[1]贺亚鹏,朱晓华,庄珊娜,等.压缩感知雷达波形优化设计[J].南京理工大学学报(自然科学版),2011,(04):519-524.
HE Ya-peng,ZHU Xiao-hua,ZHUANG Shan-na,et al.Optimal Waveform Design for Compressive Sensing Radar[J].Journal of Nanjing University of Science and Technology,2011,(04):519-524.
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压缩感知雷达波形优化设计
《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]
- 卷:
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- 期数:
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2011年04期
- 页码:
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519-524
- 栏目:
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- 出版日期:
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2011-08-31
文章信息/Info
- Title:
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Optimal Waveform Design for Compressive Sensing Radar
- 作者:
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贺亚鹏; 朱晓华; 庄珊娜; 王克让
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南京理工大学电子工程与光电技术学院,江苏南京210094
- Author(s):
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HE Ya-peng; ZHU Xiao-hua; ZHUANG Shan-na; WANG Ke-rang
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School of Electronic Engineering and Optoelectronic Technology,NUST,Nanjing 210094,China
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- 关键词:
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压缩感知雷达; 波形优化; 感知矩阵; 相关性; 模拟退火
- Keywords:
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compressive sensing radars; waveform design; sensing matrix; coherence; simulated annealing
- 分类号:
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TN958. 8
- 摘要:
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针对压缩感知雷达( CSR) 波形优化问题,该文提出一种基于感知矩阵相关性最小化的
CSR 波形优化设计方法。首先建立了CSR 的系统模型,给出了最小化感知矩阵相关性的波形
优化目标函数,其次以多相编码信号作为优化码型,采用模拟退火( SA) 算法对目标函数进行优
化求解。优化波形有效降低了感知矩阵的相关性,由此提高了CSR 目标信息提取的准确性和
稳健性。计算机仿真表明优化波形使得感知矩阵相关系数较传统雷达波形明显减小,验证了该
方法的有效性。
- Abstract:
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To solve the problem of waveform optimization for compressive sensing radar( CSR) ,an
optimized method for CSR waveform design through minimizing the coherence of the sensing matrix is
proposed here. The system model of CSR is established and the objective function of the waveform
optimization for minimizing the coherence of the sensing matrix is presented. The simulated annealing
( SA) algorithm is employed to find the optimal solution to the objective function taking polyphase coded
signal as an example. The optimized waveform can effectively reduce the coherence of the corresponding
sensing matrix,and thus improve the accuracy and robustness of the CSR target information
extraction. The computer simulation shows that the optimized waveform significantly reduces the coherence
of the sensing matrix compared with traditional radar waveforms,and hence confirms the effectiveness
of this proposed method.
参考文献/References:
[1] 石光明,刘丹华,高大化,等. 压缩感知理论及其研
究进展[J]. 电子学报, 2009, 37( 5) : 1071-1081.
[2] Candès E J,Romberg J,Tao T. Robust uncertainty principles:
Exact signal reconstruction from highly incomplete
frequency information[J]. IEEE Transactions on Information
Theory, 2006, 52( 2) : 489-509.
[3] Candès E J,Romberg J,Tao T. Stable signal recovery
from incomplete and inaccurate measurements [J].
Communications on Pure and Applied Mathematics,
2006, 59( 8) : 1207-1223.
[4] Candès E J. Compressive sampling[A]. Proceedings of
ICM2006[C]. Madrid,Spain: Association International
Congress of Mathematicians, 2006: 1433-1452.
[5] Donoho D L. Compressed sensing [J ]. IEEE
Transactions on Information Theory, 2006, 52( 4) : 1289
-1306.
[6] Baraniuk R, Steeghs P. Compressive radar imaging[A].
Proceedings of IEEE International Radar Conference [C]. Boston,USA: IEEE Press, 2007: 128-133.
[7] Herman M A,Strohmer T. High-resolution radar via
compressed sensing[J]. IEEE Transactions on Signal
Processing, 2009, 57( 6) : 2275-2284.
[8] 余慧敏,方广有. 压缩感知理论在探地雷达三维成
像中的应用[J]. 电子与信息学报,2010,32( 1) : 12
-16.
[9] 宋琳,曹吉海. 基于随机滤波的雷达信号采样和目
标重建方法[J]. 科技导报, 2008, 26( 13) : 64-67.
[10] Shi G M,Chen X Y,Qi F, et al. UWB echo signal detection
with ultra-low rate sampling based on compressed
sensing[J]. IEEE Transactions on Circuits and Systems
II: Express Briefs, 2008, 55( 4) : 379-383.
[11] Tello A M,López-Dekker F,Mallorquí J J. A novel
strategy for radar imaging based on compressive
sensing[J]. IEEE Transactions on Geoscience and Remote
Sensing, 2010, 48( 9) : 1-11.
[12] Subotic N S,Thelen B,Cooper K,et al. Distributed
radar waveform design based on compressive sensing
considerations[A]. Proceedings of IEEE International
Radar Conference[C]. Rome, Italy: IEEE Press, 2008:
1-6.
[13] Donoho D L,Elad M,Temlyakov V N. Stable recovery
of sparse overcomplete representations in the presence
of noise[J]. IEEE Transactions on Information Theory,
2006, 52( 1) : 6-18.
[14] Deng H. Synthesis of binary sequences with good autocorrelation
and crosscorrelation properties by simulated
annealing[J]. IEEE Transactions on Aerospace and Electronic
Systems, 1996, 32( 1) : 98-107.
[15] 张宇,王建新,孙锦涛. MIMO 雷达的相位编码信号
设计[J]. 兵工学报, 2010, 31( 1) : 109-112.
[16] Levanon N,Mozeson E. Radar signal[M]. New York:
John Wiley & Sons, 2004: 297-301.
备注/Memo
- 备注/Memo:
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基金项目: 南京理工大学自主科研专项计划( 2010ZYTS028; 2010ZDJH05)
作者简介: 贺亚鹏( 1984-) ,男,博士生,主要研究方向: 高分辨雷达信号处理、阵列信号处理、压缩感知雷达信号
采样与处理等,E-mail: yapeng. he@ gmail. com; 通讯作者: 朱晓华( 1966-) ,男,教授,博士生导师,主要
研究方向: 雷达系统、高速实时数字信号处理等,E-mail: zxh@ mail. njust. edu. cn。
更新日期/Last Update:
2012-10-23