Pub Date : 2023-07-03DOI: 10.1109/PIERS59004.2023.10221544
C. Macciò, M. B. Lodi, N. Curreli, A. Melis, G. Mazzarella, M. Bozzi, A. Fanti
This work aims to advance the design of a microwave device capable of detecting, through indirect measurements, variations in the permittivity of the food materials. To this aim, a novel sensor based on double ridge waveguide configuration and a specific sample holder, to be 3D-printed, are designed. To numerically study the microwave signal propagation in the designed device and investigate its wideband performance, simulations with different food materials are performed. In particular, the complex dielectric permittivity of Carasau bread doughs, a traditional food product from Sardinia (Italy), and different distilled water-based solutions with various percentage of solutes in them, are measured with open-ended coaxial probe in the range 0.5-8.5 GHz and the acquired data are then used as material under test. The results show a good ability of the device to discriminate variations of the percentage of solute in solutions. Differences of up to 60MHz in the position of the $vert S_{11}vert$ peak and 15.8 dB in amplitude are in fact observed between adjacent curves. However, in the case of Carasau bread dough, this device was not capable of clearly discriminating variations in the percentage of ingredients used.
{"title":"A 3D-Printed Wideband Sensor for Food Complex Permittivity Estimation Based on Double Ridge Waveguide","authors":"C. Macciò, M. B. Lodi, N. Curreli, A. Melis, G. Mazzarella, M. Bozzi, A. Fanti","doi":"10.1109/PIERS59004.2023.10221544","DOIUrl":"https://doi.org/10.1109/PIERS59004.2023.10221544","url":null,"abstract":"This work aims to advance the design of a microwave device capable of detecting, through indirect measurements, variations in the permittivity of the food materials. To this aim, a novel sensor based on double ridge waveguide configuration and a specific sample holder, to be 3D-printed, are designed. To numerically study the microwave signal propagation in the designed device and investigate its wideband performance, simulations with different food materials are performed. In particular, the complex dielectric permittivity of Carasau bread doughs, a traditional food product from Sardinia (Italy), and different distilled water-based solutions with various percentage of solutes in them, are measured with open-ended coaxial probe in the range 0.5-8.5 GHz and the acquired data are then used as material under test. The results show a good ability of the device to discriminate variations of the percentage of solute in solutions. Differences of up to 60MHz in the position of the $vert S_{11}vert$ peak and 15.8 dB in amplitude are in fact observed between adjacent curves. However, in the case of Carasau bread dough, this device was not capable of clearly discriminating variations in the percentage of ingredients used.","PeriodicalId":354610,"journal":{"name":"2023 Photonics & Electromagnetics Research Symposium (PIERS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131008190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-03DOI: 10.1109/PIERS59004.2023.10221454
L. Cerman, O. Sadílek, V. Hebelka
The article deals with the waveform total harmonic distortion (THD) analysis at the multilevel converter output under selected conditions. The simulations results take into account the influence of the converter topology, the number of converter levels and the phase shift in the individual branches of single-phase multilevel converters, the switching frequency and the type of PWM. The converter simulation also considers specific traffic situations with a subsequent evaluation of the investigated quantities influence. The analysis aim can be summarized in finding the ideal configuration of the output converter from the THD point of view.
{"title":"THD Analysis of Converter Power Station 25 kV 50 Hz","authors":"L. Cerman, O. Sadílek, V. Hebelka","doi":"10.1109/PIERS59004.2023.10221454","DOIUrl":"https://doi.org/10.1109/PIERS59004.2023.10221454","url":null,"abstract":"The article deals with the waveform total harmonic distortion (THD) analysis at the multilevel converter output under selected conditions. The simulations results take into account the influence of the converter topology, the number of converter levels and the phase shift in the individual branches of single-phase multilevel converters, the switching frequency and the type of PWM. The converter simulation also considers specific traffic situations with a subsequent evaluation of the investigated quantities influence. The analysis aim can be summarized in finding the ideal configuration of the output converter from the THD point of view.","PeriodicalId":354610,"journal":{"name":"2023 Photonics & Electromagnetics Research Symposium (PIERS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131050807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-03DOI: 10.1109/PIERS59004.2023.10221296
Y. Yan, B. Zhang, Shigu Cao
With nonlinear effects in the electromechanical oscillators, subharmonic oscillations can be generated, whose period is multiple that of the driving signal. Such oscillations possess multiple states with identical amplitude and evenly offset phases. Their phases can be used to encode information which was proposed early to half a century ago with the name “Parametron.” Until recently, the oscillations with a period tripled that of the drive just realized through enhanced energy transfer between the modes with a ratio of eigenfrequencies close to 1: 3 in the micro-scale mechanical resonator. In this paper, we demonstrate a well-designed structure of a nano-scale GaAs beam resonator that can generate period-tripled subharmonic oscillations through the mode coupling at 1: 3 internal resonances using numerical simulation and theoretical analysis. The generated states can be used to encode and store information on a base-3 basis. Similar to the micro-scale counterpart, for encoding, an extra excitation pulse is required. By changing its phase, the resonator can switch among the stable states. Furthermore, multiple sets of period-tripled states can be generated via different excitation schemes or non-linear effects. This design has a smaller size, lower energy consumption, and higher operating frequency in comparison with the micro-scale resonators, which favors the practical applications of the mechanical-based many-valued logic elements.
