| 改进的时序多重稀疏贝叶斯学习冰下水声信道估计方法 |
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| 引用本文： | 洪丹阳,王巍,尹力,普湛清,周成阳,黄海宁.改进的时序多重稀疏贝叶斯学习冰下水声信道估计方法[J].声学学报,2022,47(5):591-602. |
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| 作者姓名： | 洪丹阳 王巍 尹力 普湛清 周成阳 黄海宁 |
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| 作者单位： | 1. 中国科学院声学研究所 北京 100190; |
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| 基金项目： | 国家重点研发计划项目(2018YFC1405904)资助 |
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| 摘 要： | 针对时序多重稀疏贝叶斯学习信道估计方法计算复杂度高且在低信噪比时估计精度低的问题,本文提出了一种改进的时序多重稀疏贝叶斯学习正交频分复用冰下水声信道估计方法。首先,采用奇异值分解方法对接收导频矩阵进行去噪;随后利用去噪后的接收导频矩阵结合最小二乘信道估计方法获得时序多重稀疏贝叶斯信道估计的超参数矩阵、感知矩阵等先验知识;最后,利用冰下水声信道的稀疏特性和多途结构较为稳定的特点,采用时序多重稀疏贝叶斯信道估计对不同符号的冰下水声信道进行联合重建。仿真结果显示,在能量系数为0.03时,改进方法信道估计均方误差相比较于原始方法至少降低了约2.87×10-5,运算时间至少下降了约为90%。第11次北极科学考察冰下试验结果显示,改进方法的平均原始误码率略微低于原始方法,平均运算时间降低约75%。研究结果表明,利用冰下水声信道的特点,改进方法可以实现高精度冰下水声信道估计,并且有效降低系统计算复杂度。
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| 关 键 词： | 冰下水声信道特性 稀疏贝叶斯学习 冰下水声通信 TMSBL信道估计 |
| 收稿时间： | 2021-03-19 |
An improved temporal multiple sparse Bayesian learning under-ice acoustic channel estimation method |
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| Affiliation: | 1. Institute of Acoustics, Chinese Academy of Sciences Beijing 100190;2. University of Chinese Academy of Sciences Beijing 100049;3. Key Laboratory of Science and Technology on Advanced Underwater Acoustic Signal Processing, Chinese Academy of Sciences Beijing 100190 |
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| Abstract: | In order to solve the problem of high computational complexity and low estimation accuracy of the Temporal Multiple Sparse Bayesian Learning（TMSBL） channel estimation method at low signal-to-noise ratio,an improved TMSBL under-iceacoustic channel estimation method for Orthogonal Frequency Division Multiplexing（OFDM） is proposed.Firstly,the Singular Value Decomposition（SVD） is used to denoise the receiving pilot matrix.Then,combining with the Least Square（LS） channel estimation method and the denoised receiving pilot matrix,we obtain the prior knowledge of the TMSBL channel estimation method.Finally,by using the sparse characteristic and the stable multipath structure characteristic of under-ice acoustic channel,the TMSBL channel estimation method is used to jointly reconstruct the under-ice acoustic channels with different symbols.The simulation results show that when the energy coefficient is 0.03,compared with TMSBL,the mean squared error of the channel estimation of the improved method is reduced by at least about 2.87 × 10-5,and the operation time is reduced by at least 20 s.The under-ice communication experimental results of the 11th Arctic expedition show that the average origin bit error rate of the improved method is slightly lower than that of TMSBL,and the average operation time is reduced about 25 s.The research results demonstrate that the improved method can achieve high precision under-ice acoustic channel estimation and effectively reduce the computational complexity of the system by using the characteristics of under-ice acoustic channel. |
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