Pub Date : 2026-02-23DOI: 10.1109/JMASS.2026.3653611
{"title":"The Journal of Miniaturized Air and Space Systems","authors":"","doi":"10.1109/JMASS.2026.3653611","DOIUrl":"https://doi.org/10.1109/JMASS.2026.3653611","url":null,"abstract":"","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"7 1","pages":"C2-C2"},"PeriodicalIF":2.1,"publicationDate":"2026-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11408352","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146778937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-05DOI: 10.1109/JMASS.2026.3650755
Ratul De;Mahesh P. Abegaonkar;Ananjan Basu
A shared aperture Fabry–Perot cavity (FPC)-Lens hybrid dual band high gain antenna is proposed in this article for very low cost small flying object (SFO)-based imaging radar implementation. The designed single layer superstrate acts as a highly reflecting surface for FPC antenna and a highly transmitting phase correcting surface for lens antenna. The transmission and reflection properties of superstrate unit cells can be selected independently. A combination of two different types of unit cells is used to increase the transmission phase variation while keeping the reflection band properties intact. A single feed dual band source patch is designed to illuminate the cavity, whose both operating frequencies can also be decided independently. For small frequency ratio and without any complicated feed network, this antenna achieves high gain at both the operating bands. The fabricated prototype antenna provides a measured impedance bandwidth (BW) of 440 MHz and a peak realized gain of 17.3 dBi at X band and a BW of 785 MHz and peak gain of 16.5 dBi at Ku band. The structure is compact, lightweight, offers high gain with high polarization purity at both the frequencies making it suitable for SFO-based imaging radar.
{"title":"A Shared Aperture FPC-Lens Antenna for Low Cost Small Flying Object-Based Imaging Radar Applications","authors":"Ratul De;Mahesh P. Abegaonkar;Ananjan Basu","doi":"10.1109/JMASS.2026.3650755","DOIUrl":"https://doi.org/10.1109/JMASS.2026.3650755","url":null,"abstract":"A shared aperture Fabry–Perot cavity (FPC)-Lens hybrid dual band high gain antenna is proposed in this article for very low cost small flying object (SFO)-based imaging radar implementation. The designed single layer superstrate acts as a highly reflecting surface for FPC antenna and a highly transmitting phase correcting surface for lens antenna. The transmission and reflection properties of superstrate unit cells can be selected independently. A combination of two different types of unit cells is used to increase the transmission phase variation while keeping the reflection band properties intact. A single feed dual band source patch is designed to illuminate the cavity, whose both operating frequencies can also be decided independently. For small frequency ratio and without any complicated feed network, this antenna achieves high gain at both the operating bands. The fabricated prototype antenna provides a measured impedance bandwidth (BW) of 440 MHz and a peak realized gain of 17.3 dBi at X band and a BW of 785 MHz and peak gain of 16.5 dBi at Ku band. The structure is compact, lightweight, offers high gain with high polarization purity at both the frequencies making it suitable for SFO-based imaging radar.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"7 1","pages":"142-150"},"PeriodicalIF":2.1,"publicationDate":"2026-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147237263","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 : 2025-12-31DOI: 10.1109/JMASS.2025.3649896
Vijeta Diwan;Santanu Dwari
A surrogate model is used followed by a metaheuristic search engine to reduce the number of simulation iterations. The design consists of an artificial magnetic conductor (AMC) which functions as reflector in conjunction with a monopole radiator, reducing antenna module’s profile and boosting gain. This configuration allows for effective use of the frequency spectrum by enabling closely spaced circularly polarized bands. Precision radar, navigation, and high-speed communication are among the air and space applications that benefit greatly from the antenna design’s exceptional X-band performance. Compared to previously proposed machine learning techniques for antenna optimization, our optimized antenna has a better gain (8.1 and 5.3 dB), dual band with impedance bandwidth 33% (8.6–12 GHz), and larger axial ratio bandwidth of 12.6%, 4.7% (8.9–10.1 GHz, and 11.39–11.95 GHz). The polarization sense of both the bands is LHCP and RHCP, respectively. Both optimization time and the number of electromagnetic (EM) simulations are greatly reduced.
