Radio Science最新文献_第4页

Adaptive moment estimation for polarimetric weather radar using explainable deep learning-based estimators 基于可解释深度学习的极化气象雷达自适应矩估计

IF 1.6 4区地球科学

Radio Science Pub Date : 2025-06-01 DOI: 10.1029/2025RS008266

Zhe Li;Yuechen Wu;Guifu Zhang

{"title":"Adaptive moment estimation for polarimetric weather radar using explainable deep learning-based estimators","authors":"Zhe Li;Yuechen Wu;Guifu Zhang","doi":"10.1029/2025RS008266","DOIUrl":"https://doi.org/10.1029/2025RS008266","url":null,"abstract":"This paper presents machine learning-based approaches to improve moment estimation for polarimetrie weather radar. A novel weighted multilag estimator (WMLE) is proposed, with adaptively learned weights optimized using deep learning techniques. Two approaches of multilayer perceptron (MLP) and convolutional neural network (CNN) are used to implement WMLE. The performance of WMLE is evaluated using the measurements from the Next-Generation Weather Radar (NEXRAD) system. Experimental results demonstrate that the WMLE significantly improves polarimetric data quality, achieving lower root mean square error and standard deviation compared to conventional 0-Lag and 1-Lag estimators. In addition, the CNN-based estimator surpasses its MLP counterpart by leveraging spatial information in the input data and producing content-aware dynamic adaptive weights. Furthermore, the CNN-based estimator achieves superior radar data quality using data from only 32 pulses, compared with the 0-Lag and 1-Lag estimators using 64 pulses. Moreover, the CNN model demonstrates physical explainability, as its learned weights exhibit meaningful correlations with the characteristics of NEXRAD data.","PeriodicalId":49638,"journal":{"name":"Radio Science","volume":"60 6","pages":"1-15"},"PeriodicalIF":1.6,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144550376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MCSEM induction-polarization anomaly identification based on two-scale feature extraction network and XGBoost 基于双尺度特征提取网络和XGBoost的MCSEM感应极化异常识别

IF 1.6 4区地球科学

Radio Science Pub Date : 2025-06-01 DOI: 10.1029/2024RS008194

Chunying Gu;Suyi Li;Silun Peng

{"title":"MCSEM induction-polarization anomaly identification based on two-scale feature extraction network and XGBoost","authors":"Chunying Gu;Suyi Li;Silun Peng","doi":"10.1029/2024RS008194","DOIUrl":"https://doi.org/10.1029/2024RS008194","url":null,"abstract":"Due to the presence of induced polarization effect in subsea reservoirs, marine controlled-source electromagnetic (MCSEM) data contain induction response and polarization response. The traditional magnitude versus offset (MVO) curve makes it difficult to manually identify the induction-polarization anomalies contaminated by noise, which leads to the reduction of anomaly resolution and affects the accuracy of data interpretation. Machine learning models possess strong feature extraction and classification ability, which can obtain probabilistic anomaly classification results. Therefore, this study proposes an induction-polarization anomaly identification method based on a two-scale feature extraction network (TFEN) combined with XGBoost algorithm. First, MCSEM induction-polarization theoretical data are calculated using the Cole-Cole model, with random noise added to simulate noisy field data. Then, to effectively fuse muli-scale features while maintaining computational efficiency, a TFEN model is constructed. This model employs long short-term memory and dilated convolution to automatically extract the two-scale nonlinear features from induction-polarization data, followed by feature fusion. Finally, the identification of MCSEM induction-polarization data is realized using the XGBoost. The results show that TFEN-XGBoost achieves the highest anomaly identification accuracy compared with Random Forest, TFEN alone, and XGBoost alone. When the MVO curve fails to distinguish induction-polarization anomalies, the TFEN-XGBoost model achieves a recognition accuracy of 95.89% on theoretical data and 88.93% on noisy data sets. This demonstrates that the combined TFEN-XGBoost model can effectively identify induction-polarization anomalies, providing important technical support for oil resource exploration based on MCSEM.","PeriodicalId":49638,"journal":{"name":"Radio Science","volume":"60 6","pages":"1-14"},"PeriodicalIF":1.6,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144550154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Strategy for WiFi interference detection in weather radar applications 气象雷达应用中WiFi干扰检测策略

