Frequency Estimation Algorithm of Frequency-hopping Signal Based on Image Processing and Time-frequency Analysis

WANG Xinyi; LIU Manguo; LI Keda; CHEN Ligong

doi:10.15892/j.cnki.djzdxb.2024.03.011

Journal of Projectiles, Rockets, Missiles and Guidance >

2024 , Vol. 44 >Issue 3: 81 - 86

DOI: https://doi.org/10.15892/j.cnki.djzdxb.2024.03.011

Frequency Estimation Algorithm of Frequency-hopping Signal Based on Image Processing and Time-frequency Analysis

WANG Xinyi ,
LIU Manguo ,
LI Keda ,
CHEN Ligong

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Xi’an Mordern Control Technology Research Institute,Xi’an 710065,Shaanxi,China

Received date: 2023-08-30

Online published: 2024-12-28

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Abstract

To solve the problem of frequency estimation of frequency-hopping signal in complex electromagnetic environment in the field of electronic reconnaissance, a frequency estimation algorithm based on time-frequency analysis is proposed in combination with image processing technology. Firstly, based on the differences in time-frequency characteristics between interference noise and frequency-hopping signals, Gaussian white noise and sweeping interference contained in time-frequency images are filtered out using BM3D and morphological filtering methods. Secondly, image processing methods such as grayscale, roberts edge detection and Hough transform are used to process the time-frequency distribution image of the signal to highlight the target information. Finally, the exact position of the time-frequency ridge line is located through pixel search and threshold processing to estimate the signal frequency. The simulation results show that the algorithm can preliminary estimate the signal frequency under the condition of signal-to-noise ratio≥-8 dB,can preliminary maintain the estimation mean square error within the range of 10^-5 under low signal-to-noise ratio conditions,. and can estimate the frequency of frequency hopping signals under low signal-to-noise ratio conditions.

Key words： electronic reconnaissance; frequency-hopping signal; frequency estimation; image processing; time-frequency analysis

Cite this article

WANG Xinyi , LIU Manguo , LI Keda , CHEN Ligong . Frequency Estimation Algorithm of Frequency-hopping Signal Based on Image Processing and Time-frequency Analysis[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2024 , 44(3) : 81 -86 . DOI: 10.15892/j.cnki.djzdxb.2024.03.011

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References

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[1]	米文辉, 潘子豪, 吴彬彬, 等. 非合作跳频信号的动态信道化接收方法研究[J]. 舰船电子对抗, 2022, 45(5): 36-43. MI W H, PAN Z H, WU B B, et al. Research into dynamic channelized receiving method of non-cooperative frequency hopping signals[J]. Shipboard Electronic Countermeasure, 2022, 45(5): 36-43.

[2]	刘铮, 冯永新, 钱博. 基于DQN的跳频信号干扰决策方法研究[J]. 沈阳理工大学学报, 2023, 42(3): 9-15. LIU Z, FENG Y X, QIAN B. Research on frequency hopping signal interference decision method based on DQN[J]. Journal of Shenyang Ligong University, 2023, 42(3): 9-15.

[3]	冯维婷, 梁青, 汪一楠. 一种跳频信号的时频分析和参数估计方法[J]. 西安邮电大学学报, 2021, 26(3): 32-39. FENG W T, LIANG Q, WANG Y N. A method for time-frequency analysis and parameters estimation of frequency-hopping signal[J]. Journal of Xi’an University of Posts and Telecommunications, 2021, 26(3): 32-39.

[4]	武开有, 徐以涛, 沈良. 基于Butterworth分布的跳频信号参数估计[J]. 军事通信技术, 2009, 30(1): 11-15. WU K Y, XU Y T, SHEN L. Parameter estimation of frequency-hopping signals based on butterworth distribution[J]. Journal of Military Communications Technology, 2009, 30(1): 11-15.

[5]	陈超, 郝雁中, 高宪军, 等. 基于WVD改进算法的跳频信号参数估计[J]. 吉林大学学报(信息科学版), 2010, 28(2): 124-130. CHEN C, HAO Y Z, GAO X J. Parameter estimation of frequency-hopping signals based on amelioration algorithm of WVD[J]. Journal of Jilin University(Information Science Edition), 2010, 28(2): 124-130.

[6]	冯涛, 袁超伟. 基于时频脊线的跳频参数盲估计[J]. 电子学报, 2011, 39(12): 2921-2925. FENG T, YUAN C W. Blind parameter estimation of frequency-hopping signals based on the time-frequency distribution maxima[J]. Acta Electronica Sinica, 2011, 39(12): 2921-2925.

[7]	李斌武, 李永贵, 张敬义. 基于过完备结构字典的跳频信号稀疏分解[J]. 通信技术, 2014, 47(5): 499-503. LI B W, LI Y G, ZHANG J Y. Over-complete structural dictionary based frequency-hopping signal sparse decomposition[J]. Communications Technology, 2014, 47(5): 499-503.

[8]	毕明雪, 王旭, 白帆, 等. 基于深度学习和时频分析的引信干扰信号识别研究[J]. 机械工程与自动化, 2021(6): 24-27. BI M X, WANG X, BAI F, et al. Research of fuze jamming signal recognition based on deep learning and time-frequency analysis[J]. Mechanical Engineering & Automation, 2021(6): 24-27.

[9]	朱倩倩. 非平稳信号的自适应时频分析算法研究[D]. 哈尔滨: 黑龙江大学, 2021. ZHU Q Q. Research on adaptive time-frequency analysis algorithms for non-stationary signals[D]. Harbin:Heilongjiang University, 2021.

[10]	徐华平. 基于仿射不变相似度量的BM3D算法研究[D]. 长春: 长春理工大学, 2022. XU H P. BM3D image denoising algorithm based on affine invariant patch similarity measure[D]. Changchun: Changchun University of Science and Technology, 2022.

[11]	王志欣, 张锦灿, 唐立赫. 基于形态滤波的水声通信信号同步检测方法[J]. 数字海洋与水下攻防, 2022, 5(4): 301-306. WANG Z X, ZHANG J C, TANG L H. Synchronous detection method of underwater acoustic communication signal based on morphological filtering[J]. Digital Ocean & Underwater Warfare, 2022, 5(4): 301-306.

[12]	高天姿. 基于深度卷积神经网络的接触网异物与缺陷检测算法研究[D]. 南昌: 华东交通大学, 2022. GAO T Z. Research on foreign object and defect detection algorithm of overhead catenary system based on deep convolution neural network[D]. Nanchang: East China Jiaotong University, 2022.

[13]	李晓军. 基于FPGA的实时图像边缘检测系统设计及实现[D]. 广州: 广东工业大学, 2022. LI X J. Design and implementation of real-time image edge detection system based on FPGA[D]. Guangzhou: Guangdong University of Technology, 2022.

[14]	谢永辉. 基于深度学习的激光图像边缘检测技术研究[D]. 绵阳: 中国工程物理研究院, 2018. XIE Y H. Research on laser image edge detection technology based on deep learning[D]. Mianyang: China Academy of Engineering Physics, 2018.

[15]	张放, 徐磊. 低信噪比条件下雷达对高速运动目标的检测方法[J]. 舰船电子对抗, 2022, 45(2): 57-61. ZHANG F, XU L. Test method of radar to moving targets with high speed under low snr condition[J]. Shipboard Electronic Countermeasure, 2022, 45(2): 57-61.

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