A bimodal Kalman smoother for nuclear spectrometry

We address the problem of nuclear spectrometry when input count rates are high enough that, in order to limit pile up, classical processing (shaping filter) differs drastically from matched filter solution. We propose a new representation of radiation signals based on a bimodal state space model which leads to a breakthrough in quantitative analysis for high particles rates.