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; 杨坤德; 童峰

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

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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

学术论文 | 更新时间：2024-06-05

- 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
- 通信学报 2018年39卷第6期页码：127-132
- 作者机构：
  
  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
- 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。" ]
- 基金信息：
  
  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)
- DOI：10.11959/j.issn.1000-436x.2018099
  中图分类号： TN929.3
- 网络出版日期：2018-06，
  
  纸质出版日期：2018-06-25
- 稿件说明：
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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.
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. DOI： 10.11959/j.issn.1000-436x.2018099.

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

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l

范数，该问题表现为NP难问题，因此，常将其转化为求l

范数约束最小化问题，而求l

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。

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 l

norm

which is an NP hard problem.Hence

the common methods were transferred to minimize l

norm.However

norm 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 prop

osed method is used for at-sea data telemetry.Combining with DCT

the proposed method improves the recovery accuracy.

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Keywords

references

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