高级搜索

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于压缩感知的伪随机多相码连续波雷达

贺亚鹏 王克让 张劲东 朱晓华

贺亚鹏, 王克让, 张劲东, 朱晓华. 基于压缩感知的伪随机多相码连续波雷达[J]. 电子与信息学报, 2011, 33(2): 418-423. doi: 10.3724/SP.J.1146.2010.00380
引用本文: 贺亚鹏, 王克让, 张劲东, 朱晓华. 基于压缩感知的伪随机多相码连续波雷达[J]. 电子与信息学报, 2011, 33(2): 418-423. doi: 10.3724/SP.J.1146.2010.00380
He Ya-Peng, Wang Ke-Rang, Zhang Jin-Dong, Zhu Xiao-Hua. Compressive Sensing Based Pseudo-random Multi-phase CW Radar[J]. Journal of Electronics & Information Technology, 2011, 33(2): 418-423. doi: 10.3724/SP.J.1146.2010.00380
Citation: He Ya-Peng, Wang Ke-Rang, Zhang Jin-Dong, Zhu Xiao-Hua. Compressive Sensing Based Pseudo-random Multi-phase CW Radar[J]. Journal of Electronics & Information Technology, 2011, 33(2): 418-423. doi: 10.3724/SP.J.1146.2010.00380

基于压缩感知的伪随机多相码连续波雷达

doi: 10.3724/SP.J.1146.2010.00380

Compressive Sensing Based Pseudo-random Multi-phase CW Radar

  • 摘要: 该文利用雷达目标空间的稀疏特性,提出了一种基于压缩感知的伪随机多相码连续波雷达。建立了目标信息感知模型,采用压缩感知以低于奈奎斯采样率对目标回波采样,然后从少量的采样数据中提取噪声背景下的目标场景信息。为了提高目标信息提取的有效性,采用模拟退火算法对波形进行优化。仿真结果表明了该方法的优越性。
  • Cands E J, Romberg J, and Tao T. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information [J].IEEE Transactions on Information Theory.2006, 52(2):489-509[2]Cands E J, Romberg J, and Tao T. Stable signal recovery from incomplete and inaccurate measurements [J].Communications on Pure and Applied Mathematics.2006, 59(8):1207-1223[3]Cands E J. Compressive sampling[C]. International Congress of Mathematicians, Madrid, Spain, 2006, 3: 1433-1452.[4]Donoho D L. Compressed sensing [J].IEEE Transactions on Information Theory.2006, 52(4):1289-1306[5]Cands E J and Wakin M B. An introduction to compressive sampling [J].IEEE Signal Processing Magazine.2008, 25(2):21-30[6]Romberg J. Imaging via compressive sampling [J]. IEEE Signal Processing Magazine, 2008, 25(2): 14-20.[7]Paredes J L, Arcw G R, and Wang Z M. Ultra-wideband[8]compressed sensing: channel estimation [J]. IEEE Journal of Selected Topics in Signal Processing, 2007, 1(3): 383-395.[9]Mishali M, Eldar Y C, and Tropp J A. Efficient sampling of sparse wideband analog signals [C]. IEEE 25th Convention of Electrical and Electronics Engineers, Israel, Dec 3-5, 2008: 290-294.Skolnik M I. Radar Handbook[M]. 3rd ed, New York: McGraw-Hill, 2008: 382-425.[10]Baraniuk R and Steeghs P. Compressive radar imaging [C]. 2007 IEEE International Radar Conference, Boston, Massachusetts, USA, April 17-20, 2007: 128-133.[11]Herman M A and Strohmer T. Compressed sensing radar[C]. IEEE International Conference on Acoustics, Speech and Signal Processing, Las Vegas, Nevada, USA, March 30-April 4, 2008: 2617-2620.[12]Tello M, Lopez-Dekker P, and Mallorqui J J. A novel strategy for radar imaging based on compressive sensing [C]. IEEE International Conference on Geoscience and Remote Sensing Symposium, Boston, Massachusetts, USA, July 6-11, 2008: 213-216.[13]Herman M A and Strohmer T. High-resolution radar via compressed sensing [J].IEEE Transactions on Signal Processing.2009, 57(6):2275-2284[14]Levanon N and Mozeson E. Radar Signals [M]. New York: John Wiley Sons, 2004: 297-301.[15]Cands E J and Tao T. The Dantzig selector: Statistical estimation when p is much larger than n [J].Annals of Statistics.2007, 35(6):2313-2351[16]Tropp J A. Greed is good: Algorithmic results for sparse approximation [J].IEEE Transactions on Information Theory.2004, 50(10):2231-2242[17]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
  • 加载中
计量
  • 文章访问数:  3622
  • HTML全文浏览量:  119
  • PDF下载量:  1120
  • 被引次数: 0
出版历程
  • 收稿日期:  2010-04-16
  • 修回日期:  2010-07-02
  • 刊出日期:  2011-02-19

目录

    /

    返回文章
    返回