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This paper deals with the coherent processing of time-reversal operator for microwave imaging in the frequency domain. In frequency domain time-reversal imaging approach, images obtained for different frequency bins over ultrawideband are incoherently processed. In highly dense and cluttered medium, the signal subspace over each narrow frequency bin varies from that obtained using the complete ultrawideband. As a result, the detection and localization from noncoherent imaging approach is often inconclusive. In order to improve the stability of time-reversal microwave imaging, we propose coherent processing using novel focusing matrix approach. The proposed focusing matrix makes possible the time-reversal imaging technique to coherently process each frequency bin to yield a consistent signal subspace. The performance of coherent focusing is investigated when combined with time-reversal robust Capon beamformer (TR-RCB). We have used numerical experiments on breast cancer detection using finite difference time domain employing anatomically realistic numerical breast phantoms that contain varying amounts of dense fibroglandular tissue content. The imaging results indicate that the proposed coherent-TR-RCB could overcome the limitations of time-reversal imaging in a highly heterogeneous and cluttered medium.

In this paper we investigate the detection of breast cancer using two-dimensional slices of realistic numerical phantoms employing time reversal microwave imaging. We used maximum-likelihood estimation coupled with time reversal technique to detect and estimate the location of tumor using FDTD based breast phantoms that contain dense fibroglandular tissue clutter. We show that time reversal maximum-likelihood estimation can detect and accurately localize tumors even in highly dense breasts where the dielectric contrast between healthy dense breast tissue and cancerous lesions is quite low without requiring any contrast enhancing agents.

The time reversal (TR) based minimum variance beamforming, both the standard capon beamforming (SCB) and robust capon beamforming (RCB) techniques for microwave imaging of breast for early stage breast cancer detection is considered in this paper. The performance of coherent signal subspace processing for TR-SCB and TR-RCB techniques is investigated. We have used anatomically realistic numerical breast phantoms in FDTD simulations. We consider 2D sagittal slice of the breast phantom in 2D FDTD simulation. Our simulation results indicate that coherent signal subspace processing significantly improves the performance of TR based minimum variance beamforming techniques.Index Terms -Time reversal, robust Capon beam forming, coherent signal subspace, breast cancer, microwave imaging.