University of Illinois at Urbana-Champaign
Inversion of Arecibo incoherent scatter radar coded long pulse backscatter spectra
Abstract
dc:descriptionIncoherent 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 inverting the power spectra of received scatter signals to the numerially implemented ISR forward spectral model 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 inversion process. This thesis first describes the numerical implementation of the complete collisional ISR spectral model using chirp-z algorithm, and mainly focuses on Arecibo coded long pulse (CLP) data analysis, including spectrum generation and inversion of raw voltage data from two receivers of Arecibo Observatory. Regular FFT method and the multi-level chirp-z algorithm for speeding up spectrum computation are presented. Weighted least-square spectrum inversion of the spectral estimates to double-humped spectral model of ionospheric incoherent scatter signals using various inversion techniques including the inversion of ion drift velocity using measured spectra ACF are discussed.
Degree
thesis:*- Name thesis:degree_name
- M.S.
- Level thesis:degree_level
- Thesis
- Discipline thesis:degree_discipline
- Electrical & Computer Engr
- Grantor
- University of Illinois at Urbana-Champaign
- Year dc:date
- 2020
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Wu, Yulun
- Contributors dc:contributor
-
- Kudeki, Erhan
Subjects
dc:subject × 3Rights
dc:rights- Statement dc:rights
-
- Copyright 2020 Yulun Wu
- Language dc:language
- en
Identifiers
dc:identifier.*- Handle dc:identifier
- http://hdl.handle.net/2142/108203
- OAI identifier oai:identifier
- oai:www.ideals.illinois.edu:2142/108203