IF 1.6 4区地球科学

Radio Science Pub Date : 2025-06-01 DOI: 10.1029/2025RS008232

Andy Moreno Rodríguez;Jorge Cogo;Juan Pablo Pascual

{"title":"Strategy for WiFi interference detection in weather radar applications","authors":"Andy Moreno Rodríguez;Jorge Cogo;Juan Pablo Pascual","doi":"10.1029/2025RS008232","DOIUrl":"https://doi.org/10.1029/2025RS008232","url":null,"abstract":"In the current context of intensive spectrum use by communications systems, WiFi systems have been allowed to use bands previously reserved for weather radars, as opportunity users. Some drawbacks in spectrum management make WiFi systems a source of interference that degrades the quality of observables obtained by C-band weather radars. In this work we present a strategy to detect these interfering WiFi packets at the output signal of the radar matched filter. The strategy is based on a delay and correlate algorithm that exploits the periodic structure of the WiFi packets preamble, periodicity that remains unchanged even though the signal is distorted when passing through the radar reception stages. We formulate the detection strategy as a hypothesis test that uses the squared modulus of the auto-correlation as the statistic, extended to a constant false alarm (CFAR) formulation to cope with the unknown noise power. We evaluate analytically and through numerical simulations the performance of the test in terms of detection probability. We also perform a series of controlled experiments using real-world weather radar data collected by Argentinian C-band RMA radars. The results show a high detection rate both when WiFi interference is in regions where there is only noise and when it is in regions where there is also a meteorological target.","PeriodicalId":49638,"journal":{"name":"Radio Science","volume":"60 6","pages":"1-9"},"PeriodicalIF":1.6,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144550182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A broadband gain-enhanced metasurface-based circularly polarized patch antenna for WLAN application 一种用于WLAN的宽带增益增强超表面圆极化贴片天线

IF 1.6 4区地球科学

Radio Science Pub Date : 2025-06-01 DOI: 10.1029/2024RS008063

Deepak Ram;Amit Kumar Singh;Somak Bhattacharyya

{"title":"A broadband gain-enhanced metasurface-based circularly polarized patch antenna for WLAN application","authors":"Deepak Ram;Amit Kumar Singh;Somak Bhattacharyya","doi":"10.1029/2024RS008063","DOIUrl":"https://doi.org/10.1029/2024RS008063","url":null,"abstract":"This article presents a broadband gain-enhanced circularly polarized (CP) microstrip patch antenna based on metasurface (MS). A truncated corner square patch with a cross-shaped slot has been employed as the host antenna, configured on a 1.6 mm thick FR-4 substrate backed by a copper ground plane. The MS layer consisting of a 4 × 4 square array has been designed on another 1.6 mm thick FR-4 substrate with identical outer dimensions acting as a superstrate layer. The proposed antenna exhibits a — 10-dB reflection coefficient bandwidth spanning from 4.37 to 7.03 GHz (46.67%), along with a 3-dB axial ratio (AR) bandwidth from 5.13 to 5.78 GHz (12%). At 5.3 GHz, the antenna exhibits a maximum realized gain of 6.8 dBic. Furthermore, polarization of the antenna is characterized as left-handed circularly polarized. To verify the impedance response, an equivalent circuit model of the antenna has been developed step-by-step followed by fabrication of the prototype. The measured results show high degree of similarity with the simulated responses. Being low profile (0.56λ<inf>o</inf> × 0.56λ<inf>o</inf> × 0.028λ<inf>o</inf> at 5.3 GHz), the proposed CP antenna can be utilized for applications of WLAN, Wi-Fi wireless computer networks etc.","PeriodicalId":49638,"journal":{"name":"Radio Science","volume":"60 6","pages":"1-13"},"PeriodicalIF":1.6,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144550375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Front matters 前面问题

