| 引用本文: | 李春腾,蒋宇中,刘芳君,等.感应式磁性天线设计及干扰抑制算法研究.[J].国防科技大学学报,2019,41(5):147-152,158.[点击复制] |
| LI Chunteng,JIANG Yuzhong,LIU Fangjun,et al.Design of search coil magnetic antenna and research on interference suppression algorithm[J].Journal of National University of Defense Technology,2019,41(5):147-152,158[点击复制] |
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| 感应式磁性天线设计及干扰抑制算法研究 |
| 李春腾1, 蒋宇中1, 刘芳君2, 赵鹏1, 李松林3 |
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(1.海军工程大学 电子工程学院， 湖北 武汉 430033;2.云南民族大学 数学与计算机科学学院， 云南 昆明 650500;3.海军工程大学 电气工程学院， 湖北 武汉 430033)
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| 摘要: |
| 当期望信号和干扰同方向时，为了有效改善超低频频段的通信质量，提出了一种基于模拟电路预处理和改进广义旁瓣抵消的干扰抑制算法，设计了磁性天线、低噪声前置放大电路，制作了灵敏度较高的磁传感器，有效地抑制了工频及其谐波干扰。鉴于超低频频段的信号十分微弱，在广义旁瓣抵消算法的基础上做了几点改进，为主通道提供较多的参考信息，从而提高了算法的性能，有效地解决了传统算法失效的问题。为了验证所提算法的有效性，在实验室环境下搭建实验平台，设计了多组对照实验，实验结果表明：无论期望信号与干扰是否同方向，改进后的广义旁瓣抵消算法相比原来的算法，在信噪比的提升和噪声底限的降低等方面均有较大程度的改善。 |
| 关键词: 超低频通信 干扰抑制 模拟电路 磁传感器 广义旁瓣抵消 盲源分离 阻塞矩阵 |
| DOI：10.11887/j.cn.201905021 |
| 投稿日期：2018-05-21 |
| 基金项目:国家自然科学基金资助项目(41631072) |
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| Design of search coil magnetic antenna and research on interference suppression algorithm |
| LI Chunteng1, JIANG Yuzhong1, LIU Fangjun2, ZHAO Peng1, LI Songlin3 |
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(1.College of Electronic Engineering, Naval University of Engineering, Wuhan 430033, China;2.Academy of Mathematics and Computer Science, Yunnan Nationalities University, Kunming 650500, China;3.College of Electrical Engineering, Naval University of Engineering, Wuhan 430033, China)
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| Abstract: |
| When the desired signal and the interference are in the same direction, in order to improve the communication quality in the ELF (extremely-low-frequency) communication effectively, a kind of interference suppression algorithm based on analog circuits preprocessing and improved GSC (generalized sidelobe cancellation) algorithm was proposed. The magnetic antennas and preamplifier circuits with lower noise were designed, and the magnetic sensor with high sensitivity was produced, which can suppress 50Hz interference and its harmonic components effectively. In view of the weak desired signal in ELF communication, on the basis of the GSC algorithm, several improvements have been made to provide more reference information about interference for the main channel, which can improve the original GSC algorithm′s performance furtherly and address the problem of the traditional algorithm effectively. In order to validate the effectiveness of the proposed algorithm, an experimental platform was set up under the laboratory environment and multiple sets of controlled experiments were performed. Experimental results show that the improved GSC algorithm is better for the improvement of SNR and the noise floor, compared with the original GSC algorithm, regardless of whether the desired signal and the interference are in the same direction. |
| Keywords: extremely-low-frequency communication interference suppression analog circuit magnetic sensor generalized sidelobe cancellation blind source separation blocking matrix |
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