Recognition of Micro-Motion Jamming Based on Complex-Valued Convolutional Neural Network

被引：0
|
作者：
Shi, Chongwei [1 ]
Zhang, Qun [1 ]
Lin, Tao [1 ]
Liu, Zhidong [1 ]
Li, Shiliang [2 ]
机构：
[1] AF Engn Univ, Informat & Nav Sch, Xian 710077, Peoples R China
[2] AF Engn Univ, Equipment Management & Unmanned Aerial Vehicle Eng, Xian 710051, Peoples R China
来源：
SENSORS | 2023年 / 23卷 / 03期
基金：
中国国家自然科学基金;
关键词：
inverse synthetic aperture radar (ISAR); micro-motion jamming; recognition; complex-valued convolutional neural network (CV-CNN);
D O I：
10.3390/s23031118
中图分类号：
O65 [分析化学];
学科分类号：
070302 ; 081704 ;
摘要：
Micro-motion jamming is a new jamming method to inverse synthetic aperture radar (ISAR) in recent years. Compared with traditional jamming methods, it is more flexible and controllable, and is a great threat to ISAR. The prerequisite of taking relevant anti-jamming measures is to recognize the patterns of micro-motion jamming. In this paper, a method of micro-motion jamming pattern recognition based on complex-valued convolutional neural network (CV-CNN) is proposed. The micro-motion jamming echo signals are serialized and input to the network, and the result of recognition is output. Compared with real-valued convolutional neural network (RV-CNN), it can be found that the proposed method has a higher recognition accuracy rate. Additionally, the recognition accuracy rate is analyzed with different signal-to-noise ratio (SNR) and number of training samples. Simulation results prove the effectiveness of the proposed recognition method.
引用
收藏
页数：17
相关论文
共 50 条
  • [41] Redundancy of the parameters of the complex-valued neural network
    Nitta, T
    [J]. NEUROCOMPUTING, 2002, 49 : 423 - 428
  • [42] Network inversion for complex-valued neural networks
    Ogawa, T
    Kanada, H
    [J]. 2005 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), Vols 1 and 2, 2005, : 850 - 855
  • [43] The new complex-valued wavelet neural network
    Li, Sufang
    Jiang, Mingyan
    [J]. Telkomnika (Telecommunication Computing Electronics and Control), 2014, 12 (03) : 613 - 622
  • [44] On the critical points of the complex-valued neural network
    Nitta, T
    [J]. ICONIP'02: PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON NEURAL INFORMATION PROCESSING: COMPUTATIONAL INTELLIGENCE FOR THE E-AGE, 2002, : 1099 - 1103
  • [45] A modified complex-valued BP neural network
    [J]. Jiang, Mingyan, 1600, Binary Information Press (10):
  • [46] Gridless DOA Estimation Using Complex-Valued Convolutional Neural Network With Phasor Normalization
    Tan, Zhi-Wei
    Liu, Yuan
    Khong, Andy W. H.
    Nguyen, Anh H. T.
    [J]. IEEE SIGNAL PROCESSING LETTERS, 2023, 30 : 813 - 817
  • [47] The realization of quantum complex-valued backpropagation neural network in pattern recognition problem
    Mitrpanont, JL
    Srisuphab, A
    [J]. ICONIP'02: PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON NEURAL INFORMATION PROCESSING: COMPUTATIONAL INTELLIGENCE FOR THE E-AGE, 2002, : 462 - 466
  • [48] Complex-Valued Convolutional Neural Network and Its Application in Polarimetric SAR Image Classification
    Zhang, Zhimian
    Wang, Haipeng
    Xu, Feng
    Jin, Ya-Qiu
    [J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2017, 55 (12): : 7177 - 7188
  • [49] Complex-Valued 3-D Convolutional Neural Network for PolSAR Image Classification
    Tan, Xiaofeng
    Li, Ming
    Zhang, Peng
    Wu, Yan
    Song, Wanying
    [J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2020, 17 (06) : 1022 - 1026
  • [50] Robust Beamforming Based on Complex-Valued Convolutional Neural Networks for Sensor Arrays
    Mohammadzadeh, Saeed
    Nascimento, Vitor H.
    de Lamare, Rodrigo C.
    Hajarolasvadi, Noushin
    [J]. IEEE SIGNAL PROCESSING LETTERS, 2022, 29 : 2108 - 2112
12345