IF 1.6 4区地球科学

Radio Science Pub Date : 2025-06-01 DOI: 10.1002/rds.21330

引用次数: 0

Rectenna design optimized by binary genetic algorithm for hybrid energy harvesting applications across 5G sub-6 GHz band 采用二进制遗传算法优化的整流天线设计，用于5G sub- 6ghz频段的混合能量收集应用

IF 1.6 4区地球科学

Radio Science Pub Date : 2025-06-01 DOI: 10.1029/2024RS008154

Ahmed Rifaat Hamad;Ammar Al-Adhami;Nouf Abd Elmunim;Mohammad Alibakhshikenari;Bal Virdee;Hasan Salman Hamad;Renu Jayanthi;Dion Mariyanayagam;Innocent Lubangakene;Sunil Kumar;Salahuddin Khan;Yi Tang;Lida Kouhalvandi;Taha A. Elwi;Mohsin Ali Ahmed;Nasr Rashid

{"title":"Rectenna design optimized by binary genetic algorithm for hybrid energy harvesting applications across 5G sub-6 GHz band","authors":"Ahmed Rifaat Hamad;Ammar Al-Adhami;Nouf Abd Elmunim;Mohammad Alibakhshikenari;Bal Virdee;Hasan Salman Hamad;Renu Jayanthi;Dion Mariyanayagam;Innocent Lubangakene;Sunil Kumar;Salahuddin Khan;Yi Tang;Lida Kouhalvandi;Taha A. Elwi;Mohsin Ali Ahmed;Nasr Rashid","doi":"10.1029/2024RS008154","DOIUrl":"https://doi.org/10.1029/2024RS008154","url":null,"abstract":"This paper presents a novel rectenna design for hybrid energy harvesting, optimized using a binary genetic algorithm (BGA) with binary coding to improve geometry, impedance matching, and radiation efficiency. The fabricated rectenna achieves reflection coefficients below −40 dB at 2.45 and 5.8 GHz, demonstrating excellent impedance matching. A commercial rectifier (Powercast P21XXCSR-EVB), employing a voltage doubler topology and Schottky diodes (Skyworks SMS7630 and Avago HSMS 285B), is integrated for RF-to-DC conversion. Peak efficiencies of 90% at 2.45 GHz and 52% at 5.8 GHz are recorded at 11 dBm input power, while efficiencies above 80% and 50%, respectively, are maintained at 0 dBm. The rectifier also exhibits wide impedance bandwidths, with reflection coefficients of − 23 dB and −18 dB at the respective frequencies. Outdoor testing yields DC output voltages of 92.6 mV (2.45 GHz) and 64 mV (5.8 GHz). The system's efficiency and adaptability under variable conditions make it ideal for low-power applications such as wireless sensor networks, Internet of Things devices, and remote monitoring. Its robust performance across environments highlights its potential for autonomous energy harvesting in 5G and sub-6 GHz networks.","PeriodicalId":49638,"journal":{"name":"Radio Science","volume":"60 6","pages":"1-15"},"PeriodicalIF":1.6,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144550297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Path loss prediction for vehicle-to-infrastructure communications via synesthesia of machines (SoM) 基于机器联觉（SoM）的车辆与基础设施通信路径损失预测

