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Pattern Reconfigurable Wideband Loop Antenna for Thorax Imaging
摘要： A unidirectional loop antenna that can achieve wideband pattern re-configurability from -40 to +40 degrees in azimuth plane is presented. The antenna is designed to fulfill the multi-slice (level) scanning requirements of electromagnetic imaging (EMI) systems for thorax imaging. To overcome the need for positioning of several antenna-arrays, and hence eliminate the mutual coupling related complications, a square-loop antenna with reconfigurable pattern is designed. To create a unidirectional radiation, the loop is loaded with capacitive gaps, which convert its radiation mechanism to that of two virtual dipole arrays with quadrature phase excitation. By utilizing this feature, the location of the gaps are varied on the loop's structure to form virtual dipole arrays in different directions, thus rotating the radiation pattern without physically moving the structure of the antenna. As a proof of concept, six gaps were created on the loop and each gap is loaded with a PIN diode to electronically switch between the positions of the designed gaps, thus enabling changing the radiation direction. The proposed antenna can achieve a compact size of 0.32λ×0.32λ×0.002λ (λ is the wavelength of the lowest resonance of the antenna) and a wide fractional bandwidth of 32% at 0.8-1.15 GHz, with a peak gain and front-to-back-ratio of 2.1 dBi and 8 dB, respectively. The antenna is successfully tested on a thorax imaging platform to detect small volume of water (5 mL) inside lungs as an emulation of early pulmonary edema.
关键词： unidirectional antenna,virtual dipole array,pattern reconfigurable antenna,loop antenna,Electromagnetic imaging,wideband antenna
更新于2025-09-23 15:23:52
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[IEEE 2018 IEEE International Conference on Computational Electromagnetics (ICCEM) - Chengdu (2018.3.26-2018.3.28)] 2018 IEEE International Conference on Computational Electromagnetics (ICCEM) - Complex-Valued Deep Convolutional Networks for Nonlinear Electromagnetic Inverse Scattering
摘要： Electromagnetic inverse scattering problem is a typical complex problem while traditional deep convolutional neural network can only be applied to real problem. Motivated by this, this paper presents a new approach for electromagnetic inverse problem with complex convolutional neural network. In this way, several cascaded convolutional neural network modules are introduced to learn a model to realize super-resolution for electromagnetic imaging. The simulation and experimental results show that the proposed method paves a new way addressing real-time practical large-scale electromagnetic inverse scattering problems.
关键词： super-resolution,electromagnetic imaging,convolutional neural network,electromagnetic inverse problem
更新于2025-09-23 15:21:21
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[IEEE 2019 Photonics & Electromagnetics Research Symposium - Fall (PIERS - Fall) - Xiamen, China (2019.12.17-2019.12.20)] 2019 Photonics & Electromagnetics Research Symposium - Fall (PIERS - Fall) - An Efficient Algorithm of Explicit Sensitivity Matrix in 3D Marine Controlled-source Electromagnetic Imaging
摘要： In this paper, we set up an e?cient algorithm of the 3D synthetic response and explicit sensitivity matrix of 3D mCSEM inversion in the two di?erent model spaces: block model and pixel model. The Helmholtz equations of coupled electrical scalar-vector potentials with Coulomb gauge is discretized by 3D ?nite volume method at Yee’s staggered girds to form a large, sparse and complex linear system with multi-transmitters. A direct solver PARDISO is used to stably and accurately solve the system. Furthermore, the scattered EM ?elds caused by the conductivity perturbation are also solved by the 3D ?nite volume method based on the scattered scalar-vector potentials at the same Yee’s staggered girds. In order to further enhance the whole computation e?ciency, the interpolation operator and projection operator are advanced to realize directly and fast transformation of the terms on right hands side of discrete systems to the EM ?elds at arbitrary position because the number of receivers is greatly less than that of scattering sources and transmitters. The explicit EM sensitivity matrix in the two di?erent model space will be set up by only addition of a two-matrix multiple. Finally, we investigate the distributing disciplinarian and response characteristics of explicit sensitivity matrix in two di?erent cases for block and pixel inversion.
关键词： finite volume method,block model,pixel model,explicit sensitivity matrix,3D marine controlled-source electromagnetic imaging,PARDISO
更新于2025-09-23 15:19:57
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Feature Extraction of Structures in Sea Water Using Self-Organizing Maps and Electromagnetic Waves
摘要： The use of Self-Organizing Map (SOM) algorithm for feature extraction and dimensionality reduction applied to underwater object detection with Low Frequency Electromagnetic Waves is presented. Computer simulation is used to generate a direct model for the study region, and a Self Organizing Map Algorithm is used to fit the data and return a similar model, with smaller dimensionality and same characteristics. Results show that virtual sensors are created by the SOM algorithm with consistent predictions, filling the resolution gap of the input data. These results are useful for fastening decision making algorithms by reducing the number of inputs to a group of significant data.
关键词： Self-Organizing Maps,electromagnetic imaging,unsupervised neural networks
更新于2025-09-19 17:15:36