PIER | PIER Journals

2023-12-31

PIER

Vol. 178, 129-147, 2023

download: 586

SWE Retrieval Algorithms Based on the Parameterized BI-Continuous DMRT Model Without Priors on Grain Size or Scattering Albedo

Firoz Kanti Borah, Leung Tsang and Edward J. Kim

In this paper, we develop two new algorithms for snow water equivalent (SWE) retrieval based on the volume scattering snow at X (9.6 GHz) and Ku (17.2 GHz). Significantly, neither algorithm requires a prior on grain size or on scattering albedo. The two algorithms are based on modifications of the previous algorithm published in our previous two papers (Zhu et al. 2018, 2021). The physical model is the bi-continuous DMRT model, and a parametrization is carried out over a look-up table of DMRT results. The parameterized model gives the X and Ku band co-polarization backscatter as a pair of equations in terms of two parameters SWE and scattering albedo at X band (ω_X). By directly inverting the pair of equations for, σ^X (SWE, ω_X) and σ^Ku (SWE, ω_X), we show that there are at most a pair of solutions which have SWE values that are far apart in most cases, facilitating identification of the correct solution. The first algorithm described in this paper, labelled an algebraic algorithm, uses inversion alone and does not employ a cost function. The proposed algebraic algorithm is validated with multiple airborne data sets and three years of tower-based snow observations. The robustness of the no-prior approach was validated with the airborne observations, by using a prior SWE value that is intentionally far (75% different) from the true SWE. For the validation using tower-based data, three years of observations from the NoSREx experiment in Sodankyla, Finland were used in which the previous SWE result helps to correctly choose between the two solutions. The second cost function-based algorithm finds the SWE and ω_X pair which minimizes the difference between the observed volume scattering σ^X,obs and σ^Ku,obs and the model-predicted volume scattering σ^X,mod and σ^Ku,mod. The cost function uses prior information on SWE, also based on a time series starting with zero/low SWE. NoSREx data is used to show results from this approach. The new algorithm combined with time series eliminates needs of ancillary information of SWE and grain sizes, making the algorithm useful for level-2 products of a satellite mission.

SWE Retrieval Algorithms Based on the Parameterized Bi-continuous DMRT Model without Priors on Grain Size or Scattering Albedo

2023-12-29

PIER

Vol. 178, 111-127, 2023

doi:10.2528/PIER23082204

download: 637

Full-Wave Electromagnetic Simulations of Forests at L-Band by Using Fast Hybrid Method

Jongwoo Jeong, Leung Tsang, Andreas Colliander and Simon Yueh

Wave propagation in forests at L-band has essential applications in satellite communication system design, foliage penetration (FOPEN), and remote sensing of forest canopy and soil using passive, active, and reflectometry techniques. In this work, we propose applying the fast hybrid method (FHM) for full wave simulations of forests. The FHM significantly improves CPU time and memory efficiency for full-wave electromagnetic solutions. In this paper, we present simulations of forests of up to 72 trees with heights up to 13 m with FHM. Spatial distributions of electric fields at the bottom plane of the trees are illustrated, showing constructive and destructive interferences. The electric field distributions show that the amplitudes of the electric fields can be as large as twice that of incident waves. The transmissivities are computed and averaged over realizations based on the electric fields underneath the forest. The simulations were performed on a desktop and required a CPU time of only 1346 seconds and the memory of 16.5 GB for the case of 72 13-m tall trees, demonstrating that the FHM method is substantially more efficient than the available commercial software. The results show that the L-band signals can penetrate forests to sense the soil moisture and detect targets hidden within forests, as evidenced by significant electric field intensities under forest canopies. Also, we illustrate that GPS signals can penetrate forests and be successfully received by GPS receivers. In the study on clustering effects, we present two distinct solutions for transmissivities, each corresponding to different spatial distributions of trees while maintaining the same average tree density.

Full-wave Electromagnetic Simulations of Forests at L-band by Using Fast Hybrid Method

2023-12-08

PIER

Vol. 178, 103-110, 2023

doi:10.2528/PIER23100604

download: 785

Generalized Phase Retrieval Model Based on Physics-Inspired Network for Holographic Metasurface (Invited Paper)

Lei Jin, Jialei Xie, Baicao Pan and Guoqing Luo

Phase holographic metasurfaces encode the phase profiles of holograms in metasurfaces formed by the meta-atom arrays, and accurately modulate the field distribution in desired region. Iterative optimization methods or data-driven learning methods are used to retrieve the phase profile under the given physical setups, such as working wavelength λ, metasurfaces' period ∆x, and image distance Z. However, those methods usually repeat the optimization or training process to retrieve the phase profile for different physical setups. Here, we propose a generalized phase retrieval model (GPRM) based on physics-inspired network to retrieve the phase profile from the input λ, ∆x, Z, and desired image without retraining the neural network. The GPRM consists of deep neural network (DNN), parabolic phase, and Fresnel diffraction propagation, which is able to generate phase profile with high reconstruction quality in extraordinary broadband, such as visible, terahertz, and microwave region. By combining with corresponding meta-atom pool, the proposed method has great potential to design versatile meta-devices for image display, data encoding, and beam shaping. Furthermore, the proposed method accelerates the design of Fresnel phase hologram, which can cooperate with programmable metasurfaces to realize dynamic three-dimensional or full-color display.

