Symbol Rate Estimation for CPM Signal Based on Discrete Wavelet Decomposition and Frequency Ridge Analysis

LIU Qiu-hong; LI Tian-yun; WANG Bin; XU Man-kun; QIU Zhao-yang

doi:10.3969/j.issn.0372-2112.2020.03.008

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Symbol Rate Estimation for CPM Signal Based on Discrete Wavelet Decomposition and Frequency Ridge Analysis

更新时间：2025-07-16

- Symbol Rate Estimation for CPM Signal Based on Discrete Wavelet Decomposition and Frequency Ridge Analysis
- Acta Electronica Sinica Vol. 48, Issue 3, Pages: 470-477(2020)
- 作者机构：
  
  中国人民解放军战略支援部队信息工程大学,河南,郑州,450001
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0372-2112.2020.03.008
  CLC： TN911.6
- Published Online：25 March 2020，
  
  Published：2020
- 稿件说明：
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LIU Qiu-hong, LI Tian-yun, WANG Bin, et al. Symbol Rate Estimation for CPM Signal Based on Discrete Wavelet Decomposition and Frequency Ridge Analysis[J]. Acta Electronica Sinica, 2020, 48(3): 470-477.
DOI：

LIU Qiu-hong, LI Tian-yun, WANG Bin, et al. Symbol Rate Estimation for CPM Signal Based on Discrete Wavelet Decomposition and Frequency Ridge Analysis[J]. Acta Electronica Sinica, 2020, 48(3): 470-477. DOI： 10.3969/j.issn.0372-2112.2020.03.008.

摘要

非合作接收条件下，连续相位调制（CPM，Continuous Phase Modulation）信号多变未知的信号体制使其符号速率盲估计一直是分析该类信号的难点之一.现有的算法大多直接基于信号的瞬时频率或循环平稳性，存在抗噪性能差，不适用于多指数CPM信号等问题.针对该问题，本文通过分析小波变换在信号分解和时频分析中的优势，提出一种综合利用离散小波（DWT，Discrete Wavelet Transform）分解和频率脊线提取的CPM信号符号速率估计的新算法.算法对比分析表明，所提算法具有更好的抗噪性能且在小数据量时也能达到较好的估计性能.

Abstract

In the case of non-cooperative reception

blind estimation for the symbol rate estimation of continuous phase modulation (CPM) signals is usually one of the difficulties in signal analysis due to the varied signal specification. Most of the existing algorithms are based directly on instantaneous frequency or cyclostationarity

which have poor anti-noise performance and are not suitable for multi-h CPM signals. By analyzing the advantages of wavelet transform in signal decomposition and time-frequency

a new algorithm based on discrete wavelet transform (DWT) and frequency ridge extraction is proposed to estimate the symbol rate of CPM signal. Comparative analysis of the algorithm shows that the proposed method has better performance in condition of the low signal to noise ratio (SNR) and small data volume.

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