LL-P-KF Hybrid Algorithm for Detecting and Recovering Sinusoidal Signal in Strong Chaotic Noise

SU Li-yun; SUN Huan-huan; LI Chen-long

doi:10.3969/j.issn.0372-2112.2017.04.011

您当前的位置：

首页 >

文章列表页 >

LL-P-KF Hybrid Algorithm for Detecting and Recovering Sinusoidal Signal in Strong Chaotic Noise

更新时间：2025-07-16

- LL-P-KF Hybrid Algorithm for Detecting and Recovering Sinusoidal Signal in Strong Chaotic Noise
- Acta Electronica Sinica Vol. 45, Issue 4, Pages: 837-843(2017)
- 作者机构：
  
  重庆理工大学数学与统计学院,重庆,400054
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.11471060);Basic and Frontier Research Program of Chongqing Municipal Science and Technology Commission (No.cstc2014jcyjA40003)
- DOI：10.3969/j.issn.0372-2112.2017.04.011
  CLC： TN911.23N941.7
- Published Online：25 April 2017，
  
  Published：2017
- 稿件说明：
移动端阅览
SU Li-yun, SUN Huan-huan, LI Chen-long. LL-P-KF Hybrid Algorithm for Detecting and Recovering Sinusoidal Signal in Strong Chaotic Noise[J]. Acta Electronica Sinica, 2017, 45(4): 837-843.
DOI：

SU Li-yun, SUN Huan-huan, LI Chen-long. LL-P-KF Hybrid Algorithm for Detecting and Recovering Sinusoidal Signal in Strong Chaotic Noise[J]. Acta Electronica Sinica, 2017, 45(4): 837-843. DOI： 10.3969/j.issn.0372-2112.2017.04.011.

摘要

本文提出一种局域线性-周期图检测-卡尔曼滤波混合算法LL-P-KF，用来恢复强混沌背景下正弦信号.首先，建立混沌信号的一步预测模型；然后，利用周期图检测潜在周期；最后，应用卡尔曼滤波从误差中恢复正弦信号.仿真实验表明该混合算法具有较好的恢复效果.

Abstract

The paper proposes a local linear-periodogram-Kalman filtering (LL-P-KF) hybrid algorithm.Firstly

a local linear method is established;secondly

the periods of sinusoidal signal are detected from modeling error by using periodogram;finally

the sinusoidal signal is recovered from the error by using Kalman filtering.Simulation results show that the LL-P-KF hybrid algorithm has better recovery results.

关键词

Keywords

references

Views

354

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Detection of LDDoS Attack Based on Kalman Filtering

Technique of Two Searches on SITAN Algorithm for Seabed Terrain-Aided Navigation

Kalman Filtering of Fractal Stochastic Signals Based on Wavelet Transform

Optimal Data Collection Strategies for Energy-Constrained Sensor Networks

Related Author

李广侠

常江

吕晶

李罡

YUE Meng

WU Zhi-jun

CHEN Jia-bin

DENG Wei

Related Institution

Key Laboratory of Satellite Communications,PLA University of Science and Technology

College of Electronics and Information Engineering,Civil Aviation University of China

Department of Automatic ControlSchool of Information Science and TechnologyBeijing Institute of TechnologyBeijing 100081China

Beijing Key Laboratory of Spatial Information Integration and ApplicationsPeking UniversityBeijing 100871China

Department of Automatic Control,School of Information Science and Technology,Beijing Institute of Technology

⁰