Generalized Phase Retrieval Model Based on Physics-inspired Network for Holographic Metasurface (Invited paper)

Featured Article

2023-11-20

PIER

Vol. 178, 83-91, 2023

doi:10.2528/PIER23090201

download: 2046

Enabling Intelligent Metasurfaces for Semi-Known Input

Pujing Lin, Chao Qian, Jie Zhang, Jieting Chen, Xiaoyue Zhu, Zhedong Wang, Jiangtao Huangfu and Hongsheng Chen

Compelling evidence suggests that the interaction between electromagnetic metasurfaces and deep learning gives rise to the proliferation of intelligent metasurfaces in the past decade. In general, deep learning offers a transformative force to reform the design and working style of metasurfaces. A majority of the inverse-design literature announce that, given a user-defined input, the pre-trained deep learning models can quickly output the metasurface candidates with high fidelity. However, they largely ignore an important fact, that is, the practical input is always semi-known. In this work, we introduce a generation-elimination network that is robust to semi-known input and information pollution. The network is composed of a generative network to generate a number of possible answers and then a discriminative network to eliminate suboptimal answers. We benchmark the feasibility via two scenes, the on-demand metasurface design of the reflection spectra and the far-field pattern. In the microwave experiment, we fabricated and measured the reconfigurable metasurfaces to automatically meet the semi-known beam steering requirement that widely exist in wireless communication. Our work for the first time answers the question of how to cope with semi-known input, which is ubiquitous in a panoply of real-world applications, such as imaging, sensing, and communication across noisy environment.

Enabling Intelligent Metasurfaces for Semi-known Input

2023-09-25

PIER

Vol. 178, 37-47, 2023

doi:10.2528/PIER23081008

download: 1093

Polarization-Wavelength Locked Plasmonic Topological States

Yuan-Zhen Li, Zijian Zhang, Hongsheng Chen and Fei Gao

Plasmonic topological states, providing a new way to bypass the diffraction limits and against fabrication disorders, have attracted intense attention. In addition to the near-field coupling and band topology, the localized surface plasmonic resonance modes can be manipulated with far-field degrees of freedom (DoFs), such as polarization. However, changing the frequency of the topological edge states with different polarized incident waves remains a challenge, which has led to significant interest in multiplexed radiative topological devices. Here, we report the realization of polarization-wavelength locked plasmonic topological edge states on the Su-Schrieffer-Heeger (SSH) model. We theoretically and numerically show that such phenomenon is based on two mechanisms, i.e., the splitting in the spectra of plasmonic topological edge states with different intrinsic parity DoF and projecting the far-field polarizations to the parity of lattice modes. These results promise applications in robust optical emitters and multiplexed photonic devices.

Polarization-wavelength Locked Plasmonic Topological States

2023-10-01

PIER

Vol. 178, 49-62, 2023

doi:10.2528/PIER23082303

download: 881

High-Accuracy Rapid Identification and Classification of Mixed Bacteria Using Hyperspectral Transmission Microscopic Imaging and Machine Learning

He Zhu, Jing Luo, Jiaqi Liao and Sailing He

In this paper, we developed a hyperspectral transmission microscopic imaging (HTMI) system for rapid detection of pathogenic bacteria, which can realize precise identification and classification of mixed pathogenic bacteria to a single-bacterium level. The system worksin trans-illumination patterns and a self-developed dispersive hyperspectral imaging module is usedas the detection setup, providing spectral images with high SNR, and showing excellent performances with spatial resolution of 2.19 µm and spectral resolutions less than 1 nm. Hyperspectral microscopic imaging of five types of bacteria in low concentration were performed. The merging spatial-spectral profiles of individual bacteria for each species were extracted and utilized for species identification, achieving high classification accuracy of 93.6% using a simple PCA-SVM method. Species identification experiments of the mixed bacterial sampleswere further carried out, and the results demonstrate the validity and capability of the system assisted with simple machine learning methods to be used as an effective and rapid diagnostic tool for elaborate identification of mixed bacterial pathogen samples, providing guidance for the use of correct antibiotics.

High-accuracy Rapid Identification and Classification of Mixed Bacteria Using Hyperspectral Transmission Microscopic Imaging and Machine Learning

2023-07-23

PIER

Vol. 178, 1-12, 2023

doi:10.2528/PIER23040401

download: 795

Reservoir Computing and Task Performing through Using High-β Lasers with Delayed Optical Feedback

Tao Wang, Can Jiang, Qing Fang, Xingxing Guo, Yahui Zhang, Chaoyuan Jin and Shuiying Xiang

Nonlinear photonic sources including semiconductor lasers have been recently utilized as ideal computation elements for information processing. They supply energy-efficient way and rich dynamics for classification and recognition tasks. In this work, we propose and numerically study the dynamics of complex photonic systems including high-β laser element with delayed feedback and functional current modulation, and employ nonlinear laser dynamics of near-threshold region for the application in reservoir computing. The results indicate a perfect (100%) recognition accuracy for the pattern recognition task and an accuracy about 98% for the Mackey-Glass chaotic sequences prediction. Therefore, the system shows an improvement of performance with low-power consumption. In particular, the error rate is an order of magnitude smaller than previous works. Furthermore, by changing the DC pump, we are able to modify the number of spontaneous emission photons of the system, which then allows us to explore how the laser noise impacts the performance of the reservoir computing system. Through manipulating these variables, we show a deeper understanding on the proposed system, which is helpful for the practical applications of reservoir computing.