{"title":"Many-Valued Logic-Memory Elements Based on Nano-Scale Electromechanical Oscillators","authors":"Y. Yan, B. Zhang, Shigu Cao","doi":"10.1109/PIERS59004.2023.10221296","DOIUrl":"https://doi.org/10.1109/PIERS59004.2023.10221296","url":null,"abstract":"With nonlinear effects in the electromechanical oscillators, subharmonic oscillations can be generated, whose period is multiple that of the driving signal. Such oscillations possess multiple states with identical amplitude and evenly offset phases. Their phases can be used to encode information which was proposed early to half a century ago with the name “Parametron.” Until recently, the oscillations with a period tripled that of the drive just realized through enhanced energy transfer between the modes with a ratio of eigenfrequencies close to 1: 3 in the micro-scale mechanical resonator. In this paper, we demonstrate a well-designed structure of a nano-scale GaAs beam resonator that can generate period-tripled subharmonic oscillations through the mode coupling at 1: 3 internal resonances using numerical simulation and theoretical analysis. The generated states can be used to encode and store information on a base-3 basis. Similar to the micro-scale counterpart, for encoding, an extra excitation pulse is required. By changing its phase, the resonator can switch among the stable states. Furthermore, multiple sets of period-tripled states can be generated via different excitation schemes or non-linear effects. This design has a smaller size, lower energy consumption, and higher operating frequency in comparison with the micro-scale resonators, which favors the practical applications of the mechanical-based many-valued logic elements.","PeriodicalId":354610,"journal":{"name":"2023 Photonics & Electromagnetics Research Symposium (PIERS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133124812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-03DOI: 10.1109/PIERS59004.2023.10221405
U. Kose, M. Kartal
In this paper, a hybrid sensor composed of a frequency selective surface (FSS) and microstrip patch antenna is investigated numerically for non-invasive glucose sensing in the microwave region. The sensing method relies on detecting changes in the dielectric constant of the sample under test (SUT) in response to variations in the concentration of glucose-deionized water solutions. The SUT consists of the area between the microstrip patch antenna and FSS. Four glucose-deionized water solutions (i.e., 72 mg/dL, 216 mg/dL, 330 mg/dL, and 600 mg/dL) are tested in the SUT. The dielectric properties of the solutions are determined using the Debye model. For the sensitivity analyses, the return losses $(vert S_{11}vert (text{dB}))$ of the proposed sensor and the dependence of the resonance frequencies on the volume percentage of glucose in glucose-deionized water solutions have been noted. When the glucose-deionized water solutions changed from 72 mg/dL to 600 mg/dL, the resonance frequency of the sensor blue shifted from 11.281 GHz to 11.296 GHz. The sensitivity of the glucose sensor is calculated by absolute resonance frequency shift in response to glucose-deionized water solution concentration change. When the FSS structure is removed from the hybrid sensor (i.e., the sensor structure has consisted of just an antenna), the sensitivity value drops from 28.409 kHz/mg dL-1 to 18.939 kHz/mg dL-1 (i.e., 33.3%). Furthermore, the sensitivity of the sensor obtained by removing the antenna part from the hybrid sensor (i.e., the sensor consisting only of FSS) is calculated as 15.152 kHz/mg dL-1 in simulations. The results show that the proposed hybrid sensor structure exhibits heightened sensitivity compared to sensors solely reliant on antennas or FSS structures. This proposed novel hybrid sensor structure that is lightweight, low-cost, easy-to-fabricate, portable, and easy to integrate with microwave-integrated circuits will contribute to the non-invasive glucose sensor literature.
