کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4977530 | 1451935 | 2017 | 15 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Using graph clustering to locate sources within a dense sensor array
ترجمه فارسی عنوان
با استفاده از خوشه بندی گراف برای قرار دادن منابع در یک آرایه حسگر متراکم
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کلمات کلیدی
آرایه های لرزه ای، محلی سازی منبع، خوشه بندی گراف، برآورد غیر پارامتری،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
پردازش سیگنال
چکیده انگلیسی
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 geographic spread of these clusters can serve to localize the sources. 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 latter criterion ensures graph sparsity and thus prevents clusters from forming by chance. We verify the approach and quantify its reliability on a simulated dataset. The method is then applied to data from a dense 5200 element geophone array that blanketed 7kmÃ10km of the city of Long Beach (CA). The analysis exposes a helicopter traversing the array and oil production facilities.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Signal Processing - Volume 132, March 2017, Pages 110-120
Journal: Signal Processing - Volume 132, March 2017, Pages 110-120
نویسندگان
Nima Riahi, Peter Gerstoft,