单输入多输出水声信道的联合稀疏恢复估计

doi:10.3969/j.issn.1000-1093.2015.12.015

兵工学报 ›› 2015, Vol. 36 ›› Issue (12): 2321-2329.doi: 10.3969/j.issn.1000-1093.2015.12.015

单输入多输出水声信道的联合稀疏恢复估计

周跃海，曹秀岭，童峰，陈东升

（厦门大学海洋与地球学院，福建厦门 361101）

收稿日期:2015-03-22 修回日期:2015-03-22 上线日期:2016-02-02
通讯作者: 周跃海 E-mail:ruddy100@sina.com
作者简介:周跃海（1987—），男，博士研究生
基金资助:
国家自然科学基金项目（11274259）；教育部高等学校博士学科点专项项目（20120121110030）

Joint Sparse Recovery Estimation of Underwater Acoustic Single-input-multiple-output Channels

ZHOU Yue-hai，CAO Xiu-ling，TONG Feng，CHEN Dong-sheng

（College of Ocean and Earth Science，Xiamen University，Xiamen 361101，Fujian，China）

Received:2015-03-22 Revised:2015-03-22 Online:2016-02-02
Contact: ZHOU Yue-hai E-mail:ruddy100@sina.com

摘要/Abstract

摘要： 单输入多输出(SIMO)水声通信系统可利用空间分集获取性能增益，考虑到水声信道垂直相关半径通常大于SIMO接收阵的阵元间距，因此各个SIMO信道响应的多径稀疏结构具有较强的相关性。利用SIMO信道间存在的稀疏相关性，提出分布式压缩感知（CS）框架的SIMO水声信道联合稀疏恢复估计算法，与传统CS信道估计方法只利用信道自身稀疏性相比，联合稀疏恢复估计方法可进一步利用信道间多径结构的相关性提高稀疏重构性能。仿真和海试SIMO水声通信实验表明：与传统估计方法相比，利用多通道联合稀疏恢复可有效提高SIMO信道估计性能，特别是可获取较低信噪比条件下的性能改善。

关键词: 声学, 单输入多输出, 联合稀疏恢复, 分布式压缩感知, 水声信道估计

Abstract: Underwater single-input-multiple-output (SIMO) system enables the exploitation of space diversity to achieve performance enhancement. Considering that the vertical correlation radius of underwater channels is usually larger than the distance between array elements, the sparse structures of SIMO channels response exhibit considerable correlation feature. A channel estimation algorithm under the framework of distributed compressed sensing（CS）is presented to perform the joint sparse recovery estimation of SIMO channel via simultaneous orthogonal matching pursuit (OMP). Compared with the traditional CS channel estimation algorithms which only exploit the sparsity of single channel, the proposed algorithm is capable of employing the joint sparse correlation of SIMO channels to improve the performance of SIMO channel estimation. The simulation and field experimental results show that the proposed algorithm effectively improves the performance of SIMO channel estimation in terms of estimation accuracy and communication quality, especially under low signal-noise ratio.

Key words: acoustics, single-input-multiple-output, joint sparse recovery, distributed compressed sensing, underwater acoustic channel estimation

中图分类号:

TN929.3

周跃海，曹秀岭，童峰，陈东升. 单输入多输出水声信道的联合稀疏恢复估计[J]. 兵工学报, 2015, 36(12): 2321-2329.

ZHOU Yue-hai，CAO Xiu-ling，TONG Feng，CHEN Dong-sheng. Joint Sparse Recovery Estimation of Underwater Acoustic Single-input-multiple-output Channels[J]. Acta Armamentarii, 2015, 36(12): 2321-2329.

