Global Optimization of Microwave Filters Based on a Surrogate Model-Assisted Evolutionary Algorithm

This paper presents two WR-3 band (220-325 GHz) filters, one fabricated in metal using high precision computer numerically controlled milling and the other made with metallized SU-8 photoresist technology. Both are based on three coupled resonators, and are designed for a 287.3-295.9-GHz passband, and a 30-dB rejection between 317.7 and 325.9 GHz. The first filter is an extracted pole filter coupled by irises, and is precision milled using the split-block approach. The second filter is composed of three silver-coated SU-8 layers, each 432 µm thick. The filter structures are specially chosen to take advantage of the fabrication processes. When fabrication tolerances are accounted for, very good agreement between measurements and simulations are obtained, with median passband insertion losses of 0.41 and 0.45 dB for the metal and SU-8 devices, respectively. These two filters are potential replacements of frequency selective surface filters used in heterodyne radiometers for unwanted sideband rejection. Index Terms-Micromachining, SU-8, terahertz components, waveguide filter. I. INTRODUCTION M ULTICHANNEL air and spaceborne sounders are employed for spectroscopic characterization of the Earth's atmosphere [1]. These instruments perform molecular spectroscopy at millimeter and submillimeter wavelengths in relatively narrow frequency channels. Within the instrument, linearly polarized signals are frequency demultiplexed by a Manuscript

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“…The above geometric design parameters, shown in Fig. 3, are optimized by the SMEAFO method [23] using CST Microwave Studio (version 2016). Fig.…”

Section: Design Of Su-8 Micromachined Filtermentioning

confidence: 99%

WR-3 Waveguide Bandpass Filters Fabricated Using High Precision CNC Machining and SU-8 Photoresist Technology

Yang

Dhayalan

Shang

et al. 2018

IEEE Trans. THz Sci. Technol.

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“…From Tables II and III, it can be observed that the differences between the initial and optimized dimensions are about 10%. Trust region framework, a local optimization algorithm [31] integrated in CST [20], is used to perform the optimization which converges fast.…”

Section: Table III Initial and Optimized Dimensions (In Millimeters)mentioning

confidence: 99%

A 135–150-GHz Frequency Tripler With Waveguide Filter Matching

Guo

Shang

Lancaster

et al. 2018

IEEE Trans. Microwave Theory Techn.

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The design and performance of a WR-5 band 135-150-GHz Schottky diode-based frequency tripler which uses waveguide resonator filters for low loss impedance matching is presented in this paper. The filters used in this paper provide filtering, impedance matching, and microstrip (MS) to waveguide transitions in one structure. The matching optimization is achieved by scaling the external quality factors and adjusting the resonance frequency of the filter cavities. This approach transfers most of the tripler's matching networks from MS circuitry to lower loss rectangular waveguide resonators. This is desirable and useful in particular for submillimeter wave and terahertz frequencies. The device presented is a 47.5 to 142.5 GHz biasless frequency tripler with a 15-GHz output bandwidth. The tripler was measured to have a conversion loss of 13.1-14 dB across the band, at an input power of 17 dBm. The measured S 11 at the input port is better than 15 dB and all the reflection zeros from the filter resonances are distinct. The good agreement between measurements and simulations verifies the accuracy of the filter-based design approach.

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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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Global Optimization of Microwave Filters Based on a Surrogate Model-Assisted Evolutionary Algorithm

Cited by 96 publications

References 27 publications

WR-3 Waveguide Bandpass Filters Fabricated Using High Precision CNC Machining and SU-8 Photoresist Technology

WR-3 Waveguide Bandpass Filters Fabricated Using High Precision CNC Machining and SU-8 Photoresist Technology

A 135–150-GHz Frequency Tripler With Waveguide Filter Matching

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

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