{"title":"Non-Invasive Microwave Glucose Sensor by Using a Hybrid Sensor Composed of a Frequency Selective Surface and Microstrip Patch Antenna","authors":"U. Kose, M. Kartal","doi":"10.1109/PIERS59004.2023.10221405","DOIUrl":"https://doi.org/10.1109/PIERS59004.2023.10221405","url":null,"abstract":"In this paper, a hybrid sensor composed of a frequency selective surface (FSS) and microstrip patch antenna is investigated numerically for non-invasive glucose sensing in the microwave region. The sensing method relies on detecting changes in the dielectric constant of the sample under test (SUT) in response to variations in the concentration of glucose-deionized water solutions. The SUT consists of the area between the microstrip patch antenna and FSS. Four glucose-deionized water solutions (i.e., 72 mg/dL, 216 mg/dL, 330 mg/dL, and 600 mg/dL) are tested in the SUT. The dielectric properties of the solutions are determined using the Debye model. For the sensitivity analyses, the return losses $(vert S_{11}vert (text{dB}))$ of the proposed sensor and the dependence of the resonance frequencies on the volume percentage of glucose in glucose-deionized water solutions have been noted. When the glucose-deionized water solutions changed from 72 mg/dL to 600 mg/dL, the resonance frequency of the sensor blue shifted from 11.281 GHz to 11.296 GHz. The sensitivity of the glucose sensor is calculated by absolute resonance frequency shift in response to glucose-deionized water solution concentration change. When the FSS structure is removed from the hybrid sensor (i.e., the sensor structure has consisted of just an antenna), the sensitivity value drops from 28.409 kHz/mg dL-1 to 18.939 kHz/mg dL-1 (i.e., 33.3%). Furthermore, the sensitivity of the sensor obtained by removing the antenna part from the hybrid sensor (i.e., the sensor consisting only of FSS) is calculated as 15.152 kHz/mg dL-1 in simulations. The results show that the proposed hybrid sensor structure exhibits heightened sensitivity compared to sensors solely reliant on antennas or FSS structures. This proposed novel hybrid sensor structure that is lightweight, low-cost, easy-to-fabricate, portable, and easy to integrate with microwave-integrated circuits will contribute to the non-invasive glucose sensor literature.","PeriodicalId":354610,"journal":{"name":"2023 Photonics & Electromagnetics Research Symposium (PIERS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127065334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-03DOI: 10.1109/PIERS59004.2023.10221533
Chuanbao Du, Congguang Mao, Zheng Liu, Xin Nie, Wei Wu
How to predict the characteristics of high power electromagnetic (HPEM) environment surrounding the electronic victims is of vital importance for taking effective activities to be protected. Hence, this article tried to utilize the measured antenna response data excited by HPEM to predict the electric field wave of HPEM according to the combination of the system identification model and artificial intelligence method. The train and test data are generated by MoM method, which takes simple line antenna as the targeted antenna and double-exponential waves with multiple parameters as HPEM environments respectively. The classical system identi-fication method output-error (OE) model and nonlinear autoregressive model with external input (NARX) neural network (NARX-NN) are introduced to establish the inverse model of the trans-fer function from current response to HPEM. The OE prediction accuracy 68% and NARX-NN's 72.4% demonstrate that it is feasible to predict HPEM environment by using antenna response test data.
