Bayesian Forward-looking Imaging for Airborne Single-channel Radar Based on Combined Multiple Frames Data

Chen Hong-meng; Li Ming; Wang Ze-Yu; Lu Yun-long; Zhang Peng; Zuo Lei

doi:10.11999/JEIT150153

Volume 37 Issue 10

Sep. 2015

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Article Navigation > Journal of Electronics & Information Technology > 2015 > 37(10): 2328-2334

Chen Hong-meng, Li Ming, Wang Ze-Yu, Lu Yun-long, Zhang Peng, Zuo Lei. Bayesian Forward-looking Imaging for Airborne Single-channel Radar Based on Combined Multiple Frames Data[J]. Journal of Electronics & Information Technology, 2015, 37(10): 2328-2334. doi: 10.11999/JEIT150153

Citation:

Chen Hong-meng, Li Ming, Wang Ze-Yu, Lu Yun-long, Zhang Peng, Zuo Lei. Bayesian Forward-looking Imaging for Airborne Single-channel Radar Based on Combined Multiple Frames Data[J]. Journal of Electronics & Information Technology, 2015, 37(10): 2328-2334. doi: 10.11999/JEIT150153

Citation:

Chen Hong-meng, Li Ming, Wang Ze-Yu, Lu Yun-long, Zhang Peng, Zuo Lei. Bayesian Forward-looking Imaging for Airborne Single-channel Radar Based on Combined Multiple Frames Data[J]. Journal of Electronics & Information Technology, 2015, 37(10): 2328-2334. doi: 10.11999/JEIT150153

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Bayesian Forward-looking Imaging for Airborne Single-channel Radar Based on Combined Multiple Frames Data

doi: 10.11999/JEIT150153

Funds:

The National Natural Science Foundation of China (61271297, 61272281, 61301284)

Received Date: 2015-01-27
Rev Recd Date: 2015-04-20
Publish Date: 2015-10-19

Abstract

Abstract

An adaptive Bayesian super-resolution imaging algorithm based on the combined multiple frames data is proposed to enhance the azimuth resolution of airborne single-channel forward-looking radar. The echo of the forward-looking radar in the Gaussian noise is modeled, and the processing space is expanded from the low dimension of single frame data to the high dimension of multiple frames data to enhance the sparsity of domain scatterers. During the framework, the sparsity of the scatterers is modeled in spatial domain, and the imaging is converted into a problem of signal optimization based on Bayesian formalism. The final optimal result can be solved by the conjugate gradient method. In this framework, the statistic parameter is estimated with data-driven. Simulation results demonstrate that the proposed algorithm both can increase the resolution of the forward-looking imaging results and suppress the artifacts.
- Airborne radar,
- Real beam sharpening,
- Forward-looking imaging,
- Bayesian formalism,
- Super-resolution

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References(30)

References

Richards M A. Fundamentals of Radar Signal Processing [M]. New York: McGraw-Hill, 2005: 390-401.

Wang R, Deng Y K, Loffeld O, et al.. Processing the azimuth-variant bistatic SAR data by using monostatic imaging algorithms based on 2-D principle of stationary phase[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(10): 3504-3520.

Wu J, Li Z, Huang Y, et al.. Bistatic forward-looking SAR with stationary transmitter based on keystone transform and nonlinear chirp scaling[J]. IEEE Geoscience and Remote Sensing Letters, 2014, 11(1): 148-152.

Wang R, Deng Y K, Zhang Z Z, et al.. Double-channel bistatic SAR system with spaceborne illuminator for 2-D and 3-D SAR remote sensing[J]. IEEE Transactions on Geoscience and Remote Sensing, 2013, 51(8): 4496-4507.

Li W, Yang J, and Huang Y. Keystone transform-based space-variant range migration correction for airborne forward-looking scanning radar[J]. Electronics Letters, 2012, 48(2): 121-122.

包敏, 周鹏, 史林. 双天线前视弹载SAR 解模糊算法研究[J]. 电子与信息学报, 2013, 35(12): 2857-2862.

Bao Min, Zhou Peng, and Shi Lin. Study on deambiguity algorithm for double antenna forward looking missile borne

SAR[J]. Journal of Electronic Information Technology, 2013, 35(12): 2857-2862.

