部分范数约束的稀疏恢复算法及其在单载波水声数据遥测中的应用

doi:10.11959/j.issn.1000-436x.2018099

通信学报 ›› 2018, Vol. 39 ›› Issue (6): 127-132.doi: 10.11959/j.issn.1000-436x.2018099

部分范数约束的稀疏恢复算法及其在单载波水声数据遥测中的应用

伍飞云^1,²,杨坤德^1,²,童峰³

¹ 西北工业大学航海学院，陕西西安 710072
² 西北工业大学海洋声学信息感知工业和信息化部重点实验室，陕西西安 710072
³ 厦门大学水声通信与海洋信息技术教育部重点实验室，福建厦门 361005

修回日期:2018-04-09 出版日期:2018-06-01 发布日期:2018-07-09
作者简介:伍飞云（1984-），男，江西宜春人，西北工业大学助理教授，主要研究方向为信号处理、压缩感知、水声通信等。|杨坤德（1974-），男，四川邻水人，西北工业大学教授、博士生导师，主要研究方向为信号处理、压缩感知、微波传输等。|童峰（1973-），男，福建龙岩人，厦门大学教授、博士生导师，主要研究方向为水声通信、水声网络、水声信号处理等。
基金资助:
国家自然科学基金资助项目(61701405);中央高校基本科研业务费专项资金资助项目(3102017OQD007);中国博士后科学基金资助项目(2017M613208)

Partial-norm-constrained sparse recovery algorithm and its application on single carrier underwater-acoustic-data telemetry

Feiyun WU^1,²,Kunde YANG^1,²,Feng TONG³

¹ School of Marine Science and Technology,Northwestern Polytechnical University,Xi’an 710072,China
² Key Laboratory of Ocean Acoustics and Sensing Ministry of Industry and Information Technology,Northwestern Polytechnical University,Xi’an 710072,China
³ Key Laboratory of Underwater Acoustic Communication and Marine Information Technique of the Ministry of Education,Xiamen University,Xiamen 361005,China

Revised:2018-04-09 Online:2018-06-01 Published:2018-07-09
Supported by:
The National Natural Science Foundation of China(61701405);The Central University Basic Business Expenses Spe-cial Funding for Scientific Research Projects(3102017OQD007);China Postdoctoral Science Foundation Projects(2017M613208)

摘要/Abstract

摘要：

对于单载波水声数据压缩与恢复问题，压缩感知能以较低能耗获得信号压缩与恢复效果。但压缩感知核心目标是直接求最小l₀范数，该问题表现为NP难问题，因此，常将其转化为求l₁范数约束最小化问题，而求l₁范数约束最小化的稀疏解精度有限。基于此，推导出基于部分范数约束的稀疏信号恢复算法，该算法通过部分范数约束在拉格朗日求解中增加一个零吸引项，从而动态分配稀疏抽头的软阈值。同时，该算法用于实际海上数据的遥测，结合离散余弦变换（DCT），可将单载波水声数据恢复精度提高。

关键词: 压缩感知, 单载波水声数据, 部分范数约束

Abstract:

To solve the problem of single carrier underwater-acoustic-data telemetry,compressive sensing (CS) provides competitive performance of compression and recovery with low energy consumption.The primary objective of CS is to minimize the l₀norm,which is an NP hard problem.Hence,the common methods were transferred to minimize l₁norm.However,l₁norm minimization provided a limited accuracy.A partial-norm-constraint (PNC) based sparse signal recovery method was derived,which adopted PNC as a zero attraction in a Lagrange method,to distribute the soft threshold for the non-zero taps.The proposed method is used for at-sea data telemetry.Combining with DCT,the proposed method improves the recovery accuracy.

Key words: compressive sensing, single carrier underwater-acoustic-data, partial-norm-constraint

中图分类号:

TN929.3

伍飞云,杨坤德,童峰. 部分范数约束的稀疏恢复算法及其在单载波水声数据遥测中的应用[J]. 通信学报, 2018, 39(6): 127-132.

Feiyun WU,Kunde YANG,Feng TONG. Partial-norm-constrained sparse recovery algorithm and its application on single carrier underwater-acoustic-data telemetry[J]. Journal on Communications, 2018, 39(6): 127-132.

图/表 4

参考文献 17

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部分范数约束的稀疏恢复算法及其在单载波水声数据遥测中的应用

Partial-norm-constrained sparse recovery algorithm and its application on single carrier underwater-acoustic-data telemetry

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