{"title":"Feasibility Analysis of the Prediction of High Power Electromagnetic Environment from Antenna Current Response","authors":"Chuanbao Du, Congguang Mao, Zheng Liu, Xin Nie, Wei Wu","doi":"10.1109/PIERS59004.2023.10221533","DOIUrl":"https://doi.org/10.1109/PIERS59004.2023.10221533","url":null,"abstract":"How to predict the characteristics of high power electromagnetic (HPEM) environment surrounding the electronic victims is of vital importance for taking effective activities to be protected. Hence, this article tried to utilize the measured antenna response data excited by HPEM to predict the electric field wave of HPEM according to the combination of the system identification model and artificial intelligence method. The train and test data are generated by MoM method, which takes simple line antenna as the targeted antenna and double-exponential waves with multiple parameters as HPEM environments respectively. The classical system identi-fication method output-error (OE) model and nonlinear autoregressive model with external input (NARX) neural network (NARX-NN) are introduced to establish the inverse model of the trans-fer function from current response to HPEM. The OE prediction accuracy 68% and NARX-NN's 72.4% demonstrate that it is feasible to predict HPEM environment by using antenna response test data.","PeriodicalId":354610,"journal":{"name":"2023 Photonics & Electromagnetics Research Symposium (PIERS)","volume":"237 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115392037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-03DOI: 10.1109/PIERS59004.2023.10221510
Junas Haidi, A. Munir
This paper deals with the incorporation of complimentary split ring resonators (CSRRs) for enhancing bandwidth of SIW bandpass filter. The proposed filter which is designed and deployed on a 1.524mm thick Rogers 4003C dielectric substrate is intended to operate at the center frequency of 3.5 GHz. In order to attain the filter with a wide bandwidth response, an array of 14 CSRRs is incorporated on the SIW surface and arranged in a certain configuration to improve the mutual coupling. The incorporation of CSRR is also utilized to enhance the filter performance in gaining the reflection coefficient value. Based on the optimum design result, the configuration of SIW bandpass filter with CSRR incorporation is then fabricated and experimentally characterized. The measurement result shows that the realized SIW bandpass filter with CSRRs incorporation works at the center frequency of 3.38 GHz with the bandwidth of 1.24 GHz, or the fractional bandwidth $(f_{text{BW}})$ of 36.7%. This achievement is wider than the conventional one which has the second center frequency of 4.29 GHz with the bandwidth of 0.48 GHz, or $f_{text{BW}}$ of 11.2%. In addition, loading CSRRs into SIW bandpass filter can improve the reflection coefficient value more than 5 dB at its passband frequency range.
{"title":"Incorporation of CSRRs for Bandwidth Enhancement of SIW Bandpass Filter","authors":"Junas Haidi, A. Munir","doi":"10.1109/PIERS59004.2023.10221510","DOIUrl":"https://doi.org/10.1109/PIERS59004.2023.10221510","url":null,"abstract":"This paper deals with the incorporation of complimentary split ring resonators (CSRRs) for enhancing bandwidth of SIW bandpass filter. The proposed filter which is designed and deployed on a 1.524mm thick Rogers 4003C dielectric substrate is intended to operate at the center frequency of 3.5 GHz. In order to attain the filter with a wide bandwidth response, an array of 14 CSRRs is incorporated on the SIW surface and arranged in a certain configuration to improve the mutual coupling. The incorporation of CSRR is also utilized to enhance the filter performance in gaining the reflection coefficient value. Based on the optimum design result, the configuration of SIW bandpass filter with CSRR incorporation is then fabricated and experimentally characterized. The measurement result shows that the realized SIW bandpass filter with CSRRs incorporation works at the center frequency of 3.38 GHz with the bandwidth of 1.24 GHz, or the fractional bandwidth $(f_{text{BW}})$ of 36.7%. This achievement is wider than the conventional one which has the second center frequency of 4.29 GHz with the bandwidth of 0.48 GHz, or $f_{text{BW}}$ of 11.2%. In addition, loading CSRRs into SIW bandpass filter can improve the reflection coefficient value more than 5 dB at its passband frequency range.","PeriodicalId":354610,"journal":{"name":"2023 Photonics & Electromagnetics Research Symposium (PIERS)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115944206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-03DOI: 10.1109/PIERS59004.2023.10221538
Mario Del Prete
In this paper, the problem of planar phased array antenna diagnostics from near-field measurements is addressed by a Time Reversal-MUltiple SIgnal Classification (TR-MUSIC) based algorithm using a steering diversity. It is shown that the number of degrees of freedom limits the diagnostic scenarios in which the TR-MUSIC works. A difference model allows to overcome this limitation and at the same time can reduce the data required for diagnostics. Finally, numerical examples show the effectiveness of the proposed method.
