This work aims to analyze the reference (montage) problem in electroencephalographic (EEG) recordings. It is well accepted that EEG signals are a mixture of cerebral and extra-cerebral sources, and the solution to the reference problem depends on the hypothesized mixing model. We focus here on an acquisition model using a distant reference electrode and propose a method for determining and eliminating the reference signal which develops and improves Hu et al work (2007). The obtained solution, based on a constrained blind source separation (BSS) algorithm, outperforms the cited method on simulated noisy EEG signals for all noise levels.