Validation of a Numerical Model for the Correlation of Spatial Coherence Measurements
- Author:
- Brownstead, Laura
- Published:
- [University Park, Pennsylvania] : Pennsylvania State University, 2022.
- Physical Description:
- 1 electronic document
- Additional Creators:
- Blanford, Thomas E. and Schreyer Honors College
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- honors.libraries.psu.edu , Connect to this object online.
- Restrictions on Access:
- Restricted (PSU Only).
- Summary:
- Work by Blanford et al in 2019 highlighted a numerical model for estimating the correlation of covariance of acoustic signals using data from Seneca Lake collected in 2015. Blanford et al first compared the correlation of covariance of measured data to the statistical estimation assuming a stationary, Gaussian process, referring to this statistical estimation as the analytical model. Finding poor agreement, Blanford et al applied a numerical model that models data by pulling from a Wishart distribution characterized by parameters estimated by statistical properties of the data. This numerical model allowed consideration of non-stationary processes, and Blanford et al found the best agreement when varying signal power estimations. The current work aims to validate the numerical model of best agreement found by Blanford et al in 2019. This work reproduced the analytical and numerical models and found matching results to those of Blanford et al. Three additional data sets were identified to test the limits of the numerical model. The original data set represents a stable environment, while the three new data sets represent one stable and two unstable sets, for a total of four tests for validation of the numerical model. However, each of the three data sets failed to produce results because the fourth order statistics used to parametrize the numerical model are too sensitive to environmental conditions. Thus, the numerical model parametrization specified in the current work is not generally applicable to all data sets.
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- Genre(s):
- Dissertation Note:
- B.S. Pennsylvania State University 2022.
- Technical Details:
- The full text of the dissertation is available as an Adobe Acrobat .pdf file ; Adobe Acrobat Reader required to view the file.
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