庞礡, 王雪松, 代大海, 等. 基于数字波束锐化的高速前视合成孔径雷达成像算法[J]. 电波科学学报, 2014, 29(1): 92-98.

Pang Bo, Wang Xue-song, Dai Da-hai, et al.. Imaging algorithm of high velocity forward-looking SAR based on digital beam sharpening[J]. Chinese Journal of Radio Science, 2014, 29(1): 92-98.

吴迪, 朱岱寅, 田斌, 等. 单脉冲成像算法性能分析[J]. 航空学报, 2012, 33(10): 1905-1914.

Wu Di, Zhu Dai-yin, Tian Bin, et al.. Performance evaluation for monopulse imaging algorithm[J]. Acta Aeronautica et Astronautica Sinica, 2012, 33(10): 1905-1914.

杨志伟, 贺顺, 廖桂生. 机载单通道雷达实波束扫描的前视探测[J]. 航空学报, 2012, 33(12): 2240-2245.

Yang Zhi-wei, He Shun, and Liao Gui-sheng. Forward- looking detection for airborne single-channel radar with beam scanning[J]. Acta Aeronautica et Astronautica Sinica, 2012, 33(12): 2240-2245.

温晓杨, 匡纲要, 胡杰民, 等. 基于实波束扫描的相控阵雷达前视成像[J]. 航空学报, 2014, 35(7): 1977-1991.

Wen Xiao-yang, Kuang Gang-yao, Hu Jie-min, et al.. Forward-looking imaging based on real beam scanning phased array radars[J]. Acta Aeronautica et Astronautica Sinica, 2014, 35(7): 1977-1991.

王军, 赵宜楠, 乔晓林. 基于压缩感知的雷达前视向稀疏目标分解[J]. 电子与信息学报, 2014, 36(8): 1978-1984.

Wang Jun, Zhao Yi-nan, and Qiao Xiao-lin. A sparse target-scenario determination strategy based on compressed sensing for active radar in the line of sight[J]. Journal of Electronic Information Technology, 2014, 36(8): 1978-1984.

Richards M A. Iterative noncoherent angular superresolution [C]. Proceedings of the IEEE National Radar Conference, Ann Arbor, USA, 1988: 100-105.

李悦丽, 梁甸农, 黄晓涛. 一种单脉冲雷达多通道解卷积前视成像方法[J]. 信号处理, 2007, 23(5): 700-703.

Li Yue-li, Liang Dian-nong, and Huang Xiao-tao. A multi-channel deconvolution based on forward-looking

imaging method in monopulse radar[J]. Signal Processing, 2007, 23(5): 700-703.

Li D Y, Huang Y L, and Yang J Y. Real beam radar imaging based on adaptive Lucy-Richardson algorithm[C]. Proceedings of the International Conference on Radar, Chengdu, China, 2011: 1437-1440.

Babacan S D, Molina R, and Katsaggelos A K. Bayesian compressive sensing using Laplace priors[J]. IEEE Transactions on Image Processing, 2010, 19(1): 53-63.

夏建明, 杨俊安, 陈功. 参数自适应调整的稀疏贝叶斯重构算法[J]. 电子与信息学报, 2014, 36(6): 1355-1361.

Xia Jian-ming, Yang Jun-an, and Chen Gong. Bayesian sparse reconstruction with adaptive parameters adjustment [J]. Journal of Electronic Information Technology, 2014, 36(6): 1355-1361.

Xu Gang, Xing Meng-dao, Zhang Lei, et al.. Bayesian inverse synthetic aperture radar imaging[J]. IEEE Geoscience and Remote Sensing Letters, 2011, 8(6): 1150-1154.

吴敏, 邢孟道, 张磊. 基于压缩感知的二维联合超分辨ISAR成像算法[J]. 电子与信息学报, 2014, 36(1): 187-193.

Wu Min, Xing Meng-dao, and Zhang Lei. Two dimensional joint super-resolution ISAR imaging algorithm based on compressive sensing[J]. Journal of Electronic Information Technology, 2014, 36(1): 187-193.

Long Teng, Lu Zheng, Ding Ze-gang, et al.. A DBS Boppler centroid estimation algorithm based on entropy minimization[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(10): 3703-3712.

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