Ultra Wideband Radar imaging has shown promising results in the detection of small tumours within low to medium density human breasts. A wide range of beamforming algorithms has been presented in several recent studies with good tumour localization capabilities, but most of these suffer a deterioration in performance with an increase in breast tissue density. In this paper, a preprocessing filter is used to compensate for path-dependent attenuation and phase effects, in conjunction with a range of existing data-dependent and data-independent confocal microwave imaging algorithms. Results indicate that this data preprocessing improves the performance of all beamformers, enabling detection and accurate localization of multiple tumours in mild to moderately dense human breasts. The proposed framework is tested on 3D anatomically accurate numerical breast models and the performance is evaluated across a range of appropriate metrics.