This paper addresses the problem of direction of arrival (DOA) estimation and blind source separation (BSS) for non-stationary signals in the underdetermined case. These two problems are strongly related to the mixing matrix estimation problem. To deal with the non-stationary characteristics of signals, this study uses high-resolution quadratic time-frequency distributions (TFDs) to reduce the cross-terms while keeping a good resolution for the construction of the spatial TFDs (STFDs). The main contributions of this paper are (1) the formulation of a statistical test for the noise thresholding step to improve robustness and avoid the use of empirical parameters; this test performs multisource selection of the time-frequency points where the signal of interest is present; (2) the use of an algorithm, based on image processing methods, which performs an auto-source selection for mixing matrix estimation. The paper presents results on simulated signals that demonstrate an improvement of 10 dB in terms of normalized mean square error for BSS and 7% in terms of relative error for DOA estimation over standard methods.