and Zhao, {Guo Qiang} and Li, {Shi Yong} and Fang Liu and Sun, {Hou Jun} and Ran Tao",

year = "2016",

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T1 - Polarimetric super-resolution algorithm for radar range imaging via spatial smoothing processing

AU - Li, Zhang Feng

AU - Zhao, Guo Qiang

AU - Li, Shi Yong

AU - Liu, Fang

AU - Sun, Hou Jun

AU - Tao, Ran

PY - 2016/9/1

Y1 - 2016/9/1

N2 - A full-polarimetric super-resolution algorithm with spatial smoothing processing is presented for one-dimensional (1-D) radar imaging. The coherence between scattering centers is minimized by using spatial smoothing processing (SSP). Then the range and polarimetric scattering matrix of the scattering centers are estimated. The impact of different lengths of the smoothing window on the imaging quality is mainly analyzed with different signal-to-noise ratios (SNR). Simulation and experimental results show that an improved radar super-resolution range profile and more precise estimation can be obtained by adjusting the length of the smoothing window under different SNR conditions.

AB - A full-polarimetric super-resolution algorithm with spatial smoothing processing is presented for one-dimensional (1-D) radar imaging. The coherence between scattering centers is minimized by using spatial smoothing processing (SSP). Then the range and polarimetric scattering matrix of the scattering centers are estimated. The impact of different lengths of the smoothing window on the imaging quality is mainly analyzed with different signal-to-noise ratios (SNR). Simulation and experimental results show that an improved radar super-resolution range profile and more precise estimation can be obtained by adjusting the length of the smoothing window under different SNR conditions.

KW - MUSIC imaging

KW - Polarimetric radar

KW - Signal-to-noise ratio(SNR)

KW - Spatial smoothing processing(SSP)

KW - Super-resolution imaging

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DO - 10.15918/j.jbit1004-0579.201625.0313

M3 - Article

AN - SCOPUS:85009967876

SN - 1004-0579

VL - 25

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JO - Journal of Beijing Institute of Technology (English Edition)

JF - Journal of Beijing Institute of Technology (English Edition)

IS - 3

ER -

Polarimetric super-resolution algorithm for radar range imaging via spatial smoothing processing

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