{"title":"Metaheuristic Search-Based Design for Reduced Design Time of an AMC Integrated Circularly Polarized Antenna for Air and Space Applications","authors":"Vijeta Diwan;Santanu Dwari","doi":"10.1109/JMASS.2025.3649896","DOIUrl":"https://doi.org/10.1109/JMASS.2025.3649896","url":null,"abstract":"A surrogate model is used followed by a metaheuristic search engine to reduce the number of simulation iterations. The design consists of an artificial magnetic conductor (AMC) which functions as reflector in conjunction with a monopole radiator, reducing antenna module’s profile and boosting gain. This configuration allows for effective use of the frequency spectrum by enabling closely spaced circularly polarized bands. Precision radar, navigation, and high-speed communication are among the air and space applications that benefit greatly from the antenna design’s exceptional X-band performance. Compared to previously proposed machine learning techniques for antenna optimization, our optimized antenna has a better gain (8.1 and 5.3 dB), dual band with impedance bandwidth 33% (8.6–12 GHz), and larger axial ratio bandwidth of 12.6%, 4.7% (8.9–10.1 GHz, and 11.39–11.95 GHz). The polarization sense of both the bands is LHCP and RHCP, respectively. Both optimization time and the number of electromagnetic (EM) simulations are greatly reduced.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"7 1","pages":"132-141"},"PeriodicalIF":2.1,"publicationDate":"2025-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147268763","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}
With the evolution of 5G-Advanced and 6G, the terahertz (THz) band—with ultralarge bandwidth potential—has become a core candidate for 100 Gb/s-level high-speed communications. However, THz base stations (BSs) on high-rise buildings, while advantageous for emergency communications and large-scale event broadcasting, face insufficient capacity in dense urban hotspots due to THz waves’ inherent strong directivity, high path loss, and obstacle sensitivity. To solve this, this article proposes an optimal reconfigurable intelligent surface (RIS) deployment strategy for high-rise scenarios. It enhances hotspot communication by expanding signal coverage, using intelligent reflection for multipath gains, and jointly optimizing RIS spatial position, BS precoding matrix, and RIS precoding matrix. Simulation results show the proposed strategy outperforms random RIS deployment significantly: in 0–20 GHz ultrawideband, it maintains a stable 4.5–4.6 bit/s/Hz subcarrier achievable rate; at 50-dBm BS transmit power, its hotspot capacity is over 2.5 times that of random deployment.
{"title":"Enhancing Communication Capacity in Urban Hotspot Areas: Optimal Deployment Study of RIS-Assisted THz Communication Systems","authors":"Mengliang Li;Shuai Han;Jinshuo Yang;Zhiqiang Li;Chenyu Wu","doi":"10.1109/JMASS.2025.3649742","DOIUrl":"https://doi.org/10.1109/JMASS.2025.3649742","url":null,"abstract":"With the evolution of 5G-Advanced and 6G, the terahertz (THz) band—with ultralarge bandwidth potential—has become a core candidate for 100 Gb/s-level high-speed communications. However, THz base stations (BSs) on high-rise buildings, while advantageous for emergency communications and large-scale event broadcasting, face insufficient capacity in dense urban hotspots due to THz waves’ inherent strong directivity, high path loss, and obstacle sensitivity. To solve this, this article proposes an optimal reconfigurable intelligent surface (RIS) deployment strategy for high-rise scenarios. It enhances hotspot communication by expanding signal coverage, using intelligent reflection for multipath gains, and jointly optimizing RIS spatial position, BS precoding matrix, and RIS precoding matrix. Simulation results show the proposed strategy outperforms random RIS deployment significantly: in 0–20 GHz ultrawideband, it maintains a stable 4.5–4.6 bit/s/Hz subcarrier achievable rate; at 50-dBm BS transmit power, its hotspot capacity is over 2.5 times that of random deployment.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"7 1","pages":"123-131"},"PeriodicalIF":2.1,"publicationDate":"2025-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146778943","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 : 2025-12-24DOI: 10.1109/JMASS.2025.3647915
Surbhi Arora;Jayanta Mukherjee
This research presents a novel hybrid method to minimize the radar cross section (RCS) of a compact slot antenna operating over 5.1–9.9 GHz. The combination of metal reduction and characteristic mode analysis (CMA) enables the effective suppression of scattering modes, achieved by carefully analyzing and manipulating modal currents. This technique achieves an RCS reduction of up to 8.6 dB across a broad frequency range of 1–20 GHz (181%), including both in-band and out-of-band frequencies, under normal incidence of linearly polarized (LP) waves. Moreover, it demonstrates RCS reductions of up to 6 dB over an approximate frequency range of 2–20 GHz for varying incidence angles of LP waves. Additionally, RCS reductions of up to 5 dB are attained across the 3–20 GHz frequency range for both normal and obliquely incident circularly polarized (CP) waves. Notably, the RCS reduction achieved is robust and insensitive to polarization and angle variations, thereby ensuring a consistent performance enhancement, while preserving the antenna’s inherent radiation capabilities. To validate the design, a prototype was developed and tested, yielding measured results that closely match the simulated data, confirming the effectiveness of this hybrid technique.
