To satisfy with the increasingly exacting demand for real-time and high resolution requirements of TWRI, a Compressive Sensing (CS) based TWRI algorithm is proposed after the exploitation of Stepped-Frequency-Continuous-Wave (SFCW) system and signal’s sparsity. Contrasted with the traditional imaging methods, this algorithm achieved precise targets localization and low sidelobe results with less computational time. The validity of the proposed CS imaging method is verified by simulation.
| Published in | Journal of Electrical and Electronic Engineering (Volume 3, Issue 5) |
| DOI | 10.11648/j.jeee.20150305.21 |
| Page(s) | 165-169 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2015. Published by Science Publishing Group |
TWRI, SFCW, Sparsity, Compressive Sensing
| [1] | Pawan Setlur, Moeness Amin, Fauzia Ahmad, et al. Multipath Model and Exploitation in Through-the-Wall and Urban Radar Sensing [J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, Vol.49 (10): 4021-4034. |
| [2] | W Zhang, M G Amin, F. Ahmad, A Hoorfar, and G E Smith, Ultrawideband impulse radar through-the-wall imaging with compressive sensing [J]. International Journal of Antennas and Propagation, 2012, vol. 2012, p.11. |
| [3] | 赵彧，黄春琳,栗毅,雷文太.超宽带穿墙探测雷达的反向投影成像算法[J].雷达科学与技术,2007, Vol.5（1）：49-54。 |
| [4] | D Donoho. Compressed sensing [J]. IEEE Transactions on Information Theory, 2006, Vol. 52(2): 5406-5425. |
| [5] | Suksmono A B, Bharata E, Lestari A, et al. Compressive stepped-frequency continuous-wave ground penetrating radar [J]. IEEE Geoscience Remote Sensing Letters, 2010, Vol.7(4): 665-669. |
| [6] | 屈乐乐,方广有,杨天虹.压缩感知理论在频率步进探地雷达偏移成像中的应用[J].电子与信息学报,2011,33(1): 21-26。 |
| [7] | Michael Leigsnering, Moeness G Amin and Fauzia Ahmad, Multipath exploitation and suppression for SAR imaging of building interiors [J]. IEEE Signal Processing Magazine, 2014, Vol.31(4): 110-119. |
| [8] | 吴仁彪,刘家学,张蓓.探地雷达地杂波抑制方法研究进展[J].信号处理, 2005, Vol.21(4A): 510-513。 |
| [9] | Candes E J, Wakin M B, An introduction to compressed sampling [J]. IEEE Signal Processing Magazine, 2008, Vol.25(2): 21-30. |
| [10] | D Needell and R Vershynin, Uniform uncertainty principle and signal recovery via regularized orthogonal matching pursuit [J]. Foundations of Computational Mathematics, 2009, Vol.9(3): 317-334. |
| [11] | C H Seng, A Bouzerdoum, M G Amin and S L Phung, Two-stage fuzzy fusion with applications to through-the-wall radar imaging [J]. IEEE Geoscience and Remote Sensing Letters, 2012, 10, 687-691. |
APA Style
Sun Yanpeng, Cui Zhao, Qu Lele. (2015). A CS and SFCW Based Reconstruction Algorithm for Through-the-Wall Radar Imaging. Journal of Electrical and Electronic Engineering, 3(5), 165-169. https://doi.org/10.11648/j.jeee.20150305.21
ACS Style
Sun Yanpeng; Cui Zhao; Qu Lele. A CS and SFCW Based Reconstruction Algorithm for Through-the-Wall Radar Imaging. J. Electr. Electron. Eng. 2015, 3(5), 165-169. doi: 10.11648/j.jeee.20150305.21
AMA Style
Sun Yanpeng, Cui Zhao, Qu Lele. A CS and SFCW Based Reconstruction Algorithm for Through-the-Wall Radar Imaging. J Electr Electron Eng. 2015;3(5):165-169. doi: 10.11648/j.jeee.20150305.21
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Download@article{10.11648/j.jeee.20150305.21,
author = {Sun Yanpeng and Cui Zhao and Qu Lele},
title = {A CS and SFCW Based Reconstruction Algorithm for Through-the-Wall Radar Imaging},
journal = {Journal of Electrical and Electronic Engineering},
volume = {3},
number = {5},
pages = {165-169},
doi = {10.11648/j.jeee.20150305.21},
url = {https://doi.org/10.11648/j.jeee.20150305.21},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jeee.20150305.21},
abstract = {To satisfy with the increasingly exacting demand for real-time and high resolution requirements of TWRI, a Compressive Sensing (CS) based TWRI algorithm is proposed after the exploitation of Stepped-Frequency-Continuous-Wave (SFCW) system and signal’s sparsity. Contrasted with the traditional imaging methods, this algorithm achieved precise targets localization and low sidelobe results with less computational time. The validity of the proposed CS imaging method is verified by simulation.},
year = {2015}
}
TY - JOUR T1 - A CS and SFCW Based Reconstruction Algorithm for Through-the-Wall Radar Imaging AU - Sun Yanpeng AU - Cui Zhao AU - Qu Lele Y1 - 2015/12/03 PY - 2015 N1 - https://doi.org/10.11648/j.jeee.20150305.21 DO - 10.11648/j.jeee.20150305.21 T2 - Journal of Electrical and Electronic Engineering JF - Journal of Electrical and Electronic Engineering JO - Journal of Electrical and Electronic Engineering SP - 165 EP - 169 PB - Science Publishing Group SN - 2329-1605 UR - https://doi.org/10.11648/j.jeee.20150305.21 AB - To satisfy with the increasingly exacting demand for real-time and high resolution requirements of TWRI, a Compressive Sensing (CS) based TWRI algorithm is proposed after the exploitation of Stepped-Frequency-Continuous-Wave (SFCW) system and signal’s sparsity. Contrasted with the traditional imaging methods, this algorithm achieved precise targets localization and low sidelobe results with less computational time. The validity of the proposed CS imaging method is verified by simulation. VL - 3 IS - 5 ER -
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