Statistical techniques applied to aerial radiometric surveys (STAARS): time series analysis of airborne radiometric data. National Uranium Resource Evaluation
Airborne radiometric data are often used in reconnaissance for minerals with radiologic isotopes present. The US Department of Energy, through the National Uranium Resource Evaluation (NURE) program, has conducted extensive airborne radiometric surveys over parts of the United States to assist in the location of potentially profitable mineral deposits. In this paper techniques useful in the analysis of these survey data are presented. This paper presents the concept of linearly certain point processes. This concept unifies and extends several previously published models for airborne radiometric data. The concept of filtering a point process together with the model for the process can then be used to derive the matched filter to optimally extract the ground level concentration information from the airborne data. Several additional topics are also discussed. The first is how the airborne data may be used to enhance design of ground-based experiments and measurements. Next, concepts of multivariate time series are developed to show how several energy bands can be optimally used to estimate the concentration of a single isotope using time series regression methods. Finally, time series principal components are used to gain better signal-to-noise properties than are typically obtained with the use of traditional principal components.
- Research Organization:
- Data Information Associates, Inc., Albuquerque, NM (USA)
- DOE Contract Number:
- W-7405-ENG-36; AC13-76GJ01664
- OSTI ID:
- 6749444
- Report Number(s):
- GJBX-215-18; ON: DE83000782
- Country of Publication:
- United States
- Language:
- English
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