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Acoustic travel-time tomography of t...
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Vecherin, S. N.
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Acoustic travel-time tomography of the atmosphere.
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Acoustic travel-time tomography of the atmosphere./
作者:
Vecherin, S. N.
面頁冊數:
135 p.
附註:
Adviser: Vladimir Ostashev.
Contained By:
Dissertation Abstracts International68-07B.
標題:
Atmospheric Sciences. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3273246
ISBN:
9780549131519
Acoustic travel-time tomography of the atmosphere.
Vecherin, S. N.
Acoustic travel-time tomography of the atmosphere.
- 135 p.
Adviser: Vladimir Ostashev.
Thesis (Ph.D.)--New Mexico State University, 2007.
Knowledge of temperature and wind velocity fields in the near-ground atmospheric layer is important for many areas, e.g. boundary layer meteorology, theories of turbulence, and study of sound and electromagnetic wave propagation. The conventional way to measure temperature and wind velocity uses in-situ sensors (e.g., meteorological thermometer-anemometers). However, such measurements provide the values of temperature and wind velocity only at widely separated points. More sensors are required to measure the fields at other points. However, a large number of sensors will significantly distort the original fields. In contrast, acoustic travel-tune tomography allows remote sensing of temperature and wind velocity fields, and requires far fewer transducers for the same amount of data than the conventional in-situ measurements. This dissertation studies several different tomographic approaches, which can be divided into three classes: (i) algebraic techniques that divide the fields into constant-valued cells; (ii) a basis function approach that represents the fields as the sum of known basis functions with unknown coefficients; and (iii) stochastic approaches that take into account spatial or spatial-temporal correlations of the fields. First, it is shown that the conventional stochastic inversion approach, which utilizes spatial correlations, yields more detailed and accurate reconstruction of temperature and wind velocity fields in the atmosphere than traditional algebraic techniques and a basis function approach. Second, it is shown that a more general time-dependent stochastic approach, which utilizes both spatial and temporal correlations, allows more accurate reconstruction than any of the other techniques mentioned above.
ISBN: 9780549131519Subjects--Topical Terms:
1019179
Atmospheric Sciences.
Acoustic travel-time tomography of the atmosphere.
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Knowledge of temperature and wind velocity fields in the near-ground atmospheric layer is important for many areas, e.g. boundary layer meteorology, theories of turbulence, and study of sound and electromagnetic wave propagation. The conventional way to measure temperature and wind velocity uses in-situ sensors (e.g., meteorological thermometer-anemometers). However, such measurements provide the values of temperature and wind velocity only at widely separated points. More sensors are required to measure the fields at other points. However, a large number of sensors will significantly distort the original fields. In contrast, acoustic travel-tune tomography allows remote sensing of temperature and wind velocity fields, and requires far fewer transducers for the same amount of data than the conventional in-situ measurements. This dissertation studies several different tomographic approaches, which can be divided into three classes: (i) algebraic techniques that divide the fields into constant-valued cells; (ii) a basis function approach that represents the fields as the sum of known basis functions with unknown coefficients; and (iii) stochastic approaches that take into account spatial or spatial-temporal correlations of the fields. First, it is shown that the conventional stochastic inversion approach, which utilizes spatial correlations, yields more detailed and accurate reconstruction of temperature and wind velocity fields in the atmosphere than traditional algebraic techniques and a basis function approach. Second, it is shown that a more general time-dependent stochastic approach, which utilizes both spatial and temporal correlations, allows more accurate reconstruction than any of the other techniques mentioned above.
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