Ionisation spectra in nanometric volumes at a given distance from a charged particle track are obtained by using electron (or ion) gas detectors, having non-uniformly distributed detection efficiency. Therefore, such spectra should be properly processed in order to reconstruct the frequency distribution of clusters really produced in the detector gas. A Bayesian unfolding has been applied to ionisation distributions due to 5.4 MeV alpha particles in a 20-nm site obtained by Monte Carlo simulations, taking into account different detection efficiency conditions. It will be shown that Bayesian analysis provides a valid tool for reconstructing the true ionisation distributions, well beyond the maximum measured cluster size.