Machine Learning For Modulation Classification Of Radar Signals: A Survey
Automatic modulation recognition of radar waveform is a major topic and has many military applications. This paper surveys the models and the techniques used in recognizing different modulation types of intercepted radar waveform. The literature shows the outstanding performance of deep learning ne...
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| Format: | Article |
| Language: | English |
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Shaheed Zulfikar Ali Bhutto Institute of Science and Technology
2019-12-01
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| Series: | JISR on Computing |
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| Online Access: | https://jisrc.szabist.edu.pk/ojs/index.php/jisrc/article/view/78 |
| _version_ | 1797742123058987008 |
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| author | Hitham Alshoubaki |
| author_facet | Hitham Alshoubaki |
| author_sort | Hitham Alshoubaki |
| collection | DOAJ |
| description |
Automatic modulation recognition of radar waveform is a major topic and has many military applications. This paper surveys the models and the techniques used in recognizing different modulation types of intercepted radar waveform. The literature shows the outstanding performance of deep learning neural network at low SNR values and in signal[1]overlapped environments as well. Additionally, using different mathematical and statistical algorithms demonstrated that utilized in features extraction of the data in order to feed them into the neural network improves the performance significantly. However, reducing computation complexity is in development too.
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| first_indexed | 2024-03-12T14:36:26Z |
| format | Article |
| id | doaj.art-a61651a2dc0241b1b990859e938c6b31 |
| institution | Directory Open Access Journal |
| issn | 2412-0448 1998-4154 |
| language | English |
| last_indexed | 2024-03-12T14:36:26Z |
| publishDate | 2019-12-01 |
| publisher | Shaheed Zulfikar Ali Bhutto Institute of Science and Technology |
| record_format | Article |
| series | JISR on Computing |
| spelling | doaj.art-a61651a2dc0241b1b990859e938c6b312023-08-17T06:44:58ZengShaheed Zulfikar Ali Bhutto Institute of Science and TechnologyJISR on Computing2412-04481998-41542019-12-0117210.31645/17Machine Learning For Modulation Classification Of Radar Signals: A SurveyHitham Alshoubaki0Department Of Electrical And Computer Engineering Bachelor Of Engineering, King Abdulaziz University, Jeddah, Saudi Arabia Automatic modulation recognition of radar waveform is a major topic and has many military applications. This paper surveys the models and the techniques used in recognizing different modulation types of intercepted radar waveform. The literature shows the outstanding performance of deep learning neural network at low SNR values and in signal[1]overlapped environments as well. Additionally, using different mathematical and statistical algorithms demonstrated that utilized in features extraction of the data in order to feed them into the neural network improves the performance significantly. However, reducing computation complexity is in development too. https://jisrc.szabist.edu.pk/ojs/index.php/jisrc/article/view/78Modulation classification |
| spellingShingle | Hitham Alshoubaki Machine Learning For Modulation Classification Of Radar Signals: A Survey JISR on Computing Modulation classification |
| title | Machine Learning For Modulation Classification Of Radar Signals: A Survey |
| title_full | Machine Learning For Modulation Classification Of Radar Signals: A Survey |
| title_fullStr | Machine Learning For Modulation Classification Of Radar Signals: A Survey |
| title_full_unstemmed | Machine Learning For Modulation Classification Of Radar Signals: A Survey |
| title_short | Machine Learning For Modulation Classification Of Radar Signals: A Survey |
| title_sort | machine learning for modulation classification of radar signals a survey |
| topic | Modulation classification |
| url | https://jisrc.szabist.edu.pk/ojs/index.php/jisrc/article/view/78 |
| work_keys_str_mv | AT hithamalshoubaki machinelearningformodulationclassificationofradarsignalsasurvey |