摘要
被广泛应用声源识别领域。但在实际的工程运用中,无法满足提前确定声源数目的条件,可能造成识别结果不准确。因此本文提出了一种分段取阈值的OMP-DAMAS算法,在声源稀疏度未知的情况下,通过对内积和最小二乘解取阈值将伪声源和旁瓣对应的列序号从原子支撑集中删除,直接精确的识别出真实声源的位置。仿真和实验结果表明了所提算法与传统的延时求和算法相比,可以明显的减小主瓣宽度,提高空间分辨率,同样能达到OMP-DAMAS算法的重构效果,对噪声具有较好的鲁棒性,且具有极高的识别稳定性。
Abstract
Orthogonal matching pursuit deconvolution algorithm (OMP-DAMAS) is widely used in the field of sound source identification because of its high computational efficiency, spatial resolution, and reconstruction accuracy. However, in practical engineering applications, the condition of determining the number of sound sources in advance cannot be met, which may result in inaccurate identification results. Therefore, this paper proposes a segmented threshold OMP-DAMAS algorithm. When the sparsity of the sound source is unknown, the column numbers corresponding to the pseudo sound source and sidelobe are deleted from the atomic support set by thresholding the inner product and the least square, and the position of the real sound source can be directly and accurately identified. The simulation and experimental results show that compared with the traditional delay summation algorithm, the proposed algorithm can obviously reduce the main lobe width and improve the spatial resolution, and can also achieve the reconstruction effect of OMP-DAMAS algorithm, which has good robustness to noise and high recognition stability.
关键词
正交匹配追踪 /
反卷积 /
声源识别算法 /
阈值
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Key words
orthogonal matching pursuit /
deconvolution /
sound source identification algorithm /
threshold value
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赵卫鹏,毛锦,刘凯,杜进辅.
分段取阈值正交匹配追踪反卷积声源识别算法[J]. 振动与冲击, 2023, 42(15): 268-276
ZHAO Weipeng, MAO Jin, LIU Kai, DU Jinfu.
Deconvolution sound soure indentification algorithm based on piecewise thresholding OMP[J]. Journal of Vibration and Shock, 2023, 42(15): 268-276
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脚注
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