Regularized sparse representation for spectrometric pulse separation and counting rate estimation

Abstract

One of the objectives of nuclear spectroscopy is to estimate the varying counting rate activity of unknown radioactive sources. When this activity is high, however, nonparalyzable detectors suffer from a type of distortion called pile-up effect, when pulses created from different sources tend to overlap. This distortion leads to an underestimation of the activity, which explains the interest of methods for individual pulse separation. We suggest in this paper a two-step method for a better counting rate estimation: the signal is first approximated using a block-sparse regression method, allowing to separate individual pulses quite well. We then estimate their arrival times and plug them into a known activity estimator. Results on simulations and real data illustrate the efficiency of the proposed approach. © 2012 Springer-Verlag.