Title :
Improvement of SNM Detection Performance by Fusion of Data From Multiple Inspection Systems
Author :
Shaw, T.J. ; Strellis, Dan A. ; Keeley, Doug ; Yee, Ryan ; Gozani, Tsahi
Author_Institution :
Rapiscan Labs., Inc., Sunnyvale, CA
fDate :
6/1/2009 12:00:00 AM
Abstract :
Data fusion has the potential to improve the performance of multiple systems over algorithms involving only Boolean combinations of decisions from the separate systems. To achieve this improvement, it is essential to utilize the complementary aspects of the systems involved. In this paper, we demonstrate that data fusion of x-ray radiography and neutron capture gamma ray spectroscopy provide complementary data to differential die away analysis, and thereby a substantial improvement in both detection performance and throughput.
Keywords :
gamma-ray detection; gamma-ray spectra; inspection; neutron detection; neutron spectroscopy; nuclear engineering computing; radiography; sensor fusion; Boolean combinations; SNM detection; data fusion; differential die away analysis; multiple inspection systems; neutron capture gamma ray spectroscopy; special nuclear material detection; x-ray radiography; Gamma ray detection; Gamma ray detectors; Inspection; Neutrons; Performance analysis; Radiography; Spectroscopy; Throughput; X-ray detection; X-ray detectors; Contraband detection; SNM detection; data fusion; radiation detectors;
Journal_Title :
Nuclear Science, IEEE Transactions on
DOI :
10.1109/TNS.2008.2011806