Limitations caused by traditional breast cancer detection and screening techniques have encouraged researchers to investigate alternative solutions. This study examines the use of a microwave-based approach for tumor detection in breast tissue and related tumor type classification using matched-filtering. Radar-like confocal microwave imaging (CMI) method constructs the foundation of such tumor detection approach. In particular, a microwave pulse is first transmitted, then back-scattered pulses are collected. All major reflective sites in the breast tissue are detected by repeating this procedure on a microwave pulse transmission-reception grid, aligning captured signals in-time to focus on a particular region in the breast tissue and superimposing such time-shifted signals to improve signal-to-clutter level. In the observed signals, clutter is originated by the heterogeneity of the breast tissue while signal is originated by a tumor site as a function of its water content.All calculations, in the study, were performed computationally in terms of a 3D Finite-Difference Time-Domain (FDTD) simulation models. For the antenna system, two cross-polarized resistively loaded bow-ties antennas were used in the computational model, and the tumor site was modeled using five different size and morphologies. Matched-filtering, on the other hand, was performed matching such obtained observations with that of a homogenous breast tissue, namely clutter-free model. Performance of the proposed approach was tested for two different antenna array resolutions, and it was observed that this parameter is important for successful detection and classification of a tumor-site in a realistic heterogenous breast tissue model.