Fitting PDV spectrograms with likelihood methods

Photonic Doppler Velocimetry (PDV) spectrograms are most often used to extract the single velocity of a single moving surface as a function of time. However, spectrograms regularly have further features than single surfaces with single velocities, including secondary surfaces, clouds and ejecta, and...

Full description

Saved in:
Bibliographic Details
Main Author: Harding, J. Patrick
Format: Conference Proceeding
Language:English
Subjects:
Ejecta
Spectrograms
Statistical methods
Velocimetry
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Photonic Doppler Velocimetry (PDV) spectrograms are most often used to extract the single velocity of a single moving surface as a function of time. However, spectrograms regularly have further features than single surfaces with single velocities, including secondary surfaces, clouds and ejecta, and surface break-up. We present a method for analyzing PDV spectrograms using likelihood methods which can extract the spectrogram information more accurately and uniformly. We demonstrate on data that these methods give statistically-valid velocities and velocity uncertainties. We also show how these methods can be used to derive extractions of complicated surfaces, such as those with ejecta. Finally, we discuss how these methods can be used directly with models of the expected surface velocity to constrain model parameters, even for complicated observations.
ISSN:0094-243X
1551-7616
DOI:10.1063/12.0000878