IF 1.6 4区地球科学

Radio Science Pub Date : 2025-06-01 DOI: 10.1029/2024RS008187

Mengyuan Lu;Lu Bai;Ziwei Huang;Mi Yang;Xiang Cheng

{"title":"Path loss prediction for vehicle-to-infrastructure communications via synesthesia of machines (SoM)","authors":"Mengyuan Lu;Lu Bai;Ziwei Huang;Mi Yang;Xiang Cheng","doi":"10.1029/2024RS008187","DOIUrl":"https://doi.org/10.1029/2024RS008187","url":null,"abstract":"In this paper, a new real-time path loss prediction model based on multi-modal sensory data is proposed to enhance the accuracy of path loss prediction in vehicular communication scenarios. A new multimodal data set containing communication and sensory data is constructed based on simulation platforms. The data set is constructed for intelligent sensing-communication integration in urban vehicular crossroads scenarios. Based on the constructed data set, the mapping relationship between physical space and electromagnetic space is explored. Furthermore, path loss prediction is achieved with environmental information via multi-modal sensory data. Simulation results show that the proposed path loss prediction model is validated, which achieves a mean squared error of 1.9283 × 10<sup>−6</sup>. The proposed model improves the accuracy by 2 orders of magnitude over 3GPP TR 38.901 channel models. Compared to the artificial neural network, support vector regression, random forest, and gradient tree boosting, the proposed model achieves the highest accuracy. Finally, the effectiveness of multi-modal sensory data fusion in path loss prediction for vehicular communication scenarios is validated, which shows a 19.8% improvement in accuracy compared to predictions based on uni-modal data.","PeriodicalId":49638,"journal":{"name":"Radio Science","volume":"60 6","pages":"1-15"},"PeriodicalIF":1.6,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144550299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Isolation enhancement in H-plane coupled 5G MIMO antenna with tight spacing using miniaturized epsilon negative (ENG) metamaterial 小型化负epsilon （ENG）超材料增强h平面耦合5G MIMO天线的隔离

IF 1.6 4区地球科学

Radio Science Pub Date : 2025-06-01 DOI: 10.1029/2024RS008171

R. K. Rabin Kanisha;C. Rimmya

{"title":"Isolation enhancement in H-plane coupled 5G MIMO antenna with tight spacing using miniaturized epsilon negative (ENG) metamaterial","authors":"R. K. Rabin Kanisha;C. Rimmya","doi":"10.1029/2024RS008171","DOIUrl":"https://doi.org/10.1029/2024RS008171","url":null,"abstract":"A novel miniaturized epsilon negative metamaterial is proposed vide this article to address coupling in a tightly spaced H-plane configured two-element multiple input multiple output (MIMO) antenna operating at the globally popular 5G NR (new radio) band of 3.5 GHz frequency. Wave evanescence exhibited by the devised metamaterial unit element (MTM UE) (4.2 × 4.2 sq.mm) at 3.5 GHz resonance is verified by interposing the MTM UE array (5 × 1) in an MIMO antenna with an edge-to-edge spacing of 5 mm. Each radiator constituting the MIMO array (37 × 80.6 sq.mm) is a modified rectangular patch antenna with dimensions 27 × 33.4 sq.mm that are excited by the cost-effective microstrip transmission line. After the insertion of the proposed MTM unit element, the port isolation reported is <—20>9.8 dB) and Envelope Correlation Coefficient (<0.04) values from the radiation pattern, which adhered to the acceptance rate. Proposed MTM UE even rendered improved radiation gain with negligible impact on the efficiency. To verify the evanescence mechanism in real-time, the prototype covering the two-element MIMO with the proposed miniaturized MTM UE is fabricated and tested, which presents a perfect agreement. All these features make the proposed design viable for Wi-Max (IEEE 802.16e) (3.4–3.5 GHz) technology dedicated to space-constrained modern wireless applications. In addition, this article also presents the RLC equivalence derived for the proposed MTM UE and the two-element MIMO antenna.","PeriodicalId":49638,"journal":{"name":"Radio Science","volume":"60 6","pages":"1-11"},"PeriodicalIF":1.6,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144550377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A CM-based fast computation method for the angular glint feature of multiple objects 一种基于cm的多目标角闪烁特征快速计算方法

IF 1.6 4区地球科学

Radio Science Pub Date : 2025-06-01 DOI: 10.1029/2025RS008245

Jihong Gu;Jiaxuan Wang;Jie Kang;Jiamin Shi;Zhaoyuan Wang;Dazhi Ding

引用次数: 0

A review on ultra-wideband antennas for through wall imaging and ground penetrating radar applications 超宽带天线在穿墙成像和探地雷达中的应用综述

IF 1.6 4区地球科学

Radio Science Pub Date : 2025-06-01 DOI: 10.1029/2024RS008094

Sangeetha Subbaraj;Saffrine Kingsly

引用次数: 0