Rail corrugation is an ondulatory mechanical wear of rail surface raising from the interaction between rail and wheel. Signal processing approaches to corrugation monitoring recommended by the European standards are designed in the distance or wavelength domain. However a joint distance and wavelength domain analysis of the monitoring data can provide crucial information about the distance-evolution of the corrugation modes. We have recently proposed to perform such a distance-wavelength domain analysis using the ARCAP method. This method assumes a model of the data that fits well to a sum of sinusoids. Since each corrugation mode is described by a sinusoid, the ARCAP method is a good candidate for corrugation analysis. Experimental studies performed on data collected on the French RATP metro network have shown that the ARCAP method outperforms the standard distance or wavelength domain methods in localizing and characterizing corrugation. However the ARCAP method suffers from two drawbacks: the amplitude estimator is known to be biased and a priori knowledge of the number of corrugation modes is required. In this contribution we explore a modification of the ARCAP method aimed at tackling these drawbacks. We propose to estimate the corrugation depth using the unbiased APES technique in order to get a more reliable estimation of the amplitude and phase of the modes. We propose also to incorporate a sub-band spectral estimation step so that to improve the frequency estimation performance of the method.