A Maximum-Entropy Technique for Deconvolution of Atmospheric Bremsstrahlung Spectra.

Abstract

Spectral parameters of auroral electrons incident on the atmosphere can be inferred from satellite observations of bremsstrahlung X ray spectra. Although the production and transport of >1 keV bremsstrahlung X rays in the atmosphere are reasonably well understood, in practice the use of bremsstrahlung measurements to infer incident electron spectra is hampered by instrumental limitations and low signal to noise ratio. Thus, a spectral deconvolution scheme which makes the most effective use of available data is required. The maximum entropy formalism is a statistical technique which provides a statistically optimal estimator of a continuous quantity (in this case, the electron spectrum) when a discrete set of integral functions of that quantity are known (namely, the observed X ray spectrum). A numerical maximum entropy deconvolution scheme has been developed and applied to bremsstrahlung X ray measurements from the Aerospace X ray spectrometer on DMSP-F6. Good results have been obtained for inferred electron spectra acquired from a variety of auroral forms. These results are presented, and the stability and uniqueness of the solutions are discussed.

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Document Details

Document Type
Technical Report
Publication Date
Oct 15, 1986
Accession Number
ADA175153

Entities

People

  • David J. Gorney
  • James L. Roeder
  • Paul F. Mizera

Organizations

  • The Aerospace Corporation

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies
  • Space

DTIC Thesaurus Topics

  • Artificial Satellites
  • Bremsstrahlung
  • Chemical Kinetics
  • Detectors
  • Materials
  • Materials Science
  • Measurement
  • Meteorological Satellites
  • Optimal Estimators
  • Physical Theories
  • Physics Laboratories
  • Radiation
  • Semiconductor Devices
  • Space Sciences
  • Spectra
  • X Ray Spectra
  • X Rays

Fields of Study

  • Physics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Solar Physics

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • Microelectronics
  • Space