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Title:Incoherent scatter radar spectrum fitting with Arecibo Observatory data
Author(s):Wu, Yulun
Subject(s):incoherent scatter
signal processing
optimization
Abstract:Incoherent scatter radar (ISR) at Arecibo Observatory measures the scattering of electromagnetic waves from random density fluctuations of ionospheric plasma particles (electrons and ions). Information about particle temperatures, ion concentrations, and Doppler shifts caused by particle motions can be estimated by fitting the power spectra of received scatter signals in the frequency domain. Power spectrum estimates are derived by taking FFT of signal samples and averaging the magnitude square of the FFTs. Power spectra include both statistical estimation errors due to the use of finite length data sets and a characteristic shape that depends on ionospheric parameters via a known non-linear relationship that is exploited during the fitting process. This thesis mainly focuses on Arecibo data analysis including spectrum estimation with raw voltage data samples, weighted least squares fitting of the spectral estimates to double-humped spectral model of ionospheric incoherent scatter signals, as well as discussions of potential fitting errors caused by statistical estimation errors and overfit problems.
Issue Date:2017-05
Genre:Other
Type:Text
Language:English
URI:http://hdl.handle.net/2142/97893
Date Available in IDEALS:2017-08-30


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