scholarly journals Multi-feature radar signal modulation recognition based on improved PSO algorithm

2019 ◽  
Vol 2019 (19) ◽  
pp. 5588-5592 ◽  
Author(s):  
Jing-Peng Gao ◽  
Liang-Xi Shen ◽  
Fang Ye ◽  
Shang-Yue Wang ◽  
Ran Zhang
Keyword(s):  
Pso Algorithm ◽  
Radar Signal ◽  
Modulation Recognition ◽  
Signal Modulation ◽  
Improved Pso

scholarly journals Radar Signal Modulation Recognition Based on Deep Joint Learning

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 48515-48528 ◽  
Author(s):  
Dongjin Li ◽  
Ruijuan Yang ◽  
Xiaobai Li ◽  
Shengkun Zhu
Keyword(s):  
Radar Signal ◽  
Modulation Recognition ◽  
Signal Modulation ◽  
Joint Learning

Self-Attention Bi-LSTM Networks for Radar Signal Modulation Recognition

2021 ◽  
pp. 1-1
Author(s):  
Shunjun Wei ◽  
Qizhe Qu ◽  
Xiangfeng Zeng ◽  
Jiadian Liang ◽  
Jun Shi ◽  
...  
Keyword(s):  
Radar Signal ◽  
Modulation Recognition ◽  
Signal Modulation

Knowledge acquisition based on improved PSO algorithm and entropy

2009 ◽  
Vol 29 (8) ◽  
pp. 2245-2249 ◽  
Author(s):  
Xiang XU ◽  
Dong-bo ZHANG ◽  
Hui-xian HUANG ◽  
Zi-wen LIU
Keyword(s):  
Knowledge Acquisition ◽  
Pso Algorithm ◽  
Improved Pso

Improved PSO algorithm based on cosine functions and its simulation

2013 ◽  
Vol 33 (2) ◽  
pp. 319-322
Author(s):  
Min ZHANG ◽  
Qiang HUANG ◽  
Zhouzhao XU ◽  
Baizhuang JIANG
Keyword(s):  
Pso Algorithm ◽  
Cosine Functions ◽  
Improved Pso

An IES Comprehensive Profit Model Based On Improved PSO Algorithm

2019 ◽  
Author(s):  
Chen Chen ◽  
Bingjie Li ◽  
Wei Zhang ◽  
Hongda Zhao ◽  
Ciwei Gao ◽  
...  
Keyword(s):  
Pso Algorithm ◽  
Profit Model ◽  
Model Based ◽  
Improved Pso

scholarly journals Estimating the Instantaneous Frequency of Linear and Nonlinear Frequency Modulated Radar Signals—A Comparative Study

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2840
Author(s):  
Hubert Milczarek ◽  
Czesław Leśnik ◽  
Igor Djurović ◽  
Adam Kawalec
Keyword(s):  
Instantaneous Frequency ◽  
Early Warning Systems ◽  
Vital Role ◽  
Estimation Methods ◽  
Radar Signal ◽  
Nonlinear Frequency ◽  
Modulation Recognition ◽  
Electronic Warfare ◽  
Time Frequency ◽  
Radar Signals

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.

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