{"title":"Wideband and Wide-Angle Radar Cross Section Reduction of Slot Antenna for Stealth Applications","authors":"Surbhi Arora;Jayanta Mukherjee","doi":"10.1109/JMASS.2025.3647915","DOIUrl":"https://doi.org/10.1109/JMASS.2025.3647915","url":null,"abstract":"This research presents a novel hybrid method to minimize the radar cross section (RCS) of a compact slot antenna operating over 5.1–9.9 GHz. The combination of metal reduction and characteristic mode analysis (CMA) enables the effective suppression of scattering modes, achieved by carefully analyzing and manipulating modal currents. This technique achieves an RCS reduction of up to 8.6 dB across a broad frequency range of 1–20 GHz (181%), including both in-band and out-of-band frequencies, under normal incidence of linearly polarized (LP) waves. Moreover, it demonstrates RCS reductions of up to 6 dB over an approximate frequency range of 2–20 GHz for varying incidence angles of LP waves. Additionally, RCS reductions of up to 5 dB are attained across the 3–20 GHz frequency range for both normal and obliquely incident circularly polarized (CP) waves. Notably, the RCS reduction achieved is robust and insensitive to polarization and angle variations, thereby ensuring a consistent performance enhancement, while preserving the antenna’s inherent radiation capabilities. To validate the design, a prototype was developed and tested, yielding measured results that closely match the simulated data, confirming the effectiveness of this hybrid technique.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"7 1","pages":"116-122"},"PeriodicalIF":2.1,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146778941","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 : 2025-12-15DOI: 10.1109/JMASS.2025.3643848
Chenxing Mao;Weiwei Guo;Zenghui Zhang
3-D reconstruction of ground targets from multimodal remote sensing data is vital for miniaturized air systems, enabling applications, such as autonomous navigation, surveillance, and environmental monitoring. This article presents a new multimodal fusion framework for 3-D target reconstruction by jointly exploiting multiview synthetic aperture radar (SAR) and optical images. The proposed framework incorporates an integrated differentiable render for both SAR and optical images in the forward process, enabling efficient generation of simulated SAR and optical images under diverse imaging geometries. In the backward process, a new gradient-based optimization strategy is introduced to iteratively refine the 3-D target model by minimizing the discrepancy between the simulated images and the observed SAR and optical images. Comprehensive experiments demonstrate the effectiveness and robustness of the proposed framework, highlighting its potential for accurate 3-D reconstruction in complex multimodal remote sensing scenarios.
{"title":"Multimodal 3-D Target Reconstruction From SAR and Optical Imagery via Differentiable Rendering","authors":"Chenxing Mao;Weiwei Guo;Zenghui Zhang","doi":"10.1109/JMASS.2025.3643848","DOIUrl":"https://doi.org/10.1109/JMASS.2025.3643848","url":null,"abstract":"3-D reconstruction of ground targets from multimodal remote sensing data is vital for miniaturized air systems, enabling applications, such as autonomous navigation, surveillance, and environmental monitoring. This article presents a new multimodal fusion framework for 3-D target reconstruction by jointly exploiting multiview synthetic aperture radar (SAR) and optical images. The proposed framework incorporates an integrated differentiable render for both SAR and optical images in the forward process, enabling efficient generation of simulated SAR and optical images under diverse imaging geometries. In the backward process, a new gradient-based optimization strategy is introduced to iteratively refine the 3-D target model by minimizing the discrepancy between the simulated images and the observed SAR and optical images. Comprehensive experiments demonstrate the effectiveness and robustness of the proposed framework, highlighting its potential for accurate 3-D reconstruction in complex multimodal remote sensing scenarios.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"7 1","pages":"88-98"},"PeriodicalIF":2.1,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146778901","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 : 2025-12-15DOI: 10.1109/JMASS.2025.3644243
Anuradha Verma;Pankaj K. Sharma;Judhistir Mahapatro
The integration of overlay technology with simultaneous wireless information and power transfer (SWIPT) presents a promising solution to enhance and extend space–air–ground communications for next-generation wireless networks. This article explores an overlay-based space–air–ground integrated network (SAGIN) architecture, encompassing a ground-to-satellite (G2S) network and an aerial network constrained by both energy and spectrum. Through this integration, overlay technology enables efficient spectrum utilization by allowing the aerial network to opportunistically access licensed spectrum without interfering with G2S operations. The aerial transmitter (ATx) leverages SWIPT-based battery-assisted nonlinear energy harvesting, where it collects energy from incoming signals from the ground node and utilizes the harvested energy to relay signals to the satellite and the aerial receiver (ARx). By addressing the relevant stochastic positioning of the ground nodes, ARx, and satellite, we evaluate the performance of both the G2S and air-to-air (A2A) networks. Our analysis incorporates Shadowed-Rician fading for the satellite link, Nakagami-$m$ fading for the ground link, and Rician fading for the aerial link. We derive analytical expressions for the outage probability and throughput, offering insights into key design parameters that promote energy-efficient and spectrum-efficient network configurations. Finally, Monte Carlo simulations verify the theoretical findings and lay practical guidelines for the development of future SAGINs.