Reservoir Computing and Task Performing through Using High-β Lasers with Delayed Optical Feedback

2023-11-22

PIER

Vol. 178, 93-101, 2023

doi:10.2528/PIER23082805

download: 672

Dynamic Wireless Power Transfer System with Twin Perpendicular Receiver Coils (Invited Paper)

Heng-Ming Hsu, Bo Yang, Tai-Lai Yang, Hsin-Lin Cho and Naoki Shinohara

Wireless power transfer (WPT) with dynamic charging capabilities is a promising technology that can charge moving objects in real-time. However, maintaining high-efficiency power transfer during vehicle movement continues to be a significant challenge. To address this challenge, this study proposes a dynamic WPT system that utilizes orthogonal transmitter and receiver coils, offering the advantages of stable output power and efficiency, even when the vehicle is in motion. Unlike other systems, the proposed topology eliminates the need for a complicated feedback control system, thereby reducing hardware costs. To verify the effectiveness of the proposed topology, a dynamic WPT system was implemented in this study. Measurement results demonstrate that even when the vehicle moves a distance of 400 mm (four times the length of the receiving coil), the output voltage and power variations are only 4.9% and 9.6%, respectively.

Dynamic Wireless Power Transfer System with Twin Perpendicular Receiver Coils (Invited Paper)

2023-10-03

PIER

Vol. 178, 63-81, 2023

doi:10.2528/PIER23040504

download: 712

Linear Sampling Method Imaging of Three-Dimensional Conducting Targets from Limited Apertures via Phase-Delay-Constrained Formulations

Matthew Burfeindt and Hatim F. Alqadah

The linear sampling method (LSM) is a qualitative inverse scattering technique for reconstructing the shape of a target. It has several beneficial qualities, including the avoidance of nonlinear optimization and simplified scattering approximations. However, it often struggles when sensors can only be placed on one side of the target. In this paper, we investigate two alternative LSM formulations for overcoming the limited-aspect challenge. The first, the phase-delay frequency variation LSM (PDFV-LSM), incorporates coherent processing across frequency to improve discrimination in the range direction. The second, the phase-encoded LSM (PE-LSM), enhances the PDFV-LSM approach with a receive-beamforming operation to decrease the complexity of the inverse problem. We apply both techniques to simulated data from three-dimensional targets and three-dimensional limited-aspect arrays. We generate three-dimensional reconstructions and compare them to reconstructions from both the conventional LSM and conventional backprojection-based processing. The results demonstrate superior reconstruction fidelity for either the PDFV-LSM, the PE-LSM, or both, across a wide variety of imaging scenarios due to finer range resolution. They also demonstrate trade-offs between the two enhanced LSM techniques, with the PE-LSM achieving better range resolution and robustness to noise and the PDFV-LSM achieving better lateral resolution.

Linear Sampling Method Imaging of Three-dimensional Conducting Targets from Limited Apertures via Phase-delay-constrained Formulations

2023-08-14

PIER

Vol. 178, 18-36, 2023

doi:10.2528/PIER23042503

download: 1274

A Novel Noncontact Ku-Band Microwave Radiometer for Human Body Temperature Measurements

Hang Tian, Xiaodong Zhuge, Anyong Hu, Qingli Dou and Jungang Miao

In emergency departments and ICUs, a novel noncontact thermometer is urgently required to measure physical temperatures through common clothing to accomplish body temperature precise measurement for critical patients. Hence, a Ku band digital auto gain compensative microwave radiometer is proposed to get a higher theoretical temperature measurement sensitivity than a Dicke radiometer, benefit miniaturization design and reduce attenuation caused by common clothing. Meanwhile, a novel compensation method for receiver calibration is proposed to improve temperature sensitivity under non-ideal conditions, and the revised systematic calibration method is elaborated. Furthermore, in order to invert body physical temperatures through clothing, a microwave thermal radiation transmission model of clothed human body is constructed, and the microwave radiation apparent temperature equation of clothed human body is derived. Importantly, three groups of experiments are set up to confirm the designed radiometer's performance, especially the biological tissue temperature measurement. Results show that: 1) the designed radiometer has high temperature sensitivity and accuracy for unsheltered targets; 2) amplitude attenuation caused by cotton cloth for Ku band microwave is much smaller than that for infrared thermal radiation; 3) the designed radiometer can track physical temperatures of targets (such as water and swine skin tissue) sheltered or covered by cotton cloth relatively accurately. In conclusion, our designed Ku band microwave radiometer is certificated to have outstanding performance in temperature measurement for biological tissue through common clothing, which can be developed into a promising product in medical monitoring.