吉林大学学报(工学版) ›› 2024, Vol. 54 ›› Issue (11): 3392-3398.doi: 10.13229/j.cnki.jdxbgxb.20230869

• 通信与控制工程 • 上一篇    

低信噪比下短波数字信号调制识别算法

郑礼1,2(),闫光辉1(),严天峰1,2   

  1. 1.兰州交通大学 电子与信息工程学院,兰州 730070
    2.甘肃省无线电监测及定位行业技术中心,兰州 730070
  • 收稿日期:2023-08-16 出版日期:2024-11-01 发布日期:2025-04-24
  • 通讯作者: 闫光辉 E-mail:zhengli3227@163.com;ghyan@mail.lzjtu.cn
  • 作者简介:郑礼(1989-),男,讲师,博士.研究方向:软件无线电,智能频频认知与机器学习.E-mail:zhengli3227@163.com
  • 基金资助:
    国家自然科学基金项目(62062049);中央指导性地方科技发展基金项目(22ZY1QA005);甘肃省重大科技专项项目(22ZD6GA041);兰州交通大学青年科学基金项目(2023009)

Modulation recognition algorithm for shortwave digital signals under low signal-to-noise ratio

Li ZHENG1,2(),Guang-hui YAN1(),Tian-feng YAN1,2   

  1. 1.School of Electronics and Information Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China
    2.Gansu Province Radio Monitoring and Positioning Industry Technology Center,Lanzhou 730070,China
  • Received:2023-08-16 Online:2024-11-01 Published:2025-04-24
  • Contact: Guang-hui YAN E-mail:zhengli3227@163.com;ghyan@mail.lzjtu.cn

摘要:

针对信道存在噪声的干扰,为了更好地获取短波数字信号,提出了低信噪比下短波数字信号调制识别算法,构建需要识别的短波数字信号模型,采集发射信号,获得脉冲噪声、高斯噪声、码间串扰信号。利用瞬时数值算出滚降和匹配滤波器的振幅频率响应,结合相位校正,抑制噪声影响。小波滤波技术通过优化瞬时信息,求出瞬时振幅、瞬时相位、瞬时频率绝对值的平均数,完成短波数字信号调制识别。通过实验,证明本文算法能有效完成数字信号调制识别,噪声影响较小,准确性高。

关键词: 低信噪比, 短波数字信号, 信号调制识别, 瞬时频率, 特征参量

Abstract:

In order to better obtain shortwave digital signals due to noise interference in the channel, a modulation recognition algorithm for shortwave digital signals under low signal-to-noise ratio is proposed. The short wave digital signal model to be identified is constructed, and the transmitted signals are collected to obtain pulse noise, Gaussian noise, and intersymbol interference signals. The roll off and the amplitude frequency response of the Matched filter are calculated using instantaneous values, and the noise effect is suppressed by combining phase correction. The instantaneous information is optimized by wavelet filtering technology, and the average of instantaneous amplitude, instantaneous phase and Instantaneous phase and frequency absolute value is calculated to complete modulation recognition of short wave digital signal. Through experiments, it has been proven that the proposed algorithm can effectively achieve digital signal modulation recognition with minimal noise impact and high accuracy.

Key words: low signal-to-noise ratio, short wave digital signal, signal modulation recognition, instantaneous phase and frequency, characteristic parameters

中图分类号: 

  • TN91

图1

短波数字信号调制识别流程"

图2

2ASK信号调制识别"

图3

4ASK信号调制识别"

图4

2FSK信号调制识别"

图5

4FSK信号调制识别"

图6

2PSK信号调制识别"

图7

4PSK信号调制识别"

