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Adaptive Extraction of Signals Using Microphone Arrays Against the Background of a Set of Intense-Interference Sources

机译:使用麦克风阵列对一组激干源的背景使用麦克风阵列的自适应提取

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摘要

We consider the problem of extracting an acoustic signal of an individual source in the presence of a set of spatially separated sources when reception is performed using a microphone array. In this case, it is assumed that the extracted-signal source is located in the preliminarily known limited spatial region. Such a problem is of practical value, e.g., for speech listening in crowded areas, extracting signals from individual sources in the problems of acoustic diagnostics of various mechanical systems, etc. An adaptive spatial-processing algorithm, which is based on using the interference model in the form of a set of sources with arbitrary unknown direction vectors, is proposed to independently solve the above-mentioned problem for each narrow band of the received signal. The advantage of the proposed method is its robustness to the discrepancies between the used model and the actual conditions. Such a robustness is achieved without using a priori data on the character of the errors in the used model. We present the results of the speech-signal extraction using numerical simulation and the experimental data for the scenarios which involve the presence of high-power interference sources, as well as the errors when specifying the direction vector. The obtained results demonstrate a higher efficiency of using the proposed method under the actual conditions compared with other available techniques.
机译:我们考虑在使用麦克风阵列执行接收时在一组空间分离的源的情况下提取单个源的声学信号的问题。在这种情况下,假设提取的信号源位于预报上已知的有限空间区域中。这样的问题是实用价值,例如,对于拥挤的区域中的语音收听,从各种机械系统的声学诊断的问题中提取来自各个源的信号等。一种自适应空间处理算法,其基于使用干扰模型以一组具有任意未知方向向量的源的形式,提出独立地解决接收信号的每个窄带的上述问题。所提出的方法的优点是其对二手模型与实际条件之间的差异的鲁棒性。在不使用经过先验的模型中的错误的特征的情况下实现这种稳健性。我们使用数值模拟和涉及高功率干扰源的情况的场景的实验数据介绍语音信号提取的结果,以及指定方向向量时的误差。获得的结果表明,与其他可用技术相比,在实际条件下使用所提出的方法的效率更高。

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