Multilayer Topology Optimization of Wideband SIW-to-Waveguide Transitions

Hassan, Emadeldeen; Scheiner, Benedict; Michler, Fabian; Berggren, Martin; Wadbro, Eddie; Rohrl, Franz Xaver; Zorn, Stefan; Weigel, Robert; Lurz, Fabian

doi:10.1109/tmtt.2019.2959759

Cited by 30 publications

(20 citation statements)

References 47 publications

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“…In contrast to this, 3D-printing tolerances and roughness limit the upper frequency bound, which will be certainly extended during the ongoing development of 3D-printing. Conventional horn antennas are available up to very high frequencies but become expensive at the same time and require a low-loss, wideband transition to the PCB [50]. The third antenna technology worth mentioning is formed by on-LTCC, on-chip and in-package antenna types.…”

Section: Antenna and Transition Designmentioning

confidence: 99%

Micrometer Sensing With Microwaves: Precise Radar Systems for Innovative Measurement Applications

et al. 2021

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Radar sensors have been widely used to estimate speed and displacement of remote targets. A novel market for contactless radar sensing is emerging in the field of automatization and process analysis, where non destructive testing and evaluation methods are desired. Here, modern radar systems offer various advantages over conventional sensors since they enable the contactless, continuous, and cost-efficient measurement of static or dynamic ranges. These can further be used for vibration and vital sign characterization. Advances in microwave technology, an increasing integration density, and the development of novel algorithms keep boosting the performance of the systems. After introducing the most common operation principles, such as unmodulated and frequency-modulated continuous-wave radar, different design aspects and building blocks of cutting-edge systems are explained in detail. In the second part, selected applications are described in detail. These include the sheet thickness monitoring of metallic foils, and the measurement of the ground speed of vehicles with the latest approaches. Exemplary low-power radar systems are presented to show the limits in terms of power consumption while still offering a high measurement precision. In addition, the topics of mechanical vibration sensing and vital sign sensing are addressed by introducing tailored systems.INDEX TERMS Radar theory, radar remote sensing, Doppler radar, radar applications.

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Section: Antenna and Transition Designmentioning

confidence: 99%

Micrometer Sensing With Microwaves: Precise Radar Systems for Innovative Measurement Applications

et al. 2021

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“…Given the aforementioned challenges, it is no surprise that the development of methods for accelerating EM-driven design procedures has been widely researched over the last decades. The available techniques include gradient-based routines expedited by adjoint sensitivities [32], [33] or sparse Jacobian updates [34], [35], as well as surrogate-assisted algorithms involving approximation models [36]- [38] and variable-fidelity simulations [39]- [41]. A representative example of the latter is space mapping [42] widely used in microwave engineering [43].…”

Section: Introductionmentioning

confidence: 99%

Improved-Efficacy Optimization of Compact Microwave Passives by Means of Frequency-Related Regularization

2020

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Electromagnetic (EM)-driven optimization is an important part of microwave design, especially for miniaturized components where the cross-coupling effects in tightly arranged layouts make traditional (e.g., equivalent network) representations grossly inaccurate. Efficient parameter tuning requires reasonably good initial designs, which are difficult to be rendered for newly developed structures or when redesign for different operating conditions or material parameters is required. If global search is needed, due to either the aforementioned issues or multi-modality of the objective function, the computational cost of the EM-driven design increases tremendously. This paper introduces a frequency-related regularization as a way of improving the efficacy of simulation-based design processes. Regularization is realized by enhancing the conventional (e.g., minimax) objective function using a dedicated penalty term that fosters the alignment of the circuit characteristics (e.g., the operating frequency or bandwidth) with the target values specified by the design requirement. This leads to smoothening of the objective function landscape, improves reliability of the optimization process, and reduces its computational cost as compared to the standard formulation. An added benefit is the increased immunity to poor initial designs and multi-modality issues. In particular, regularization can make local search routines sufficient in situations where global optimization would normally be necessary. The presented approach is validated using two miniaturized circuits, a rat-race and a branch line coupler. The numerical results demonstrate its superiority over conventional design problem formulations in terms of reliability of the optimization process. INDEX TERMS Microwave design; miniaturized passive components; design optimization; EM-driven design; gradient-based search; regularization.