{"title":"Outage Analysis of Space–Air–Ground Integrated Networks Powered by Battery-Aided SWIPT","authors":"Anuradha Verma;Pankaj K. Sharma;Judhistir Mahapatro","doi":"10.1109/JMASS.2025.3644243","DOIUrl":"https://doi.org/10.1109/JMASS.2025.3644243","url":null,"abstract":"The integration of overlay technology with simultaneous wireless information and power transfer (SWIPT) presents a promising solution to enhance and extend space–air–ground communications for next-generation wireless networks. This article explores an overlay-based space–air–ground integrated network (SAGIN) architecture, encompassing a ground-to-satellite (G2S) network and an aerial network constrained by both energy and spectrum. Through this integration, overlay technology enables efficient spectrum utilization by allowing the aerial network to opportunistically access licensed spectrum without interfering with G2S operations. The aerial transmitter (ATx) leverages SWIPT-based battery-assisted nonlinear energy harvesting, where it collects energy from incoming signals from the ground node and utilizes the harvested energy to relay signals to the satellite and the aerial receiver (ARx). By addressing the relevant stochastic positioning of the ground nodes, ARx, and satellite, we evaluate the performance of both the G2S and air-to-air (A2A) networks. Our analysis incorporates Shadowed-Rician fading for the satellite link, Nakagami-<inline-formula> <tex-math>$m$ </tex-math></inline-formula> fading for the ground link, and Rician fading for the aerial link. We derive analytical expressions for the outage probability and throughput, offering insights into key design parameters that promote energy-efficient and spectrum-efficient network configurations. Finally, Monte Carlo simulations verify the theoretical findings and lay practical guidelines for the development of future SAGINs.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"7 1","pages":"99-115"},"PeriodicalIF":2.1,"publicationDate":"2025-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146778935","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 : 2025-12-10DOI: 10.1109/JMASS.2025.3642275
Qingxi Lin;Jinhua Chang;Wanyue Jiang;Xiaorui Liu
Uncrewed aerial vehicle (UAV) path planning is essential for applications, such as infrastructure inspection, environmental monitoring, and logistics distribution. A typical mission requires the UAV to depart from a base, visit designated targets, and return, forming a closed route. However, large-scale targets, high-dimensional environments, and strict timing constraints make it challenging to achieve both accuracy and computational efficiency. To address these issues, we propose sparse graph attention network for LKH (SGAT-LKH), a hybrid path planning framework that integrates a sparse graph attention encoder with the Lin–Kernighan–Helsgaun (LKH) solver. By using a sparse graph encoder with multihead attention to extract informative neighborhood features, SGAT-LKH generates a data-driven candidate edge set, which alleviates reliance on manual heuristics. Extensive UAV path planning simulations demonstrate the effectiveness of SGAT-LKH: on 2-D random TSP500 tasks, it achieves an average runtime of 12.8 s, about 70% faster than the LKH solver. On TSPLIB benchmarks, the average gap stays below 0.8%, and the optimality gap is only 0.085% on extended 3-D tasks. These results demonstrate SGAT-LKH’s ability to balance accuracy and efficiency, providing a scalable and practical solution for large-scale and time-critical UAV missions.
