A New Radar Signal Modulation Recognition Algorithm Based on Time-frequency Transform

Author(s):  
Jinliang Bai ◽  
Lu Gao ◽  
Jingpeng Gao ◽  
Hu Li ◽  
Ran Zhang ◽  
...  
Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2840
Author(s):  
Hubert Milczarek ◽  
Czesław Leśnik ◽  
Igor Djurović ◽  
Adam Kawalec

Automatic modulation recognition plays a vital role in electronic warfare. Modern electronic intelligence and electronic support measures systems are able to automatically distinguish the modulation type of an intercepted radar signal by means of real-time intra-pulse analysis. This extra information can facilitate deinterleaving process as well as be utilized in early warning systems or give better insight into the performance of hostile radars. Existing modulation recognition algorithms usually extract signal features from one of the rudimentary waveform characteristics, namely instantaneous frequency (IF). Currently, there are a small number of studies concerning IF estimation methods, specifically for radar signals, whereas estimator accuracy may adversely affect the performance of the whole classification process. In this paper, five popular methods of evaluating the IF–law of frequency modulated radar signals are compared. The considered algorithms incorporate the two most prevalent estimation techniques, i.e., phase finite differences and time-frequency representations. The novel approach based on the generalized quasi-maximum likelihood (QML) method is also proposed. The results of simulation experiments show that the proposed QML estimator is significantly more accurate than the other considered techniques. Furthermore, for the first time in the publicly available literature, multipath influence on IF estimates has been investigated.


2019 ◽  
Vol 2019 (19) ◽  
pp. 5588-5592 ◽  
Author(s):  
Jing-Peng Gao ◽  
Liang-Xi Shen ◽  
Fang Ye ◽  
Shang-Yue Wang ◽  
Ran Zhang

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 48515-48528 ◽  
Author(s):  
Dongjin Li ◽  
Ruijuan Yang ◽  
Xiaobai Li ◽  
Shengkun Zhu

2021 ◽  
Vol 2050 (1) ◽  
pp. 012009
Author(s):  
Fan Wang ◽  
Yifeng Huang ◽  
Ming Zhu ◽  
Jun Tang ◽  
Zhaohong Jia

Abstract For purpose of solve the problem of poor discrimination and robustness of intra-pulse signal features extracted by the traditional methods, this paper proposes a radar signal intra-pulse modulation type recognition algorithm based on the improved residual network. Firstly, one-dimensional time-domain radar signal is converted into two-dimensional time-frequency image by Smoothing Pseudo Wigner-Ville Distribution; Then the time-frequency image is preprocessed; ResNet-50 network is chosen as the framework. In order to retain the feature map information as much as possible, the convolution kernel is increased in the residual module. The cross entropy loss function and the center loss function are used as the loss function to speed up the convergence of the network. The improved residual network is used to realize the intra-pulse modulation type recognition of radar signal. The simulation experiments show that when the SNR is -14dB, the overall average recognition accuracy of the improved algorithm for eight kinds of radar signals (CM, LFM, NLFM, BLFM, BPSK, QPSK, OPSK, LFM+BPSK) can reach 97.29%, which shows the effectiveness.


Author(s):  
Shunjun Wei ◽  
Qizhe Qu ◽  
Xiangfeng Zeng ◽  
Jiadian Liang ◽  
Jun Shi ◽  
...  

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