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“…In this way, these methods can introduce/remove blocks and holes of material in the design space, change the shape and topology of the EM structure, and explore new possibilities for optimal design solutions [142]. EM topology optimization has been applied in the design of microwave components to achieve higher performance or more compact configurations [84]- [86].…”

Section: Review Of Em Topology Optimizationmentioning

confidence: 99%

“…EM topology optimization has been applied in the design of microwave components to achieve higher performance or more compact configurations [84]- [86]. In EM topology optimization, the entire design space is divided into many small cells and the material composition of each cell is regarded as a design variable.…”

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confidence: 99%

“…The topology optimizations in [91]- [93] deal with the presence or absence of the material in each small cell within the design space, i.e., the material properties are represented by binary variables. There are generally two types of optimization methods for the topology optimization, i.e., the gradient-based optimization method [83], [86] and the gradient-free optimization method [94]- [97]. The main advantage of the gradient-based optimization method is to converge rapidly toward the nearest local optimal solution.…”

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Advanced Neural Network Modeling and Electromagnetic Optimization Approaches for Microwave Passive Components

Jin¹

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Microwave modeling and optimization techniques play important roles in electromagnetic (EM)-based microwave component design. The purpose of this thesis is to propose advanced neural network modeling and EM optimization approaches for microwave passive components. This thesis first proposes a new deep neural network technique to solve high-dimensional microwave modeling problems which are more challenging than those solved by previous shallow neural networks. A smooth rectified linear unit (ReLU) is proposed for the new deep neural network. The proposed deep neural network employs both the sigmoid function and the smooth ReLU as activation functions. An advanced three-stage deep learning algorithm is proposed to train the new deep neural network model. This algorithm can determine the number of hidden layers with sigmoid functions and those with smooth ReLUs in the training process. It can also overcome the vanishing gradient problem for training the deep neural network. The proposed deep neural network technique can solve microwave modeling problems in higher dimension than the previous neural network method, i.e., shallow neural network method. Compared to the standard deep neural network using only ReLUs, the proposed deep neural network can achieve higher accuracy with fewer number of hidden neurons. The proposed deep neural network technique is a useful surrogate modeling technique for microwave components. Based on the investigation of the surrogate modeling technique, this thesis further studies the efficient surrogate-based EM optimization method and proposes an advanced cognition-driven EM optimization incorporating transfer function-based feature surrogate for EM geometry optimization of microwave filters. The proposed i optimization technique addresses the situations where the response at the starting point for the design optimization is substantially misaligned with the design specifications. We propose to extract transfer function-based feature parameters for optimization to address the challenge that the features cannot be clearly and explicitly identified from the filter response. Multiple transfer function-based feature parameters are extracted and used to develop the feature surrogate model for the proposed cognition-driven optimization. Furthermore, we derive new objective functions for the cognition-driven optimization directly in the feature space. The proposed cognition-driven optimization incorporating transfer function-based feature surrogate can achieve faster convergence than the existing feature-assisted EM optimization methods.Moreover, to address the EM topology optimization that our proposed cognitiondriven optimization method is not applicable, this thesis further proposes an efficient EM topology optimization technique for microwave component design. In the proposed technique, the finite element method (FEM) is used for EM simulation. We propose a new method to integrate Matrix Padé via Lanczos (MPVL) and Householder formula. The proposed method combines the advantages of MPVL and H...

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Multilayer Topology Optimization of Wideband SIW-to-Waveguide Transitions

Cited by 30 publications

References 47 publications

Micrometer Sensing With Microwaves: Precise Radar Systems for Innovative Measurement Applications

Micrometer Sensing With Microwaves: Precise Radar Systems for Innovative Measurement Applications

Improved-Efficacy Optimization of Compact Microwave Passives by Means of Frequency-Related Regularization

Advanced Neural Network Modeling and Electromagnetic Optimization Approaches for Microwave Passive Components

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