Abstract

The time series of data from a radiation portal monitor (RPM) system are evaluated for the presence of point sources by isolating the contribution of anomalous radiation. Energy-windowed background spectra taken from the RPM are compared with the observed spectra at each time step during a vehicle drive-through. The total signal is turned into a ¿spectral distance¿ index using this method. This provides a time series with reduced systematic fluctuations due to background attenuation by the vehicle, and allows for point source detection by time-series analyses. The anomalous time series is reanalyzed by using a wavelet filter function of similar size to the expected source profile. A number of real drive-through data sets taken at a U.S. port of entry are analyzed in this way. A set of isotopes are injected into the data set, and the resultant ¿benign¿ and ¿injected¿ data sets are analyzed with gross-counting, spectral-ratio, and time-based algorithms. Spectral and time methods together offer a significant increase to detection performance.

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