Safety evaluation of steel structures requires knowledge of corrosion progression stages. The deteriorative stage of corrosion involves multiple parameters, and thus it is difficult to be characterised by model-based approaches. In this work, we propose a steel corrosion stages characterisation method using microwave open-ended rectangular waveguide (ORWG) probes and a statistical-based principal component analysis (PCA) method. Two ORWG probes operating in successive bands, ranging between 9.5 to 26.5 GHz, are utilised to obtain reflection coefficient spectra from specific sets of corrosion samples; i.e., uncoated corrosion progression, coated corrosion progression and surface preparation. PCA is applied to extract corrosion progression feature from spectral responses of training samples. The robustness of the PC-based features is analysed with influences of operating frequency, coating layer and surface condition. It is found that the corrosion feature extracted by the first principal component (PC1) from coated and uncoated corrosion samples are highly correlated to the corrosion progress regardless of probe parameter and coating layer.