| Tian Yanan,Han Xiao,Yin Jingwei,Chen Hongxia,Liu Qingyu.An improved least mean square/fourth direct adaptive equalizer for under-water acoustic communications in the Arctic[J].Acta Oceanologica Sinica,2020,39(9):133-139 |
| 北极冰下水声通信中改进的最小均方/四次方直接自适应均衡器 |
| An improved least mean square/fourth direct adaptive equalizer for under-water acoustic communications in the Arctic |
| 投稿时间：2019-10-13 |
| DOI：10.1007/s13131-020-1653-6 |
| 中文关键词: 水声通信 北极 直接自适应均衡器 自适应范数 |
| 英文关键词:underwater acoustic communication the Arctic direct adaptive equalizer adaptive norm |
| 基金项目:The National Natural Science Foundation of China under contract Nos 61631008 and 61901136; the National Key Research and Development Program of China under contract No. 2018YFC1405904; the Fok Ying-Tong Education Foundation under contract No. 151007; the Heilongjiang Province Outstanding Youth Science Fund under contract No. JC2017017; the Opening Funding of Science and Technology on Sonar Laboratory under contract No. 6142109KF201802; the Innovation Special Zone of National Defense Science and Technology. |
| 作者 | 单位 | E-mail | | 田亚男 | 哈尔滨工程大学水声技术重点实验室, 哈尔滨, 150001
海洋信息获取与安全工信部重点实验室(哈尔滨工程大学), 工业和信息化部, 哈尔滨, 150001
哈尔滨工程大学 水声工程学院, 哈尔滨, 150001 | | | 韩笑 | 哈尔滨工程大学水声技术重点实验室, 哈尔滨, 150001
海洋信息获取与安全工信部重点实验室(哈尔滨工程大学), 工业和信息化部, 哈尔滨, 150001
哈尔滨工程大学 水声工程学院, 哈尔滨, 150001 | hanxiao1322@hrbeu.edu.cn | | 殷敬伟 | 哈尔滨工程大学水声技术重点实验室, 哈尔滨, 150001
海洋信息获取与安全工信部重点实验室(哈尔滨工程大学), 工业和信息化部, 哈尔滨, 150001
哈尔滨工程大学 水声工程学院, 哈尔滨, 150001 | | | 陈红霞 | 自然资源部第一海洋研究所, 青岛, 266061 | | | 刘清宇 | 海军研究院, 北京, 100161 | |
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| 中文摘要: |
| 本文提出了一种适用于北极冰下水声通信的最小均方/四次方直接自适应均衡器（LMS/F-DAE）。它能处理基带复信号，与LMS相比，具有更好的均衡效果。考虑到均衡器的稀疏特性，在其代价函数中加入自适应范数（AN）作为约束。它能根据均衡器系数的大小自适应变化：对于小系数，此约束项存在以加快收敛速度；对于大系数，此约束项不存在以减小均衡误差。利用第九次中国北极科学考察得到的实验数据验证AN-LMS/F-DAE的性能。结果表明，与传统的LMS/F-DAE相比，AN-LMS/F-DAE能提升均衡器的稀疏性且均衡性能更优。 |
| 英文摘要: |
| An improved least mean square/fourth direct adaptive equalizer (LMS/F-DAE) is proposed in this paper for underwater acoustic communication in the Arctic. It is able to process complex-valued baseband signals and has better equalization performance than LMS. Considering the sparsity feature of equalizer tap coefficients, an adaptive norm (AN) is incorporated into the cost function which is utilized as a sparse regularization. The norm constraint changes adaptively according to the amplitude of each coefficient. For small-scale coefficients, the sparse constraint exists to accelerate the convergence speed. For large-scale coefficients, it disappears to ensure smaller equalization error. The performance of the proposed AN-LMS/F-DAE is verified by the experimental data from the 9th Chinese National Arctic Research Expedition. The results show that compared with the standard LMS/F-DAE, AN-LMS/F-DAE can promote the sparse level of the equalizer and achieve better performance. |
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