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中文核心期刊

基于频率滤波张量鲁棒主成分分析的混响抑制

Reverberation suppression based on frequency-filtered tensor robust principal component analysis

  • 摘要: 提出了一种混响抑制方法用于提高有源声呐对水下运动小目标的探测能力。根据固定部署的有源声呐多帧波束形成数据之间相关性强的特点, 使用频率滤波张量核范数对混响的低秩性进行建模, 并使用交替方向乘子法将声呐数据分解为包含稳态混响的低秩张量和包含动目标的稀疏张量。对于稀疏张量中存在的混响起伏干扰, 进一步提出利用动目标回波与混响起伏在加权时空密度上的差异抑制混响。通过实测浅海混响数据验证了所提方法的有效性, 结果表明该方法能够有效抑制稳态混响和混响起伏, 提高有源声呐的小目标探测能力。

     

    Abstract: This paper proposes a reverberation suppression method to enhance the detection capability of active sonar for underwater moving targets. Leveraging the strong correlation between multi-frame beamforming data of fixed-position active sonar, this method models the low-rank nature of reverberation using frequency-filtering tensor nuclear norm. The alternating direction method of multiplier is applied to decompose sonar data into a low-rank tensor containing stationary reverberation and a sparse tensor containing the echoes of moving targets. Due to the presence of reverberation fluctuations in the sparse tensor, this paper further suggests suppressing reverberation by exploiting the differences in weighted spatio-temporal density between reverberation fluctuations and moving target echoes. The effectiveness of the proposed method is validated using the collected shallow-water reverberation data. The experimental results indicate that the presented method can effectively suppress steady reverberation and reverberation fluctuations, thereby enhancing the detection capability of small targets using active sonar.

     

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