Independent component analysis (ICA) is one of the most important methods for blind source separation (BSS)

in which the pre-whitening procedure of the observed signals plays an important role.Usually

principle component analysis (PCA) is employed for this preprocessing task.In practice

the observed signals of a passive radar system are usually corrupted by strong noise and outliers

which greatly reduces the performance of BSS methods.However

this problem is rarely taken into account in the whitening step of traditional BSS methods.We focus on this problem and propose a new whitening framework for noisy BSS.The idea is that the noise variance is removed from the covariance matrix of the observed signals before whitening.The experiments show that the BSS performance is greatly improved using the proposed whitening framework.