Microwave sensors are gaining increasing interest in blood glucose detection, for their potential ability to perform a continuous non-invasive monitoring of the glucose concentration, by relating the change in the blood dielectric properties to a variation in the glucose level. Usually, the involved body part (phantom) is placed on the sensor to perform the reading. However, the placement modality, as well as other external factors not related to the blood glucose concentrations (BGC) (i.e. system noise, environmental temperature, human tissues variations other than blood tissue) may also have an effect on the sensor response, due to the change in the propagation path of the electromagnetic field inside the body part under test. In this work, the variation effects induced on the microwave sensor response by the changes in the thickness and the dielectric properties of skin and fat tissues are analyzed and faced. In particular, to mitigate the above drawback in terms of sensor instability, a solid ”matching layer” is interposed between the resonant sensor and the phantom under test. A specific optimization procedure is performed to design microwave sensors with a stable response not influenced by variations in tissues different from the blood. Various sensors configurations with related resolution metrics are considered to assess the proposed idea and design methodology. Numerical results confirm the possibility to achieve a good trade-off between the measurement stability against undesired phantom variations and the sensitivity toward blood glucose levels, allowing to discriminate concentrations in the range of [100-300] mg/dL.

The problem of detecting defective elements in antenna arrays from near-field measurements by a MUSIC method is addressed. It is shown that, owing to the rank deficiency of the involved correlation matrix, MUSIC is indeed no better than back-transformation or matrix methods. In order to restore MUSIC performance, a rank recovering procedure is required. Therefore, here, we introduce a rank recovering method which is properly tailored to address the pertinent near-field configuration. Numerical examples, obtained for 2D scalar cases and linear array antennas, show the effectiveness of the method.

The problem of detecting the respiration rate of a human being located behind a wall is addressed using a continuous wave Radar. A Toeplitz based MUSIC algorithm is employed to detect the Doppler modulation induced by chest movements. This method, unlike other smoothing procedures, allows us to restore the rank of the correlation matrix without sacrificing the length of observation time interval and hence the resolution. Experimental results show that the proposed method outperforms the commonly used FFT procedure.

In this paper we consider radar approaches for breast cancer detection. The aim is to give a brief review of the main features of incoherent methods, based on beam-forming and Multiple SIgnal Classification (MUSIC) algorithms, that we have recently developed, and to compare them with classical coherent beam-forming. Those methods have the remarkable advantage of not requiring antenna characterization/compensation, which can be problematic in view of the close (to the breast) proximity set-up usually employed in breast imaging. Moreover, we proceed to an experimental validation of one of the incoherent methods, i.e., the I-MUSIC, using the multimodal breast phantom we have previously developed. While in a previous paper we focused on the phantom manufacture and characterization, here we are mainly concerned with providing the detail of the reconstruction algorithm, in particular for a new multi-step clutter rejection method that was employed and only barely described. In this regard, this contribution can be considered as a completion of our previous study. The experiments against the phantom show promising results and highlight the crucial role played by the clutter rejection procedure.

Time-reversal MUSIC is a super-resolving imaging method that allows localizing point-like scatterers with a resolution much smaller than the diffraction limits. In this letter, we check this statement for a populated scattering scene for the case of 2-D cylindrical perfect electric conducting objects. It is shown that when the data are corrupted even by a small amount of noise, there is an intrinsic limit on the number of scatterers that can be successfully detected. This number turns out to be linked with the so-called number of degrees of freedom corresponding to the spatial region where the targets are located. Moreover, it is shown that the transverse electric polarization is more sensitive to the noise as, given the size of the spatial region occupied by the scatterers, the maximum number of scatterers that can be detected is three times lower than that detectable by the transverse magnetic illumination.