1 白维维, 梁丽香. 物联网下多径信道数字信号调制检测研究[J]. 计算机仿真, 2018, 35(5): 346-349.
Bai Wei-wei, Liang Li-xiang. Research on modulation detection of multipath channels under internet of things[J]. Computer Simulation, 2018, 35(5): 346-349.
2 Chen W, Jiang Y, Zhang L, et al. A new modulation recognition method based on wavelet transform and high-order cumulants[J]. Journal of Physics Conference Series, 2021, 1738: 012025.
3 李泊含, 刘芸江, 李艳福. 基于多尺度金字塔池化的调制识别算法[J]. 电光与控制, 2022, 29(12): 18-24.
Li Bo-han, Liu Yun-jiang, Li Yan-fu. A modulation recognition algorithm based on multi-scale pyramid pooling[J]. Electronics Optics & Control, 2022, 29(12): 18-24.
4 Mi X, Chen X, Liu Q, et al. Radar signals modulation recognition based on bispectrum feature processing[J]. Journal of Physics: Conference Series, 2021, 1971(1): 012099.
5 Chen K, Zhu L, Chen S, et al. Deep residual learning in modulation recognition of radar signals using higher-order spectral distribution[J]. Measurement, 2021, 185: 109945.
6 戴江安, 栾声扬, 赵明龙, 等. 脉冲噪声下基于平滑循环相关熵谱的调制识别方法[J]. 通信学报, 2021, 42(12): 121-133.
Dai Jiang-an, Luan Sheng-yang, Zhao Ming-long, et al. Pol-CCES based modulation recognition method under impulsive noise[J]. Journal on Communications, 2021, 42(12): 121-133.
7 Peng L, Fang S, Fan Y, et al. A method of noise reduction for radio communication signal based on RAGAN[J]. Sensors, 2023, 23(1): 23010475.
8 宋子豪, 程伟, 彭岑昕, 等. 基于CWD和残差收缩网络的调制方式识别方法[J]. 系统工程与电子技术, 2021, 43(11): 3371-3379.
Song Zi-hao, Cheng Wei, Peng Cen-xin, et al. Modulation recognition method based on CWD and residual shrinkage network[J]. Systems Engineering and Electronics, 2021, 43(11): 3371-3379.
9 杨洪娟, 时统志, 李博, 等. 基于联合特征参数的卫星单-混信号调制识别研究[J]. 电子与信息学报, 2022, 44(10): 3499-3506.
Yang Hong-juan, Shi Tong-zhi, Li Bo, et al. Research on satellite single-mixed signal modulation recognition based on joint feature parameters[J]. Journal of Electronics & Information Technology, 2022, 44(10): 3499-3506.
10 许华, 苟泽中, 蒋磊, 等. 适用于样本分布差异的迁移学习调制识别算法[J]. 华中科技大学学报: 自然科学版, 2021, 49(4): 127-132.
Xu Hua, Gou Ze-zhong, Jiang Lei, et al. Transfer learning modulation recognition algorithm for differences in sample distribution[J]. Journal of Huazhong University of Science and Technology (Nature Science Edition), 2021, 49(4): 127-132.
11 An Z L, Zhang T Q, Ma B Z, et al. A two-stage high-order modulation recognition based on projected accumulated constellation vector in non-cooperative B5G OSTBC-OFDM systems[J]. Signal Processing: The Official Publication of the European Association for Signal Processing (EURASIP), 2022, 200: 108673.
12 高敬鹏, 毛新蕊, 吴若无, 等. 混合滤波器优化的雷达信号调制识别算法[J]. 哈尔滨工程大学学报, 2022, 43(10): 1522-1531.
Gao Jing-peng, Mao Xin-rui, Wu Ruo-wu, et al. Modulation recognition of radar signals based on hybrid filter optimization[J]. Journal of Harbin Engineering University, 2022, 43(10): 1522-1531.
13 Chen J, Han B, Ma X, et al. Underwater target recognition based on multi-decision lofar spectrum enhancement: a deep-learning approach[J]. Future Internet, 2021, 13(10): 13100625.
14 王洋, 冯永新, 宋碧雪, 等. DP-DRCnet卷积神经网络信号调制识别算法[J]. 兵工学报, 2023, 44(2): 545-555.
Wang Yang, Feng Yong-xin, Song Bi-xue, et al. A modulation recognition algorithm of DP-DRCnet convolutional neural network[J]. Acta Armamentarii, 2023, 44(2): 545-555.
15 Gao J, Wang X, Wu R, et al. A new modulation recognition method based on flying fish swarm algorithm[J]. IEEE Access, 2021, 9: 76689-76706.
16 张笑宇, 冯永新, 钱博. 一种分数域数字信号调制方式识别方法[J]. 弹箭与制导学报, 2021, 41(1): 13-17.
Zhang Xiao-yu, Feng Yong-xin, Qian Bo. A modulation recognition method for digital signals in fractional domain[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2021, 41(1): 13-17.
17 董章华, 赵士杰, 赖莉. 一种基于Swin Transformer神经网络的低截获概率雷达信号调制类型的识别方法[J]. 四川大学学报: 自然科学版, 2023, 60(2): 42-48.
Dong Zhang-hua, Zhao Shi-jie, Lai Li. A radar signal modulation type recognition method based on Swin Transformer neural network[J]. Journal of Sichuan University (Natural Science Edition), 2023, 60(2): 42-48.
18 任庭瑞, 于笑楠, 佟首峰, 等. 基于数字信号处理的高灵敏度水下光通信发收机设计与评估[J]. 中国激光, 2022, 49(4): 107-116.
Ren Ting-rui, Yu Xiao-nan, Tong Shou-feng, et al. Design and evaluation of high-sensitivity underwater optical communication transceiver based on digital signal processing[J]. Chinese Journal of Lasers, 2022, 49(4): 107-116.
19 Chen K, Zhang J, Chen S, et al. Automatic modulation classification of radar signals utilizing X-net[J]. Digital Signal Processing, 2022, 123: 103396.
20 吴力华, 杨露菁, 袁园. 基于EEMD降噪和模糊函数奇异值向量的雷达辐射源信号识别算法[J]. 火力与指挥控制, 2022, 47(2): 121-126.
Wu Li-hua, Yang Lu-jing, Yuan Yuan. An identification algorithmfor radar emitter signals based on EEMD denoise and ambiguity function singular value vectors[J]. Fire Control & Command Control, 2022, 47(2): 121-126.
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