| 认知型水声通信时空自适应处理算法研究 |
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| 引用本文： | 王峰,周易,龚道银.认知型水声通信时空自适应处理算法研究[J].声学技术,2019,38(1):91-96. |
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| 作者姓名： | 王峰 周易 龚道银 |
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| 作者单位： | 河海大学计算机与信息学院阵列与信息处理实验室;厦门大学水声通信与海洋信息技术教育部重点实验室 |
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| 基金项目： | 水声通信与海洋信息技术教育部重点实验室开放基金资助（厦门大学）（201703）；江苏省自然科学基金资助项目（BK20151501）；中央高校基本科研业务费专项资助项目（2015B03014） |
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| 摘 要： | 针对浅海水声通信面临的复杂干扰环境,提出了一种适用于水声通信系统的认知型时空自适应处理算法。该算法在传统时空自适应阵列处理算法的基础上引入了干扰认知的功能,通过干扰认知处理降低计算量,并且实现干扰样本的选取,确保自适应算法的可靠收敛。利用了协方差矩阵特征分解和多重信号分类(Multiple Signal Classification, MUSIC)估计干扰的个数,辅助选取盲源分离算法中的维度和时空自适应算法中的空域维度,进行算法降维处理。针对采用盲源分离后的各干扰,采用包络检测法提取时域特征,采用短时傅里叶变换(Short-time Fourier Transform, STFT)方法提取时频谱特征,分析干扰特征,实现干扰分类,从而实现干扰样本的选取。通过计算机仿真验证了该认知处理算法的性能。
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| 关 键 词： | 认知水声通信 时空自适应处理 特征提取 |
| 收稿时间： | 2018/5/4 0:00:00 |
| 修稿时间： | 2018/7/18 0:00:00 |
Space-time adaptive processing with cognitive capability for underwater acoustic communication systems |
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| WANG Feng,ZHOU Yi and GONG Dao-yin.Space-time adaptive processing with cognitive capability for underwater acoustic communication systems[J].Technical Acoustics,2019,38(1):91-96. |
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| Authors: | WANG Feng ZHOU Yi and GONG Dao-yin |
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| Affiliation: | Array and Information Processing Laboratory, College of Computer and Information, Hohai University, Nanjing 211100, Jiangsu, China;Key Laboratory of Underwater Acoustic Communication and Ocean Information Technology of Ministry of Education, Xiamen University, Xiamen 361005, Fujian, China,Array and Information Processing Laboratory, College of Computer and Information, Hohai University, Nanjing 211100, Jiangsu, China and Array and Information Processing Laboratory, College of Computer and Information, Hohai University, Nanjing 211100, Jiangsu, China |
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| Abstract: | In order to mitigate the jamming effect in underwater acoustic communication system, a cognitive space-time adaptive processing algorithm is proposed, which converges faster and reliably due to the sample selection based on interference cognition. The number of jamming is estimated by covariance matrix feature decomposition and MUSIC power spectrum, and the algorithm dimensionality reduction processing is carried out based on the auxiliary selection of the dimensions of the blind source separation algorithm and the spatial dimension of the space-time adaptive algorithm. For the interference after blind source separation, several interference cognition methods exploited to sample selection are studied, including the time domain analysis based on envelope detection and the time-frequency analysis based on Short-time Fourier Transform (STFT). Finally, the performance of this algorithm is confirmed by numerical simulations. |
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| Keywords: | cognitive underwater acoustic communication space-time adaptive processing characteristic extraction |
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