基于鄰近頻點相關特性的水聲信號盲源分離
Blind Source Separation of Underwater Acoustic Signals Based on the Correlation between Neighbor Frequency Bins
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摘要: 排序和幅度不一致性是信號頻域盲源分離的主要困難。該文建立了鄰近頻點相關特性理論，并針對水聲信號進行深入研究，結論表明單個水聲信號鄰近頻點間相關特性良好，且性能非常穩(wěn)定；而兩個不同水聲信號鄰近頻點相關性非常弱。提出基于鄰近頻點相關特性的盲源分離算法，用于消除卷積信號盲源分離過程中排序不確定性，實驗表明該方法對卷積混合形式的水聲信號能取得較好分離效果。Abstract: Indeterminacies in amplitude and permutation are the two main cumbersome aspects in frequency domain blind signal separation. A correlation theory between neighbour frequency bins is developed in this paper. It is found that the correlation between neighbor frequency bins of single underwater acoustic signal is strong and stable, while it is very weak in the case of two different signals. Based on these correlation characters, a novel blind source separation method is developed, which can get rid of the permutation indeterminacy. Simulation experiments prove that convolution mixed underwater acoustic signals can be well separated by this method.
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