{"title":"Phased Array Diagnostics by TR-MUSIC Approach by a Reduced Set of Measurements","authors":"Mario Del Prete","doi":"10.1109/PIERS59004.2023.10221538","DOIUrl":"https://doi.org/10.1109/PIERS59004.2023.10221538","url":null,"abstract":"In this paper, the problem of planar phased array antenna diagnostics from near-field measurements is addressed by a Time Reversal-MUltiple SIgnal Classification (TR-MUSIC) based algorithm using a steering diversity. It is shown that the number of degrees of freedom limits the diagnostic scenarios in which the TR-MUSIC works. A difference model allows to overcome this limitation and at the same time can reduce the data required for diagnostics. Finally, numerical examples show the effectiveness of the proposed method.","PeriodicalId":354610,"journal":{"name":"2023 Photonics & Electromagnetics Research Symposium (PIERS)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114985998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-03DOI: 10.1109/PIERS59004.2023.10221515
F. Giovanneschi, A. Ramesh, Maria Antonia Gonzalez Huici, Erdem Altuntac
The interest in LiDAR sensors for autonomous driving applications has recently increased: solid state architectures have made it possible to reduce sizes and costs while maintaining higher scanning resolution compared to RADAR sensors. In a dynamic automotive scenario, LiDAR depth measurements result in a discrete point cloud which is typically sparse and may contain irregular/missing depth information, moreover, one may further reduce the illuminated pixels to increase the scanning rate and reduce computational cost. Here, a novel application of both a patch based and a convolutional sparse coding (CSC) approach for LiDAR depth completion are presented and validated using the publicly available KITTI dataset of outdoor automotive scenarios. Patch-based sparse coding approach may result inaccurate in representing global image features and edges, especially when the missing data percentage is high. CSC allows to process the data globally while still preserving local information by constructing the dictio-nary as a concatenation of convolutional filters. The dictionary considered for both approaches is either composed of Daubechies Wavelets or learned from depth images of the urban SYNTHIA dataset using K-SVD and Convolutional Dictionary Learning (CDL) strategies. Resulting depth maps using the CSC based approach for various sparsity levels produce smooth images and an enhanced scenario awareness. An analysis based on the Sparse Mean Absolute Error (SMAE) and Weighted Mean Absolute Error (WMAE) indicates that depth and edge preservation improves with respect to patch-based strategies.
{"title":"Convolutional Sparse Coding and Dictionary Learning for Lidar Depth Completion in Automotive Scenarios","authors":"F. Giovanneschi, A. Ramesh, Maria Antonia Gonzalez Huici, Erdem Altuntac","doi":"10.1109/PIERS59004.2023.10221515","DOIUrl":"https://doi.org/10.1109/PIERS59004.2023.10221515","url":null,"abstract":"The interest in LiDAR sensors for autonomous driving applications has recently increased: solid state architectures have made it possible to reduce sizes and costs while maintaining higher scanning resolution compared to RADAR sensors. In a dynamic automotive scenario, LiDAR depth measurements result in a discrete point cloud which is typically sparse and may contain irregular/missing depth information, moreover, one may further reduce the illuminated pixels to increase the scanning rate and reduce computational cost. Here, a novel application of both a patch based and a convolutional sparse coding (CSC) approach for LiDAR depth completion are presented and validated using the publicly available KITTI dataset of outdoor automotive scenarios. Patch-based sparse coding approach may result inaccurate in representing global image features and edges, especially when the missing data percentage is high. CSC allows to process the data globally while still preserving local information by constructing the dictio-nary as a concatenation of convolutional filters. The dictionary considered for both approaches is either composed of Daubechies Wavelets or learned from depth images of the urban SYNTHIA dataset using K-SVD and Convolutional Dictionary Learning (CDL) strategies. Resulting depth maps using the CSC based approach for various sparsity levels produce smooth images and an enhanced scenario awareness. An analysis based on the Sparse Mean Absolute Error (SMAE) and Weighted Mean Absolute Error (WMAE) indicates that depth and edge preservation improves with respect to patch-based strategies.","PeriodicalId":354610,"journal":{"name":"2023 Photonics & Electromagnetics Research Symposium (PIERS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116321626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-03DOI: 10.1109/PIERS59004.2023.10221318
Yibin Ren, Xiaofeng Li, Yanyuan Huang
Accurate classification of different types of Arctic sea ice is crucial for safe marine navigation. Synthetic aperture radar (SAR) images are widely used for this purpose, but the backscattering coefficient intensity, which is critical for sea ice classification accuracy, is influenced by the incident angle (IA) of the SAR image. In this study, we investigated the impact of SAR IA on sea ice classification using a U-Net deep learning model. We collected 14 Sentinel-1 A/B Extended Wide (EW) mode images as testing datasets and conducted sensitivity experiments to compare the accuracy of sea ice classification with and without IA input, as well as with SAR images after IA correction. Our results indicate that the highest classification accuracy was achieved with SAR images that underwent IA correction as the model's input. Therefore, it is essential to correct the SAR images with IA in the sea ice classification model based on deep learning to improve the accuracy of sea ice type identification.
