Bayesian Processing for the Detection of Radioactive Contraband from Uncertain Measurements

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Description

With the increase in terrorist activities throughout the world, the need to develop techniques capable of detecting radioactive contraband in a timely manner is a critical requirement. The development of Bayesian processors for the detection of contraband stems from the fact that the posterior distribution is clearly multimodal eliminating the usual Gaussian-based processors. The development of a sequential bootstrap processor for this problem is discussed and shown how it is capable of providing an enhanced signal for eventual detection.

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6 p. (0.3 MB)

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Candy, J V; Sale, K; Guidry, B; Breitfeller, E; Manatt, D & Chambers, D June 26, 2007.

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Description

With the increase in terrorist activities throughout the world, the need to develop techniques capable of detecting radioactive contraband in a timely manner is a critical requirement. The development of Bayesian processors for the detection of contraband stems from the fact that the posterior distribution is clearly multimodal eliminating the usual Gaussian-based processors. The development of a sequential bootstrap processor for this problem is discussed and shown how it is capable of providing an enhanced signal for eventual detection.

Physical Description

6 p. (0.3 MB)

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PDF-file: 6 pages; size: 0.3 Mbytes

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  • Journal Name: IEEE CAMSAP '07, vol. 2, no. 1, December 15, 2007, pp. 2-15

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  • Report No.: UCRL-JRNL-232317
  • Grant Number: W-7405-ENG-48
  • Office of Scientific & Technical Information Report Number: 942026
  • Archival Resource Key: ark:/67531/metadc895777

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  • June 26, 2007

Added to The UNT Digital Library

  • Sept. 27, 2016, 1:39 a.m.

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  • April 13, 2017, 6:20 p.m.

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Candy, J V; Sale, K; Guidry, B; Breitfeller, E; Manatt, D & Chambers, D. Bayesian Processing for the Detection of Radioactive Contraband from Uncertain Measurements, article, June 26, 2007; Livermore, California. (digital.library.unt.edu/ark:/67531/metadc895777/: accessed September 23, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.