Fast blind detection of short-wave frequency hopping signal based on MeanShift
In the complex short-wave channel environment, combined with time-frequency analysis technology, a fast blind detection algorithm of the connected domain labeled frequency hopping signals based on MeanShift algorithm was proposed to reduce the influence of various interference signals and noises on...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2022-06-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2022118/ |
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| _version_ | 1841539215742992384 |
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| author | Zhengyu ZHU Yu LIN Zixuan WANG Kexian GONG Pengfei CHEN Zhongyong WANG Jing LIANG |
| author_facet | Zhengyu ZHU Yu LIN Zixuan WANG Kexian GONG Pengfei CHEN Zhongyong WANG Jing LIANG |
| author_sort | Zhengyu ZHU |
| collection | DOAJ |
| description | In the complex short-wave channel environment, combined with time-frequency analysis technology, a fast blind detection algorithm of the connected domain labeled frequency hopping signals based on MeanShift algorithm was proposed to reduce the influence of various interference signals and noises on frequency hopping signals and realize blind detection of frequency hopping signals under low signal-to-noise ratio.Firstly, the channel environment gray-scale time-frequency map was filtered by the secondary gray-scale morphology to obtain the binary time-frequency map.Secondly, the maximum duration of the signal was calculated by the connected domain labeling algorithm.Then, the MeanShift algorithm was used to cluster the maximum duration of the signal.Finally, the clustering result was made a second judgment by combining with the adaptive double threshold.The simulation results show that the proposed algorithm can quickly separate various interference signals and sharp noise under low signal-to-noise ratio, and realize fast blind detection of frequency hopping signals without any prior information.It has high detection probability, strong anti-interference ability in short-wave channel environment, low computational complexity and high engineering practical value. |
| format | Article |
| id | doaj-art-935b9f703a014ff2a718c29e8e54c9bf |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2022-06-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-935b9f703a014ff2a718c29e8e54c9bf2025-01-14T07:23:46ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2022-06-014320021059837143Fast blind detection of short-wave frequency hopping signal based on MeanShiftZhengyu ZHUYu LINZixuan WANGKexian GONGPengfei CHENZhongyong WANGJing LIANGIn the complex short-wave channel environment, combined with time-frequency analysis technology, a fast blind detection algorithm of the connected domain labeled frequency hopping signals based on MeanShift algorithm was proposed to reduce the influence of various interference signals and noises on frequency hopping signals and realize blind detection of frequency hopping signals under low signal-to-noise ratio.Firstly, the channel environment gray-scale time-frequency map was filtered by the secondary gray-scale morphology to obtain the binary time-frequency map.Secondly, the maximum duration of the signal was calculated by the connected domain labeling algorithm.Then, the MeanShift algorithm was used to cluster the maximum duration of the signal.Finally, the clustering result was made a second judgment by combining with the adaptive double threshold.The simulation results show that the proposed algorithm can quickly separate various interference signals and sharp noise under low signal-to-noise ratio, and realize fast blind detection of frequency hopping signals without any prior information.It has high detection probability, strong anti-interference ability in short-wave channel environment, low computational complexity and high engineering practical value.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2022118/connected domain labelingfrequency hopping signalfast blind detectionMeanShifttime-frequency analysis |
| spellingShingle | Zhengyu ZHU Yu LIN Zixuan WANG Kexian GONG Pengfei CHEN Zhongyong WANG Jing LIANG Fast blind detection of short-wave frequency hopping signal based on MeanShift Tongxin xuebao connected domain labeling frequency hopping signal fast blind detection MeanShift time-frequency analysis |
| title | Fast blind detection of short-wave frequency hopping signal based on MeanShift |
| title_full | Fast blind detection of short-wave frequency hopping signal based on MeanShift |
| title_fullStr | Fast blind detection of short-wave frequency hopping signal based on MeanShift |
| title_full_unstemmed | Fast blind detection of short-wave frequency hopping signal based on MeanShift |
| title_short | Fast blind detection of short-wave frequency hopping signal based on MeanShift |
| title_sort | fast blind detection of short wave frequency hopping signal based on meanshift |
| topic | connected domain labeling frequency hopping signal fast blind detection MeanShift time-frequency analysis |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2022118/ |
| work_keys_str_mv | AT zhengyuzhu fastblinddetectionofshortwavefrequencyhoppingsignalbasedonmeanshift AT yulin fastblinddetectionofshortwavefrequencyhoppingsignalbasedonmeanshift AT zixuanwang fastblinddetectionofshortwavefrequencyhoppingsignalbasedonmeanshift AT kexiangong fastblinddetectionofshortwavefrequencyhoppingsignalbasedonmeanshift AT pengfeichen fastblinddetectionofshortwavefrequencyhoppingsignalbasedonmeanshift AT zhongyongwang fastblinddetectionofshortwavefrequencyhoppingsignalbasedonmeanshift AT jingliang fastblinddetectionofshortwavefrequencyhoppingsignalbasedonmeanshift |