In this work, a feasibility study for lung lesion detection through microwave imaging based on Huygens’ principle (HP) has been performed using multilayer oval shaped phantoms mimicking human torso having a cylindrically shaped inclusion simulating lung lesion. First, validation of the proposed imaging method has been performed through phantom experiments using a dedicated realistic human torso model inside an anechoic chamber, employing a frequency range of 1–5 GHz. Subsequently, the miniaturized torso phantom validation (using both single and double inclusion scenarios) has been accomplished using a microwave imaging (MWI) device, which operates in free space using two antennas in multi-bistatic configuration. The identification of the target’s presence in the lung layer has been achieved on the obtained images after applying both of the following artifact removal procedures: (i) the “rotation subtraction” method using two adjacent transmitting antenna positions, and (ii) the “ideal” artifact removal procedure utilizing the difference between received signals from unhealthy and healthy scenarios. In addition, a quantitative analysis of the obtained images was executed based on the definition of signal to clutter ratio (SCR). The obtained results verify that HP can be utilized successfully to discover the presence and location of the inclusion in the lung-mimicking phantom, achieving an SCR of 9.88 dB.

This paper aims to show the capability of the Huygens Principle-based microwave imaging for use in Lung COVID-19 infection detection. Frequency-domain measurements have been performed in an anechoic chamber using two Microstrip antennas operating at frequency range of 1 to 5 GHz, in a multi-bistatic fashion, employing dedicated phantoms that mimic the dimensions and the dielectric properties of a human torso, containing a target mimicking an infection. A Multi-layered elliptically-shaped torso-mimicking phantom having the circumference of 82 cm has been constructed; the external layer mimics the dielectric properties of a combination of muscle, fat and rib bone tissues, the inner layer mimics the dielectric properties of lung (inflated). A cylindrically-shaped tube of water has been positioned inside the inner layer to dielectrically mimic the infection. The S 21 signals have been used for image reconstruction (after removing artifacts), obtaining detection with a signal to clutter ratio of 7 dB. Our results confirm that Huygens based technique can be successfully used for lung infection detection even if antennas and phantom are in free space, i.e., no coupling liquid is required.

The main aim of this paper is to upgrade MammoWave acquisition and appropriately extend the Huygens Principle (HP) algorithm for allowing a 3D imaging reconstruction. The MammoWave device contains a cylindrical hub and two antennas, which are positioned at the same height and connected to a 2-port vector network analyser (Cobalt C1209, Copper Mountain, Indianapolis, IN). The two antennas can rotate azimuthally all around the object to be imaged. Measurements are performed recording the complex S21 in a multi-bistatic fashion. In this paper, we have performed a phantom-based investigation using a multi-quote scanning procedure via MammoWave operating at a 1-6.5 GHz frequency range. Specifically, a cylindrical phantom possessing a radius of 5.5 cm and height of 13 cm is constructed and a 3D structured volumetric flask with the spherical bottom (radius 1.75 cm) is used as inclusion. The materials and mixtures used in the preparation of the phantom have a contrast of 5 in dielectric properties. Next, measurements at six different planes along the z-axis are performed and multi-quote data are used in a modified version of the HP-based algorithm via superimposition theorem. The complex 6×15×80 S21 is processed allowing 3D imaging reconstruction; our results clearly show the 3D visualisation of the detected inclusion at multiple planes. In more details, we verified that the dimension of the detected inclusion varies in the different planes of visualisation, accordingly to the spherical inclusion cross-section, with an average error in dimension qualification of <10%.

This work focuses on developing a 3D microwave imaging (MWI) algorithm based on Huygens principle (HP). Specifically, a novel, fast MWI device (MammoWave) has been presented and exploited for its capabilities of extending image reconstruction from 2D to 3D. For this purpose, dedicated phantoms containing 3D structured inclusion have been prepared with mixtures having different dielectric properties. Phantom measurements have been performed at multiple planes along the z-axis by simultaneously changing the transmitter and receiver antenna height via the graphic user interface (GUI) integrated with MammoWave. We have recorded the complex S21 multi-quote data at multiple planes along the z-axis. The complex multidimensional raw data has been processed via an enhanced HP based image algorithm for 3D image reconstruction. This paper demonstrates the successful detection and 3D visualization of the inclusion with varying dimensions at multiple planes/cross-sections along the z-axis with a dimensional error lower than 7.5%. Moreover, the paper shows successful detection and 3D visualization of the inclusion in a skull-mimicking phantom having a cylindrically shaped inclusion, with the location of the detected inclusion in agreement with the experimental setup. Additionally, the localization of a 3D structured spherical inclusion has been shown in a more complex scenario using a 3-layer cylindrically shaped phantom, along with the corresponding 3D image reconstruction and visualization.INDEX TERMS Huygens Principle (HP), MammoWave, Microwave Imaging (MWI), Ultra-wideband (UWB).

This paper reviews the current status, challenges and prognostications of wave energy systems (WES), which have momentous scope in the UK that could deliver the UK's net zero energy target by 2050. In Britain, there are 43 primary seaside towns around the coast in which 37 are in England that encompass a collective population of 2.9 million and signify around 5.7 % of the population of England as a whole where the zero energy coastline house projects can be initiated with WES. The progress in the development of standalone WES for a vision of zero energy coastline houses is still in its initial stages. This paper exhibited a brief review of the onshore, nearshore and offshore WES technologies, particular focus was made to the scope in the UK. The feasibility and efficiency of WES study imply that the power take off (PTO) efficiency is crucially important as the overall output depends on the optimum energy harness from WES that will improve its competitive prowess with other renewable technologies and further reduce the cost of WES manufacturing. This study implicates one of prognostications that developing marine energy resources in the UK can save 60 metric tons of carbon dioxide by 2025. This study also concluded that WES can pose environmental challenges such as alterations of water column to biota and sea-bed habitats, dredging, noise and vibrations. The prognostication of zero energy coastline houses arises due to the location of the UK, which is one of the major determinants for the future success of wave energy projects, as the UK is located at the long fetch of the Atlantic Ocean and has the wind direction from the west. The available resource to harness wave energy in the UK is around 120 GW.