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A Separation-Based Localization Method Between Rotating and Static Sources
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AI
DOI：10.1109/LSP.2024.3397727.png)
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摘要
En 中文
Traditional sound source localization methods encounter significant challenges in simultaneously locating rotating and static sources. These challenges arise from the different motion patterns of these two types of sound sources, and they are typically not situated on the same plane. To address this issue, a method based on Modal Composition Beamforming (MCB) and the equivalent source method is proposed for separating rotating and static sound sources, which fully utilizes the prior knowledge of the spatiotemporal properties of these sources. The proposed approach involves establishing a Rotating-Static Sources Power Propagation (R-S2P) model, utilizing the relationship between the equivalent source strength and the actual beamforming output. By employing this forward model and applying an appropriate inversion method, it is possible to separate the components of rotating and static sources. Simulations for three cases with different source strengths are presented, and the R-S2P inversion problem is resolved using the Least Absolute Shrinkage and Selection Operator (LASSO) method. We showed that this method enables accurate separation and localization of rotating and static sources on different planes with varying relative intensities, even if the background noise is strong.
Keyword:
Array signal processing
Location awareness
Microphone arrays
Vectors
Imaging
Background noise
Time-frequency analysis
Separation of Rotating and Static Sources
Modal Composition Beamforming
Sound Source Localization
期刊
IF:
9.6
论文数:
1.1W
被引数:
1.7W
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