基于幂函数型随机共振的微弱信号恢复

doi:10.3969/j.issn.0372-2112.2018.08.015

电子学报 ›› 2018, Vol. 46 ›› Issue (8): 1906-1914.DOI: 10.3969/j.issn.0372-2112.2018.08.015

基于幂函数型随机共振的微弱信号恢复

贺利芳, 曹莉, 张刚, 易甜

重庆邮电大学信号与信息处理重庆市重点实验室, 重庆, 400065

收稿日期:2017-05-02 修回日期:2018-01-03 出版日期:2018-08-25
- 作者简介:
- 贺利芳 女,1979年出生于河南济源,重庆邮电大学副教授,研究方向为微弱信号检测及处理.E-mail:helf@cqupt.edu.cn;曹莉女,1992年出生于湖北黄冈,重庆邮电大学硕士研究生,研究方向为微弱信号检测.E-mail:1050020996@qq.com
- 基金资助:
- 国家自然科学基金 (No.61771085，No.61671095，No.61371164）; 信号与信息处理重庆市市级重点实验室建设项目 (No.CSTC2009CA2003）; 重庆市教育委员会科研项目 (No.KJ1600427，No.KJ1600429）

Weak Signal Recovery Based on Power Function Stochastic Resonance

HE Li-fang, CAO Li, ZHANG Gang, YI Tian

Chongqing Key Laboratory of Signal and Information Processing, Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Received:2017-05-02 Revised:2018-01-03 Online:2018-08-25 Published:2018-08-25

摘要/Abstract

摘要： 针对微弱信号淹没在强噪声中难以恢复的问题，提出幂函数恢复系统实现信号还原.采用互相关系数为测量指标，研究不同参数、噪声强度以及信号幅度对恢复性能的影响.并利用粒子群算法寻优参数，在采样点数较少情况下，实现单频、多频正弦信号以及单脉冲信号的恢复，结果表明理论分析与实际仿真结果一致，证明所提幂函数恢复系统有效可行，恢复效果理想.

关键词: 幂函数, 随机共振, 弱信号复原, 粒子群算法

Abstract: Aiming at the fact that the output signal is difficult to recover in the strong noise background,to solve this problem,power function recovery system is proposed to realize the signal restoration in this paper.The influence of different parameters and noise intensity as well as signal amplitude on the recovery performance are studied by using the mutual correlation coefficient as the measurement index.Power function recovery system achieves single-frequency sinusoidal signal and multi-frequency sinusoidal signal as well as single pulse signal recovery in the case of fewer sampling points and optimize parameters are opted with the particle swarm algorithm.Simulation results show that the theoretical analysis results are consistent with the simulations,which proves the proposed method is feasible and effective,and the achieved recovery effect is ideal.

Key words: power function, stochastic resonance, weak signal recovery, particle swarm optimization algorithm

中图分类号:

TN911.23

贺利芳, 曹莉, 张刚, 易甜. 基于幂函数型随机共振的微弱信号恢复[J]. 电子学报, 2018, 46(8): 1906-1914.

HE Li-fang, CAO Li, ZHANG Gang, YI Tian. Weak Signal Recovery Based on Power Function Stochastic Resonance[J]. Acta Electronica Sinica, 2018, 46(8): 1906-1914.

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基于幂函数型随机共振的微弱信号恢复

Weak Signal Recovery Based on Power Function Stochastic Resonance

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