{"title":"Evaluating the Effect of Incident Angle on Sea Ice Classification in SAR Images Based on a Deep Learning Model","authors":"Yibin Ren, Xiaofeng Li, Yanyuan Huang","doi":"10.1109/PIERS59004.2023.10221318","DOIUrl":"https://doi.org/10.1109/PIERS59004.2023.10221318","url":null,"abstract":"Accurate classification of different types of Arctic sea ice is crucial for safe marine navigation. Synthetic aperture radar (SAR) images are widely used for this purpose, but the backscattering coefficient intensity, which is critical for sea ice classification accuracy, is influenced by the incident angle (IA) of the SAR image. In this study, we investigated the impact of SAR IA on sea ice classification using a U-Net deep learning model. We collected 14 Sentinel-1 A/B Extended Wide (EW) mode images as testing datasets and conducted sensitivity experiments to compare the accuracy of sea ice classification with and without IA input, as well as with SAR images after IA correction. Our results indicate that the highest classification accuracy was achieved with SAR images that underwent IA correction as the model's input. Therefore, it is essential to correct the SAR images with IA in the sea ice classification model based on deep learning to improve the accuracy of sea ice type identification.","PeriodicalId":354610,"journal":{"name":"2023 Photonics & Electromagnetics Research Symposium (PIERS)","volume":"162 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117080934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-03DOI: 10.1109/PIERS59004.2023.10221441
Renzhou Gui, Aobo Zhang, Shuai Liu, M. Tong
There are biological noises such as blood pressure, respiration and heartbeat in fMRI signals, and some existing methods remove these fundamental noises, but the effect of venous vessels in the brain is often neglected. The venous effect interferes with the extraction of blood oxygen signals from brain activity and can cause peak shift and trailing of the HRF(hemodynamic response function), and improving the spatial resolution of fMRI requires eliminating the effect of venous effect. The existing methods to address the venous effect are still imperfect, and most of the existing methods to address the venous effect are done from source acquisition of fMRI data, which is demanding on equipment and costly in time. The difficulty lies in eliminating the effect on BOLD(blood oxygenation level dependent) signals at the data level without increasing the time cost using signal processing methods. It is proposed to extract data from different spatial layers and at different brain depths, ranging from the surface of the soft cerebrum to the junction of the gray matter white matter, with data covering the location of the large veins. After the onset of external experimental stimulation, the effect of venous effects is attenuated by a data-driven approach with HRF peak correction for data points in the ventricles affected by venous vessels.
{"title":"A Filter Approach to Attenuate the Effects of Venous Effects in Task-based fMRI Data","authors":"Renzhou Gui, Aobo Zhang, Shuai Liu, M. Tong","doi":"10.1109/PIERS59004.2023.10221441","DOIUrl":"https://doi.org/10.1109/PIERS59004.2023.10221441","url":null,"abstract":"There are biological noises such as blood pressure, respiration and heartbeat in fMRI signals, and some existing methods remove these fundamental noises, but the effect of venous vessels in the brain is often neglected. The venous effect interferes with the extraction of blood oxygen signals from brain activity and can cause peak shift and trailing of the HRF(hemodynamic response function), and improving the spatial resolution of fMRI requires eliminating the effect of venous effect. The existing methods to address the venous effect are still imperfect, and most of the existing methods to address the venous effect are done from source acquisition of fMRI data, which is demanding on equipment and costly in time. The difficulty lies in eliminating the effect on BOLD(blood oxygenation level dependent) signals at the data level without increasing the time cost using signal processing methods. It is proposed to extract data from different spatial layers and at different brain depths, ranging from the surface of the soft cerebrum to the junction of the gray matter white matter, with data covering the location of the large veins. After the onset of external experimental stimulation, the effect of venous effects is attenuated by a data-driven approach with HRF peak correction for data points in the ventricles affected by venous vessels.","PeriodicalId":354610,"journal":{"name":"2023 Photonics & Electromagnetics Research Symposium (PIERS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123912816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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