DL-based PRI modulation classification and recognition
This report presents a comprehensive investigation into the application of Deep Learning (DL) techniques for the classification and recognition of Pulse Repetition Interval (PRI) modulated signals, with a focus on radar and communication systems. The research involves the signal data simulation,...
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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2023
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/172489 |
| _version_ | 1826127263752519680 |
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| author | Tey, Kai Hong |
| author2 | Teh Kah Chan |
| author_facet | Teh Kah Chan Tey, Kai Hong |
| author_sort | Tey, Kai Hong |
| collection | NTU |
| description | This report presents a comprehensive investigation into the application of Deep
Learning (DL) techniques for the classification and recognition of Pulse Repetition
Interval (PRI) modulated signals, with a focus on radar and communication systems.
The research involves the signal data simulation, network model implementation,
and comparison of Convolutional Neural Networks (CNNs) and Recurrent Neural
Networks (RNNs) for the automatic detection and classification of diverse PRI
modulation techniques across various environmental conditions and interference
scenarios. Our findings demonstrate the superiority of DL-based methods over
traditional signal processing approaches, shedding light on their interpretability and
real-world applicability. In this study, enhancements targeting loss function, network
architecture refinement, and the integration of advanced signal processing techniques
were proposed, collectively leading to notable performance improvements in the
classification and recognition of PRI-modulated signals.
Keywords: PRI modulation, Deep Learning, Data Signal Simulation, Convolutional
Neural Networks (CNNs), Squeeze-and-Excitation Networks, Focal Loss. |
| first_indexed | 2024-10-01T07:06:02Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/172489 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:06:02Z |
| publishDate | 2023 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1724892023-12-15T15:43:39Z DL-based PRI modulation classification and recognition Tey, Kai Hong Teh Kah Chan School of Electrical and Electronic Engineering EKCTeh@ntu.edu.sg Engineering::Electrical and electronic engineering This report presents a comprehensive investigation into the application of Deep Learning (DL) techniques for the classification and recognition of Pulse Repetition Interval (PRI) modulated signals, with a focus on radar and communication systems. The research involves the signal data simulation, network model implementation, and comparison of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) for the automatic detection and classification of diverse PRI modulation techniques across various environmental conditions and interference scenarios. Our findings demonstrate the superiority of DL-based methods over traditional signal processing approaches, shedding light on their interpretability and real-world applicability. In this study, enhancements targeting loss function, network architecture refinement, and the integration of advanced signal processing techniques were proposed, collectively leading to notable performance improvements in the classification and recognition of PRI-modulated signals. Keywords: PRI modulation, Deep Learning, Data Signal Simulation, Convolutional Neural Networks (CNNs), Squeeze-and-Excitation Networks, Focal Loss. Bachelor of Engineering (Electrical and Electronic Engineering) 2023-12-13T05:37:52Z 2023-12-13T05:37:52Z 2023 Final Year Project (FYP) Tey, K. H. (2023). DL-based PRI modulation classification and recognition. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/172489 https://hdl.handle.net/10356/172489 en application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Electrical and electronic engineering Tey, Kai Hong DL-based PRI modulation classification and recognition |
| title | DL-based PRI modulation classification and recognition |
| title_full | DL-based PRI modulation classification and recognition |
| title_fullStr | DL-based PRI modulation classification and recognition |
| title_full_unstemmed | DL-based PRI modulation classification and recognition |
| title_short | DL-based PRI modulation classification and recognition |
| title_sort | dl based pri modulation classification and recognition |
| topic | Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/172489 |
| work_keys_str_mv | AT teykaihong dlbasedprimodulationclassificationandrecognition |