电子学报 ›› 2021, Vol. 49 ›› Issue (9): 1768-1775.DOI: 10.12263/DZXB.20190147

• 学术论文 • 上一篇    下一篇

基于NSP的微弱频率确知信号的提取

胡维平1, 胡晰远2   

  1. 1.广西师范大学电子工程学院,广西 桂林 541004
    2.南京理工大学计算机科学与工程学院, 江苏 南京 210014
  • 收稿日期:2019-01-28 修回日期:2020-12-04 出版日期:2021-10-21
    • 作者简介:
    • 胡维平 男,1963年生,浙江舟山人,广西师范大学电子工程学院教授,研究方向为自适应信号处理,语音信号处理等
      胡晰远 男,1984年生,江西南昌人,南京理工大学计算机科学与工程学院教授,研究方向为自适应信号处理,数字图像处理与压缩等
    • 基金资助:
    • 国家自然科学基金 (61861005)

An Approach of Weak Frequency Determined Signal Extracting Based on Null Space Pursuit

HU Wei-ping1, HU Xi-yuan2   

  1. 1.College of Electronic Engineering, Guangxi Normal University, Guilin, Guangxi 541004, China
    2.School of Computer Science and Engineering, Nanjing University of Sciences & Technology, Nanjing, Jiangsu 210014, China
  • Received:2019-01-28 Revised:2020-12-04 Online:2021-10-21 Published:2021-09-25
    • Supported by:
    • National Natural Science Foundation of China (61861005)

摘要:

为实现确知频率信号在强噪声环境下的有效提取,本文在零空间追踪(Null Space Pursuit, NSP)方法的基础上,通过增加已知频率的先验信息约束,提出了一种基于频率确知信号约束的微弱信号提取方法.该方法继承了零空间追踪方法的优良属性,通过将确定的频率作为先验信息约束,可以实现其微弱信号相位和幅度的有效提取,仿真实验证明最多可实现高达30dB信噪比的提升;特别适合相对低信噪比环境下(信噪比小于-5dB)的微弱信号提取.该方法提供了常规的微弱确知信号的检测/提取方法之外的一种新的选择.

关键词: 自适应信号分解, 频率确知信号, 微弱信号提取, 零空间追踪

Abstract:

In order to realize the effective extraction of determined frequency signal under the strong noise environment,we propose a weak signal extraction method based on null space pursuit(NSP) and determined frequency signal constraint. The proposed approach inherits the excellent properties of NSP algorithm, by incorporating the determined frequency as prior information constraint,can extract the amplitude and phase of the weak signal effectively. The simulated experimental results show that, for the weak signal extraction, the proposed approach can improve signal to noise ratio (SNR) up to 30dB and especially suitable for low SNR environment extraction (i.e. SNR below -5dB). In addition to the traditional methods, this approach provides an alternative way for the weak signal extraction or detection.

Key words: adaptive signal separation, frequency determined signal, weak signal extracting, null space pursuit

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