Object localization using active sensor network exploiting the scattering of the emitted waves by a transmitter has been drawing a lot of research interest in the last years. For most applications, the environment leads to the arrival of multiple signals corresponding to emitted signal, signals which are scattered by the objects, and noise. In practical systems, the signals impinging on an array are frequently correlated, and the object number rapidly exceeds the number of sensors, making unsuitable most high-resolution methods used in array processing. We propose a solution to overcome these two experimental constraints. Firstly, frequential smoothing is used to decorrelate the scattered signals, enabling the estimation of their time delays of arrival (TDOA), using subspace-based methods. Secondly, an efficient algorithm for source localization using the TDOA is proposed. The advantage of the developed method is its efficiency even if the number of sources is larger than the number of sensors, in the presence of correlated signals. The performances of the proposed method are assessed on simulated signals. The results on real-world data are also presented and analyzed.