Ultrashort wave satellite channel classification and recognition algorithm based on mirror filled spectrum and LA-ResNet50
In response to the classification and identification problems of 5 kHz channels, 25 kHz channels, broadband interference channels, narrowband interference channels, and single tone interference channels in the ultrashort wave frequency band, a classification and identification method for ultrashort...
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| Format: | Article |
| Language: | zho |
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Beijing Xintong Media Co., Ltd
2023-10-01
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| Series: | Dianxin kexue |
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| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2023185/ |
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| _version_ | 1841530882086666240 |
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| author | Shang WU Lei SHEN Lijun WANG Ruxu ZHANG Xin HU |
| author_facet | Shang WU Lei SHEN Lijun WANG Ruxu ZHANG Xin HU |
| author_sort | Shang WU |
| collection | DOAJ |
| description | In response to the classification and identification problems of 5 kHz channels, 25 kHz channels, broadband interference channels, narrowband interference channels, and single tone interference channels in the ultrashort wave frequency band, a classification and identification method for ultrashort wave channels based on mirror filled spectrum and LA-ResNet50 (LBP attention ResNet50) was proposed.The problem of difficulty in distinguishing between satellite channels and background noise under low signal-to-noise ratio, as well as the identification of signal channels and interference channels with similar characteristics, has been effectively solved.Firstly, the proposed method performs mirror symmetry on the ultrashort wave spectrum and fills it in, while blackening the edges of the spectrum to construct a mirror-filled spectrum, which improves the discrimination of different types of channel spectra.Then, channel attention was introduced into ResNet50 to focus the attention of the network model on the channel.Finally, a loss function based on cross entropy and local binary pattern (LBP) was proposed to improve the extraction effect of subtle texture features on signal channels and interference channels images.The proposed method based on mirror-filled spectrum and LA-ResNet50 has shown an improvement of 19.8%, 8.2%, 1.8%, and 0.8% in classification accuracy for ultrashort wave channels compared to the traditional method utilizing fast Fourier transform (FFT) spectrum thresholding, the YOLOv5s target detection and classification method based on mirror-filled spectrum, the Attention-ResNet50 method with attention mechanism based on mirror-filled spectrum, and the Transformer network method under a signal-to-noise ratio (SNR) of 10 dB. |
| format | Article |
| id | doaj-art-049b842bb5424093a298f98e84779e0d |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2023-10-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-049b842bb5424093a298f98e84779e0d2025-01-15T02:58:03ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012023-10-0139748459560135Ultrashort wave satellite channel classification and recognition algorithm based on mirror filled spectrum and LA-ResNet50Shang WULei SHENLijun WANGRuxu ZHANGXin HUIn response to the classification and identification problems of 5 kHz channels, 25 kHz channels, broadband interference channels, narrowband interference channels, and single tone interference channels in the ultrashort wave frequency band, a classification and identification method for ultrashort wave channels based on mirror filled spectrum and LA-ResNet50 (LBP attention ResNet50) was proposed.The problem of difficulty in distinguishing between satellite channels and background noise under low signal-to-noise ratio, as well as the identification of signal channels and interference channels with similar characteristics, has been effectively solved.Firstly, the proposed method performs mirror symmetry on the ultrashort wave spectrum and fills it in, while blackening the edges of the spectrum to construct a mirror-filled spectrum, which improves the discrimination of different types of channel spectra.Then, channel attention was introduced into ResNet50 to focus the attention of the network model on the channel.Finally, a loss function based on cross entropy and local binary pattern (LBP) was proposed to improve the extraction effect of subtle texture features on signal channels and interference channels images.The proposed method based on mirror-filled spectrum and LA-ResNet50 has shown an improvement of 19.8%, 8.2%, 1.8%, and 0.8% in classification accuracy for ultrashort wave channels compared to the traditional method utilizing fast Fourier transform (FFT) spectrum thresholding, the YOLOv5s target detection and classification method based on mirror-filled spectrum, the Attention-ResNet50 method with attention mechanism based on mirror-filled spectrum, and the Transformer network method under a signal-to-noise ratio (SNR) of 10 dB.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2023185/ultrashort wave channelattention mechanismclassification and identificationResNet50 |
| spellingShingle | Shang WU Lei SHEN Lijun WANG Ruxu ZHANG Xin HU Ultrashort wave satellite channel classification and recognition algorithm based on mirror filled spectrum and LA-ResNet50 Dianxin kexue ultrashort wave channel attention mechanism classification and identification ResNet50 |
| title | Ultrashort wave satellite channel classification and recognition algorithm based on mirror filled spectrum and LA-ResNet50 |
| title_full | Ultrashort wave satellite channel classification and recognition algorithm based on mirror filled spectrum and LA-ResNet50 |
| title_fullStr | Ultrashort wave satellite channel classification and recognition algorithm based on mirror filled spectrum and LA-ResNet50 |
| title_full_unstemmed | Ultrashort wave satellite channel classification and recognition algorithm based on mirror filled spectrum and LA-ResNet50 |
| title_short | Ultrashort wave satellite channel classification and recognition algorithm based on mirror filled spectrum and LA-ResNet50 |
| title_sort | ultrashort wave satellite channel classification and recognition algorithm based on mirror filled spectrum and la resnet50 |
| topic | ultrashort wave channel attention mechanism classification and identification ResNet50 |
| url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2023185/ |
| work_keys_str_mv | AT shangwu ultrashortwavesatellitechannelclassificationandrecognitionalgorithmbasedonmirrorfilledspectrumandlaresnet50 AT leishen ultrashortwavesatellitechannelclassificationandrecognitionalgorithmbasedonmirrorfilledspectrumandlaresnet50 AT lijunwang ultrashortwavesatellitechannelclassificationandrecognitionalgorithmbasedonmirrorfilledspectrumandlaresnet50 AT ruxuzhang ultrashortwavesatellitechannelclassificationandrecognitionalgorithmbasedonmirrorfilledspectrumandlaresnet50 AT xinhu ultrashortwavesatellitechannelclassificationandrecognitionalgorithmbasedonmirrorfilledspectrumandlaresnet50 |