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Proceedings Paper

Use of spline expansions and regularization in the unfolding of data from spaceborne sensors
Author(s): Thornton R. Fisher; Joseph D. Perez
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Paper Abstract

In the analysis of data from spaceborne sensors, the problem frequently arises of determining the best estimate to a continuous spectrum based on a set of noisy data samples taken with broad, overlapping response functions. Examples of such data sets are the data from a retarding potential analyzer (RPA), or a set of line intensities from a solar x-ray spectrum which are to be used to estimate the Differential Emission Measure (DEM). Various approaches often suffer from such difficulties as ill-conditioned matrices, spurious structure, and non-physical negative values in the solution. This paper presents results from a smoothing spline approach, in which the spectrum is expanded in a space of cubic B-spline functions and the coefficients of the expansion are determined by regularization. The technique is first applied to model data which incorporate the general features of the RPA and DEM problems. An example is then given of a fit to data from the Retarding Ion Mass Spectrograph (RIMS) on the Dynamics Explorer 1 (DE-1) satellite.

Paper Details

Date Published: 1 August 1991
PDF: 14 pages
Proc. SPIE 1479, Surveillance Technologies, (1 August 1991); doi: 10.1117/12.44532
Show Author Affiliations
Thornton R. Fisher, Lockheed Missiles & Space Co., Inc. (United States)
Joseph D. Perez, Auburn Univ. (United States)


Published in SPIE Proceedings Vol. 1479:
Surveillance Technologies
Sankaran Gowrinathan; Raymond J. Mataloni; Stanley J. Schwartz, Editor(s)

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