基于稀疏分解的水下目标回波信号处理方法
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Underwater Echo Signal Processing Method Based on Sparse Decomposition
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    摘要:

    针对超低信噪比的水下弱信号处理问题,基于稀疏分解理论,重点关注入射信号和回波模型等先验信息如何融入稀疏字典(过完备原子库)的构造,并结合匹配追踪方法,提出基于稀疏分解的水下回波信号处理方法。首先建立水下回波信号亮点模型,得到回波模型和入射 信号的关系,对已知的发射信号进行离散化、能量归一化以及移位处理,构造适合回波信号自身特性的过完备原子库;然后基于匹配追踪算法实现水下回波信号的稀疏分解,并将处理结果与常用的匹配滤波方法进行对比分析。仿真结果表明,本文方法不仅能精确重构出原始回波信号,而且在处理超低信噪比水下回波信号时较匹配滤波方法具有明显的优势。

    Abstract:

    For ultra-low-SNR underwater weak signal processing problem, an underwater echo signal processing method is presented based on the theory of sparse decomposition and the combined matched pursuit method. The focus is how to integrate the prior information, such as the incident signal and the echo model, into the sparse dictionary (atoms). First, the highlight model of underwater echo signal is established, the relation between the echo model and incident signal is obtained, and the over complete dictionary fitting for echo signal characteristics is structured by discretizing, energy normalizing and shifting the known transmitting signal. And then, the sparse decomposition of underwater echo signal is conducted based on the matched pursuit method, and the processing results are compared and analyzed with the commonly used matched filter methods. The simulation results show that the proposed method can accurately reconstruct the original echo signal, and has obvious advantage in processing underwater echo signal with ultra-low SNR.

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孙同晶 贺锦鹏 谷雨.基于稀疏分解的水下目标回波信号处理方法[J].数据采集与处理,2016,31(2):282-288

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  • 在线发布日期: 2018-04-09