Bayesian Processing for the Detection of Radioactive Contraband from Uncertain Measurements
James V. Candy, Kenneth E. Sale, Brian L. Guidry, Eric Breitfeller, Douglas Manatt, David H. Chambers, Alan W. Meyer · 2007
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.