参考文献

[1] 张兰，许肖梅，冯伟，等. 浅海水声信道中重复累积性能研究[J]. 兵工学报，2012，33(2):179-185.
ZHANG Lan, XU Xiao-mei, FENG Wei, et al. Performance analysis of repeat-accumulate code over shallow water acoustic channel[J]. Acta Armamentarii，2012，33(2):179-185.（in Chinese）
[2] Song A, Abdi A, Badiey M, et al. Experimental demonstration of underwater acoustic communication by vector sensors[J]. IEEE Journal of Oceanic Engineering, 2011, 36(3): 454-461.
[3] Song A, Badiey M, Newhall A E, et al. Passive time reversal acoustic communications through shallow-water internal waves[J]. IEEE Journal of Oceanic Engineering，2010, 35(4): 756-765.
[4] Zhang G, Hovem J M, Dong H, et al. Coherent underwater communication using passive time reversal over multipath channels[J]. Applied Acoustics, 2011, 72(7): 412-419.
[5] Song H C. Time reversal communication in a time-varying sparse channel[J]. The Journal of the Acoustical Society of America, 2011, 130(4): EL161-EL166.
[6] Yang T C. Relating the performance of time-reversal-based underwater acoustic communications in different shallow water environments[J]. The Journal of the Acoustical Society of America, 2011, 130(4): 1995-2002.
[7] 周跃海, 李芳兰, 陈楷,等. 低信噪比条件下时间反转扩频水声通信研究[J]. 电子与信息学报, 2012, 34(7): 1685-1689.
ZHOU Yue-hai, LI Fang-lan, CHEN Kai, et al. Research of time reversal spread spectrum underwater acoustic communication under low SNR[J]. Journal of Electronics & Information Technology，2012, 34(7): 1685-1689. （in Chinese）
[8] 白晓慧, 孙超, 易锋, 等. 低信噪比下的浅海水声稀疏信道估计[J]. 西北工业大学学报, 2013, 31(1): 115-121.
BAI Xiao-hui, SUN Chao, YI Feng, et al. A better estimation method of sparse shallow-water acoustic channel under a low signal to noise environment[J]. Journal of Northwestern Polytechnical University, 2013, 31(1): 115-121. （in Chinese）
[9] Sazontov A G, Matveyev A L, Vdovicheva N K. Acoustic coherence in shallow water: theory and observation[J]. IEEE Journal of Oceanic Engineering，2002, 27(3): 653-664.
[10] Gorodetskaya E Y, Malekhanov A, Sazontov A G, et al. Deep-water acoustic coherence at long ranges: theoretical prediction and effects on large-array signal processing[J]. IEEE Journal of Oceanic Engineering，1999, 24(2): 156-171.
[11] Baron D，Wakin M B，Duarte M F，et al. Distributed compressed sensing［D］. Houston: Rice University, 2006
[12] 胡海峰,杨震. 无线传感器网络中基于空间相关性的分布式压缩感知[J]. 南京邮电大学学报：自然科学版，2009，29(6): 12-16.
HU Hai-feng, YANG Zhen. Spatial correlation-based distributed compressed sensing in wireless sensor networks[J]. Journal of Nanjing University of Posts and Telecommunications：Natural Science，2009，29(6): 12-16.（in Chinese）
[13] Corroy S，Mathar R. Distributed compressed sensing for the MIMO MAC with correlated sources[C]∥ 2012 IEEE International Conference on Communications. US：IEEE, 2012: 2516-2520.
[14] Tropp J A, Gilbert A C, Strauss M J. Simultaneous sparse approximation via greedy pursuit[C]∥ IEEE International Conference on Acoustics, Speech, and Signal Processing. NY, US：IEEE, 2005：721-724.
[15] 郭文彬,李春波,雷迪,等. 基于联合稀疏模型的 OFDM 压缩感知信道估计[J]. 北京邮电大学学报, 2014,37(3): 1-6.
GUO Wen-bin, LI Chun-bo, LEI Di, et al. Joint sparse model based OFDM compressed sensing channel estimation[J]. Journal of Beijing University of Posts and Telecommunications, 2014,37(3): 1-6. （in Chinese）
[16] 陈国新, 陈生昌, 王汉闯,等. 基于 L0 范数最小化的地球物理数据稀疏重构[J].应用地球物理, 2013, 10(2): 181-190.
CHEN Guo-xin, CHEN Sheng-chang, WANG Han-chuang, et al. Geophysical data sparse reconstruction via L0-norm minimization[J]. Appled Geophysics, 2013, 10(2): 181-190. （in Chinese）
[17] 张宗念, 黄仁泰, 闫敬文. 压缩感知信号盲稀疏度重构算法[J]. 电子学报, 2011, 39(1): 18-22.
ZHANG Zong-nian, HUANG Ren-tai, YAN Jing-wen. A blind sparsity reconstruction algorithm for compressed sensing signal[J]. Acta Electronica Sinica, 2012, 39(1): 18-22. （in Chinese）
[18] Wu F Y, Zhou Y H, Tong F, et al. Compressed sensing estimation of sparse underwater acoustic channels with a large time delay spread[J]. Journal of Southeast University：English Edition, 2014, 30(3)：271-277.
[19] 伍飞云,周跃海,童峰，等. 可适应稀疏度变化的非均匀范数约束水声信道估计算法[J]. 兵工学报，2014,35(9):1503-1509.
WU Fei-yun, ZHOU Yue-hai, TONG Feng, et al. Non-uniform norm constraint estimation algorithm for underwater acoustic channels at the presence of varying sparsity[J]. Acta Armamentarii, 2014, 35(9): 1503-1509. （in Chinese）
[20] Zeng W J, Xu W. Fast estimation of sparse doubly spread acoustic channels [J]. Journal of the Acoustical Society of America, 2012，131(1): 303-317.

单输入多输出水声信道的联合稀疏恢复估计

Joint Sparse Recovery Estimation of Underwater Acoustic Single-input-multiple-output Channels

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