An S-band Ultrawideband Time Reversal-based RADAR for Imaging in Cluttered Media

This work presents a new RADAR prototype built for the purpose of imaging targets located in a cluttered environment. The system is capable of performing Phase Conjugation experiments in the ultrawideband [2-4] GHz. In addition, applying the D.O.R.T. method to the inter-element matrix allows us to selectively focus onto targets, hence reducing the clutter contribution. The system has been validated by phsyically backpropagating the focusing wave into the medium all over the frequency band and observing the expected focusing properties

Eigenspace Time-Reversal Robust Capon Beamforming for Target Localization in Continuous Random Media

© 2017 IEEE. We propose a novel eigenspace time-reversal robust Capon beamformer (E-TR-RCB) for improved target localization in continuous random media. We also derive the Beamspace-TR-RCB (B-TR-RCB) algorithm and compare their localization performances by varying the medium characteristic and excitation bandwidth. Finite-difference time-domain (FDTD) method is used to numerically obtain the multistatic scattered field data from the continuous random dielectric medium. The results indicate that the E-TR-RCB has superior performance over the B-TR-RCB and outperforms the conventional (elementspace) TR-RCB and decomposition of the time-reversal operator (DORT) imaging techniques

Improved DORT for breast cancer detection in low contrast scenarios

© 2015 The Institute of Electronics, Information and Comm. Microwave imaging performance deteriorates with increasing clutter and heterogeneity in the imaging medium. Breast cancer detection becomes increasingly challenging with increasing breast density. Decomposition of the time reversal operator (DORT) uses signal subspace of the multistatic matrix which is perturbed in highly heterogeneous medium. To overcome the problem we propose coherent processing in frequency domain prior to imaging operation. Coherent DORT (C-DORT) provides robust imaging performance compared to conventional non-coherent DORT in cluttered medium as evident from the imaging results obtain using anatomically realistic numerical breast phantoms

An Ultrawideband Time Reversal-based RADAR for Microwave-range Imaging in Cluttered Media

This work presents a new RADAR prototype built for the purpose of imaging targets located in a cluttered environment. The system is capable of performing Phase Conjugation experiments in the ultrawideband [2-4] GHz. In addition, applying the D.O.R.T. method to the inter-element matrix allows us to selectively focus onto targets, hence reducing the clutter contribution. We aim to experimentally explore the use of this focusing wave into an inversion algorithm, in order to improve its robustness against noise. Before testing this idea, we show here the first results validating the prototype separately in the frame of selective focusing via the DORT method and of multistatic-multifrequency inversion

A Robust and Artifact Resistant Algorithm of Ultrawideband Imaging System for Breast Cancer Detection.

Goal: Ultrawideband radar imaging is regarded as one of the most promising alternatives for breast cancer detection. A range of algorithms reported in literature show satisfactory tumor detection capabilities. However, most of algorithms suffer significant deterioration or even fail when the early-stage artifact, including incident signals and skin-fat interface reflections, cannot be perfectly removed from received signals. Furthermore, fibro-glandular tissue poses another challenge for tumor detection, due to the small dielectric contrast between glandular and cancerous tissues. Methods: This paper introduces a novel Robust and Artifact Resistant (RAR) algorithm, in which a neighborhood pairwise correlation-based weighting is designed to overcome the adverse effects from both artifact and glandular tissues. In RAR, backscattered signals are time-shifted, summed, and weighted by the maximum combination of the neighboring pairwise correlation coefficients between shifted signals, forming the intensity of each point within an imaging area. Results: The effectiveness was investigated using 3-D anatomically and dielectrically accurate finite-difference-time-domain numerical breast models. The use of neighborhood pairwise correlation provided robustness against artifact, and enabled the detection of multiple scatterers. RAR is compared with four well-known algorithms: delay-and-sum, delay-multiply-and-sum, modified-weighted-delay-and-sum, and filtered-delay-and-sum. Conclusion: It has shown that RAR exhibits improved identification capability, robust artifact resistance, and high detectability over its counterparts in most scenarios considered, while maintaining computational efficiency. Simulated tumors in both homogeneous and heterogonous, from mildly to moderately dense breast phantoms, combining an entropy-based artifact removal algorithm, were successfully identified and localized. Significance: These results show the strong potential of RAR for breast cancer screening

Microwave-range Imagery with an Ultrawideband Time Reversal-based RADAR

This work presents a new RADAR prototype built for the purpose of imaging targets located in a cluttered environment. The system is capable of performing Phase Conjugation experiments in the ultrawideband [2-4] GHz. In addition, applying the D.O.R.T. method to the inter-element matrix allows us to selectively focus onto targets, hence reducing the clutter contribution. The system has been validated by phsyically backpropagating the focusing wave into the medium all over the frequency band and observing the expected focusing properties