Blind Recognition for Hybrid Modulation Signals Based on High-order Cumulant and Squared Spectrum Feature

XU Qi-min; WAN Jun; HE Ling; WANG Qian

doi:10.12263/DZXB.20201287

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Blind Recognition for Hybrid Modulation Signals Based on High-order Cumulant and Squared Spectrum Feature

PAPERS | 更新时间：2025-12-08

- Blind Recognition for Hybrid Modulation Signals Based on High-order Cumulant and Squared Spectrum Feature
- ACTA ELECTRONICA SINICA Vol. 50, Issue 2, Pages: 426-431(2022)
- 作者机构：
  
  1.电子科技大学航空航天学院,四川成都 611731
  2.国家无线电监测中心成都监测站,四川成都 611136
  3.飞行器集群智能感知与协同控制四川省重点实验室,四川成都 611731
- 作者简介：
- 基金信息：
- DOI：10.12263/DZXB.20201287
  CLC： TN911.6;
- Received：17 November 2020，
  
  Revised：2021-04-11，
  
  Published：25 February 2022
- 稿件说明：
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许琦敏,万峻,何羚等.基于高阶累积量和信号平方谱特征的复合调制信号盲识别[J].电子学报,2022,50(02):426-431.

XU Qi-min,WAN Jun,HE Ling,et al.Blind Recognition for Hybrid Modulation Signals Based on High-order Cumulant and Squared Spectrum Feature[J].ACTA ELECTRONICA SINICA,2022,50(02):426-431.
许琦敏,万峻,何羚等.基于高阶累积量和信号平方谱特征的复合调制信号盲识别[J].电子学报,2022,50(02):426-431. DOI： 10.12263/DZXB.20201287.

XU Qi-min,WAN Jun,HE Ling,et al.Blind Recognition for Hybrid Modulation Signals Based on High-order Cumulant and Squared Spectrum Feature[J].ACTA ELECTRONICA SINICA,2022,50(02):426-431. DOI： 10.12263/DZXB.20201287.

摘要

针对符合CCSDS（Consultative Committee for Space Data Systems，国际空间数据系统咨询委员会）标准的多种复合调制体制测控信号，本文在建立8类典型调制信号数学模型的基础上，分析了信号的频域和统计域特征，并基于高阶累积量和信号平方谱提取了4个特征参数.根据所提的特征参数，针对复合调制信号提出了一种基于特征提取的直接识别方法，给出了具体的识别流程，并在11种信噪比下对该识别方法进行了MATLAB仿真实验.仿真结果表明在2 dB信噪比条件下，8类信号的识别率均达到98%，证明了所提复合调制盲识别方法的有效性.

Abstract

Aiming at multi-type hybrid modulation TT&C(telemetry

track and command) signals that comply with CCSDS(consultative committee for space data systems) standards

this paper analyzes the frequency domain and statistical domain characteristics of the signals on the basis of establishing eight types of typical modulation signal mathematical models

and four characteristic parameters are extracted based on the high-order cumulant and the squared spectrum of the signal. According to the proposed characteristic parameters

a direct identification method based on feature extraction is proposed for the multi-type hybrid modulation. The specific recognition process is given in the paper

and MATLAB simulation experiments are carried out on this recognition method under 11 signal-to-noise ratios. The simulation results show that under the condition of 2 dB signal-to-noise ratio

the recognition rates of 8 types of signals reach 98%

which proves the effectiveness of the proposed hybrid modulation blind recognition method.

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references

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