Abstract
The narrow-band anti-jamming technology of satellite signals is mainly studied, and a piecewise adaptive threshold algorithm is proposed in this paper. The general steps of the adaptive threshold algorithm are given and analyzed. The traditional algorithm is improved, the spectral segmentation is proposed, and the second threshold is obtained. This algorithm is suitable for narrow-band anti-interference and can effectively suppress narrow-band interference signals. A comparative simulation was performed on MATLAB.
Original language | English |
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Title of host publication | Proceedings of the 2019 4th International Conference on Robotics, Control and Automation, ICRCA 2019 - Workshop 2019 the 4th International Conference on Robotics and Machine Vision, ICRMV 2019 |
Publisher | Association for Computing Machinery |
Pages | 163-167 |
Number of pages | 5 |
ISBN (Electronic) | 9781450371834 |
DOIs | |
Publication status | Published - 26 Jul 2019 |
Event | 2019 4th International Conference on Robotics, Control and Automation, ICRCA 2019 and its Workshop of 2019 4th International Conference on Robotics and Machine Vision, ICRMV 2019 - Guangzhou, China Duration: 26 Jul 2019 → 28 Jul 2019 |
Publication series
Name | ACM International Conference Proceeding Series |
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Conference
Conference | 2019 4th International Conference on Robotics, Control and Automation, ICRCA 2019 and its Workshop of 2019 4th International Conference on Robotics and Machine Vision, ICRMV 2019 |
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Country/Territory | China |
City | Guangzhou |
Period | 26/07/19 → 28/07/19 |
Keywords
- FFT
- Gaussian distribution
- MATLAB
- Narrow-band anti-jamming
- Segment adaptive threshold
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Qi, Z., Chuanjun, L., & Fei, H. (2019). Research on narrow-band anti-jamming algorithm for satellite signals. In Proceedings of the 2019 4th International Conference on Robotics, Control and Automation, ICRCA 2019 - Workshop 2019 the 4th International Conference on Robotics and Machine Vision, ICRMV 2019 (pp. 163-167). (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3351180.3351218