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- W2896431733 abstract "We develop a model-free technique to identify weak sources within dense sensor arrays using graph clustering. No knowledge about the propagation medium is needed except that signal strengths decay to insignificant levels within a scale that is shorter than the aperture. We then reinterpret the spatial coherence matrix of a wave field as a matrix whose support is a connectivity matrix of a graph with sensors as vertices. In a dense network, well-separated sources induce clusters in this graph. The support of the covariance matrix is estimated from limited-time data using a hypothesis test with a robust phase-only coherence test statistic combined with a physical distance criterion. The method is applied to a dense 5200 element geophone array that blanketed 7 km ×10 km of the city of Long Beach (CA). The analysis exposes a helicopter traversing the array." @default.
- W2896431733 created "2018-10-26" @default.
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- W2896431733 date "2018-09-01" @default.
- W2896431733 modified "2023-09-24" @default.
- W2896431733 title "Graph clustering for localization within a sensor array" @default.
- W2896431733 doi "https://doi.org/10.1121/1.5067669" @default.
- W2896431733 hasPublicationYear "2018" @default.
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