Computational polarimetric microwave imaging

We propose a polarimetric microwave imaging technique that exploits recent advances in computational imaging. We utilize a frequency-diverse cavity-backed metasurface, allowing us to demonstrate high-resolution polarimetric imaging using a single transceiver and frequency sweep over the operational microwave bandwidth. The frequency-diverse metasurface imager greatly simplifies the system architecture compared with active arrays and other conventional microwave imaging approaches. We further develop the theoretical framework for computational polarimetric imaging and validate the approach experimentally using a multi-modal leaky cavity. The scalar approximation for the interaction between the radiated waves and the target---often applied in microwave computational imaging schemes---is thus extended to retrieve the susceptibility tensors, and hence providing additional information about the targets. Computational polarimetry has relevance for existing systems in the field that extract polarimetric imagery, and particular for ground observation. A growing number of short-range microwave imaging applications can also notably benefit from computational polarimetry, particularly for imaging objects that are difficult to reconstruct when assuming scalar estimations.Comment: 17 pages, 15 figure

FMCW Signals for Radar Imaging and Channel Sounding

A linear / stepped frequency modulated continuous wave (FMCW) signal has for a long time been used in radar and channel sounding. A novel FMCW waveform known as “Gated FMCW” signal is proposed in this thesis for the suppression of strong undesired signals in microwave radar applications, such as: through-the-wall, ground penetrating, and medical imaging radar. In these applications the crosstalk signal between antennas and the reflections form the early interface (wall, ground surface, or skin respectively) are much stronger in magnitude compared to the backscattered signal from the target. Consequently, if not suppressed they overshadow the target’s return making detection a difficult task. Moreover, these strong unwanted reflections limit the radar’s dynamic range and might saturate or block the receiver causing the reflection from actual targets (especially targets with low radar cross section) to appear as noise. The effectiveness of the proposed waveform as a suppression technique was investigated in various radar scenarios, through numerical simulations and experiments. Comparisons of the radar images obtained for the radar system operating with the standard linear FMCW signal and with the proposed Gated FMCW waveform are also made. In addition to the radar work the application of FMCW signals to radio propagation measurements and channel characterisation in the 60 GHz and 2-6 GHz frequency bands in indoor and outdoor environments is described. The data are used to predict the bit error rate performance of the in-house built measurement based channel simulator and the results are compared with the theoretical multipath channel simulator available in Matlab

Microwave breast imaging using a dry setup

This article demonstrates for the first time, both numerically and experimentally, the feasibility of radar-based microwave imaging of anthropomorphic heterogeneously dense breasts in prone position, requiring no immersion liquid. The dry, contactless approach greatly simplifies the setup, favors patient comfort, and further avoids lengthy sanitation procedures after each exam. We use a radar-type technique with the antennas distributed in cylindrical configuration around the breast phantom. The reflectivity map is reconstructed using a wave-migration algorithm in the frequency domain. This article presents new developed strategies to cope with the challenges of a dry setup, namely increased skin artifact due to the concomitant absence of matching liquid and nonuniform breast shape. We propose an iterative and adaptive algorithm based on singular value decomposition that effectively removes the skin backscattering under the abovementioned conditions. It is compatible with automatic processing, and computationally fast. One of its inputs is the breast three-dimensional surface information, and its distance to the antennas, all obtained automatically from a proposed low-cost procedure based on a webcam. The imaging method is reasonably resilient to the presence of fibroglandular tissues, and to uncertainties of tissue permittivity. Another tackled challenge is the miniaturization of the antenna in air, which is achieved with an optimized balanced antipodal Vivaldi of the same size as counterparts used in dense immersion liquids. Finally, all the building blocks are combined to demonstrate experimentally the overall dry system performance, with very good detection of the tumor at three different positions in the breast, even in low-contrast scenarios.info:eu-repo/semantics/acceptedVersio

Achieving Accuracy in Early Stage Tumor Identification Systems based on Image Segmentation and 3D Structure Analysis

Cancer is a disease which can be removed if early stage tumor identification systems efficiently and accurately work at cancer hospitals. As the accuracy in detection of tumor means to detect exact size of the tumor. Because the best way to beat cancer is early stage tumor diagnosis and quality treatment. In this research article an accuracy module is proposed for computer aided tumor diagnosis system. The ultimate proposed CAD gets image of tumor infected lung and breast images from different state of the art early stage tumor detection methodologies as micrographic and mammographic based imaging systems. For accuracy in detection of early stage tumor, image enhancement and segmentation techniques are applied according to the imaging problems at input image. Also for accurate estimation of tumor the 3D image construction and 3D structure analysis are tried to realized. The realization of the proposed CAD proves that the accuracy module can assist well the computer aided tumor diagnosis systems with almost near to 100% accuracy in early stage tumor detection and size estimation for breast and lung cancer. Keywords: Computer Aided Tumor Detection, Accurate identificatio