Learning-Assisted Inversion for Solving Nonlinear Inverse Scattering Problem

Solving inverse scattering problems (ISPs) is challenging because of its intrinsic ill-posedness and the nonlinearity. When dealing with highly nonlinear ISPs, i.e., those scatterers with high contrast and/or electrically large size, the traditional iterative nonlinear inversion methods converge slowly and take lots of computation time, even maybe trapped into local wrong solution. To alleviate the above challenges, a learning-assisted (LA) inversion approach termed as the LA inversion method (LAIM) with advanced generative adversarial network (GAN) in virtue of a new recently established contraction integral equation for inversion (CIE-I) is proposed to achieve a good balance between the computational efficiency and the accuracy of solving highly nonlinear ISPs. The preliminary profiles composed of only small amount of low-frequency components can be got efficiently by the Fourier bases expansion of CIE-I inversion (FBE-CIE-I). The physically exacted information can be taken as the input of the neural network to recover super-resolution image with more high-frequency components. A weighted loss function composed of the adversarial loss, mean absolute percentage error (MAPE), and structural similarity (SSIM) is used under the pix2pix GAN framework. In addition, the self-attention module is used at the end of the generator network to capture the physical distance information between two pixels and enhance the inversion accuracy of the feature scatterers. To further improve the inversion efficiency, the data-driven method (DDM) is used to achieve real-time imaging by cascading U-net and pix2pix GAN, where U-net is used to replace FBE-CIE-I in the LAIM. Compared with other LA inversion, both the synthetic and experimental examples have validated the merits of the proposed LAIM and DDM

Reconfigurable Meta-Radiator Based on Flexible Mechanically Controlled Current Distribution in Three-dimensional Space

In this paper, we provide an experimental proof-of-concept of this dynamic 3D current manipulation through a 3D-printed reconfigurable meta-radiator with periodically slotted current elements. By utilizing the working frequency and the mechanical configuration comprehensively, the radiation pattern can be switched among 12 states. Inspired by maximum likelihood method in digital communications, a robustness-analysis method is proposed to evaluate the potential error ratio between ideal cases and practice. Our work provides a previously unidentified model for next-generation information distribution and terahertz-infrared wireless communications

A Reactance Compensated Three-Device Doherty Power Amplifier for Bandwidth and Back-Off Range Extension

This paper proposes a new broadband Doherty power amplifier topology with extended back-off range. A shunted λ/4 short line or λ/2 open line working as compensating reactance is introduced to the conventional load modulation network, which greatly improves its bandwidth. Underlying bandwidth extension mechanism of the proposed configuration is comprehensively analyzed. A three-device Doherty power amplifier is implemented for demonstration based on Cree’s 10 W HEMTs. Measurements show that at least 41% drain efficiency is maintained from 2.0 GHz to 2.6 GHz at 8 dB back-off range. In the same operating band, saturation power is larger than 43.6 dBm and drain efficiency is higher than 53%

A fast integral equation based method for solving electromagnetic inverse scattering problems with inhomogeneous background

on-line, May 2018International audienceA family of difference integral equations, consisting of difference Lippmann-Schwinger integral equation (D-LSIE)and difference new integral equation (D-NIE), is proposed to solve the electromagnetic inverse scattering problems(ISPs) with inhomogeneous background medium bounded in a finite domain. Without resorting to Green’s function forinhomogeneous background medium, in the frame of the difference integral equation methods, the Green’s functionwith homogeneous medium is utilized such that not only fast algorithms (referring to those used in forwardscattering problems, like CG-FFT, FMM) can be adopted but also the burdensome calculation for the numericalGreen’s function for the inhomogeneous background medium is avoided. Especially, to tackle the ISPs with strongnon-linearity, those with large contrast and/or large dimensions, a Low-Pass Filter-Matching (LPFM) regularizationis introduced, which aims to stably match the information from the background medium to the unknown scatterer.Together with the D-NIE model, the proposed inversion method can efficiently tackle the ISPs with strong non-linearitywhile a bounded inhomogeneous medium being present. Against both synthetic and experimental data, several representativenumerical tests illustrate the efficacy of the proposed inversion method

A Deep-Learning Approach for Wideband Design of 3D TSV-Based Inductors

A high-efficient wideband through-silicon vias (TSVs) modeling method based on deep learning is proposed, and a compact three-dimensional (3D) spiral inductor is designed using the proposed method. By comparing different activation functions and loss functions, an adaptive deep neural network (DNN) based on Gaussian Error Linear Unit (GELU) and Huber functions for constructing parameterized TSV models is proposed. The model has much higher accuracy and better robustness than commonly used circuit equivalent models over a wide range of bandwidths. Moreover, a compact 3D spiral inductor using ground TSV is designed based on the DNN model. This 3D inductor greatly reduces the inductor area compared to planar inductors and has weak crosstalk between TSV pairs. The designed inductor is simulated by direct electromagnetic calculation to verify the proposed method and design

A Multiresolution Contraction Integral Equation Method for Solving Highly Nonlinear Inverse Scattering Problems

International audienceThe solution of highly nonlinear inverse scattering problems is addressed. An innovative multiresolution microwave imaging technique, which leverages on the profitable integration of the contraction integral equation for inversion (CIE-I) and the iterative multiscaling approach (IMSA), is proposed. Thanks to the joint exploitation of the features of the CIE-I formulation and the IMSA, the arising IMSA-CIE-I inversion technique provides faithful reconstructions of complex-shaped strong scatterers with enhanced resolution and computational efficiency with respect to the state-of-the-art competitive alternatives. Numerical and experimental test cases verify the effectiveness and limitations of the proposed method