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

Feiyun WU; Kunde YANG; Feng TONG

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

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

Papers | 更新时间：2024-06-05

- Partial-norm-constrained sparse recovery algorithm and its application on single carrier underwater-acoustic-data telemetry
- Journal on Communications Vol. 39, Issue 6, Pages: 127-132(2018)
- 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：
- 基金信息：
  
  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)
- DOI：10.11959/j.issn.1000-436x.2018099
  CLC： TN929.3
- Online First：2018-06，
  
  Published：25 June 2018
- 稿件说明：
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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：

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.

关键词

Keywords

references

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