{"title":"A Hybrid Sparse Graph Attention Framework for UAV Path Planning","authors":"Qingxi Lin;Jinhua Chang;Wanyue Jiang;Xiaorui Liu","doi":"10.1109/JMASS.2025.3642275","DOIUrl":"https://doi.org/10.1109/JMASS.2025.3642275","url":null,"abstract":"Uncrewed aerial vehicle (UAV) path planning is essential for applications, such as infrastructure inspection, environmental monitoring, and logistics distribution. A typical mission requires the UAV to depart from a base, visit designated targets, and return, forming a closed route. However, large-scale targets, high-dimensional environments, and strict timing constraints make it challenging to achieve both accuracy and computational efficiency. To address these issues, we propose sparse graph attention network for LKH (SGAT-LKH), a hybrid path planning framework that integrates a sparse graph attention encoder with the Lin–Kernighan–Helsgaun (LKH) solver. By using a sparse graph encoder with multihead attention to extract informative neighborhood features, SGAT-LKH generates a data-driven candidate edge set, which alleviates reliance on manual heuristics. Extensive UAV path planning simulations demonstrate the effectiveness of SGAT-LKH: on 2-D random TSP500 tasks, it achieves an average runtime of 12.8 s, about 70% faster than the LKH solver. On TSPLIB benchmarks, the average gap stays below 0.8%, and the optimality gap is only 0.085% on extended 3-D tasks. These results demonstrate SGAT-LKH’s ability to balance accuracy and efficiency, providing a scalable and practical solution for large-scale and time-critical UAV missions.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"7 1","pages":"80-87"},"PeriodicalIF":2.1,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147237262","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}
In this article, we investigate complex-valued Chinese remainder theorem (C-CRT) with erroneous remainders, where the moduli are Gaussian integers and the errors follow wrapped complex Gaussian distributions. Based on the existing real-valued CRT utilizing maximum likelihood estimation (MLE), we propose a fast MLE-based C-CRT (MLE C-CRT). The proposed algorithm requires only $2L$ searches to obtain the optimal estimate of the common remainder, where $L$ is the number of moduli. Once the common remainder is estimated, the complex number can be determined using the C-CRT. Furthermore, we obtain a necessary and sufficient condition for the fast MLE C-CRT to achieve robust estimation. Finally, we apply the proposed algorithm to a multichannel self-reset analog-to-digital converter (ADC) system with Gaussian integers as moduli, which enables the recovery of high dynamic range complex-valued bandlimited signals at the Nyquist sampling rate. The results demonstrate that the proposed algorithm outperforms the existing methods.
{"title":"Maximum Likelihood Estimation-Based Complex-Valued Robust Chinese Remainder Theorem and Its Fast Algorithm","authors":"Xiaoping Li;Shiyang Sun;Qunying Liao;Xiang-Gen Xia","doi":"10.1109/JMASS.2025.3640013","DOIUrl":"https://doi.org/10.1109/JMASS.2025.3640013","url":null,"abstract":"In this article, we investigate complex-valued Chinese remainder theorem (C-CRT) with erroneous remainders, where the moduli are Gaussian integers and the errors follow wrapped complex Gaussian distributions. Based on the existing real-valued CRT utilizing maximum likelihood estimation (MLE), we propose a fast MLE-based C-CRT (MLE C-CRT). The proposed algorithm requires only <inline-formula> <tex-math>$2L$ </tex-math></inline-formula> searches to obtain the optimal estimate of the common remainder, where <inline-formula> <tex-math>$L$ </tex-math></inline-formula> is the number of moduli. Once the common remainder is estimated, the complex number can be determined using the C-CRT. Furthermore, we obtain a necessary and sufficient condition for the fast MLE C-CRT to achieve robust estimation. Finally, we apply the proposed algorithm to a multichannel self-reset analog-to-digital converter (ADC) system with Gaussian integers as moduli, which enables the recovery of high dynamic range complex-valued bandlimited signals at the Nyquist sampling rate. The results demonstrate that the proposed algorithm outperforms the existing methods.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"7 1","pages":"64-79"},"PeriodicalIF":2.1,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147268769","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 : 2025-12-03DOI: 10.1109/JMASS.2025.3639630
Wei Jiaju;Hua Wenqiang;Wang Xinlei;Xue Jing
With the continuous development of deep learning technology, polarimetric synthetic aperture radar (PolSAR) image interpretation based on deep learning methods has been proved to have better performance. It can automatically extract features, and the advanced features automatically extracted are more distinguishable than the features manually extracted, which can well represent the discrimination ability of images. However, most of the existing PolSAR classification methods based on deep learning usually ignore the potential physical characteristics of PolSAR and rely heavily on training data in the training process. To solve this problem, this article proposes a PolSAR image classification model based on physical scattering mechanism. By combining physical scattering and data-driven method, the complementary information of the two is fully utilized to improve the classification accuracy of PolSAR images, so as to reduce the dependence on labeled data in the training process. The overall classification accuracy on the real Flevoland I and Flevoland II datasets is 96.11% and 96.41%, which indicates that the proposed method significantly improves the classification accuracy and is significantly superior to other methods. In addition, when the number of samples is small, the proposed method also has high classification accuracy.
{"title":"PolSAR Classification Based on Physical Scattering Mechanisms","authors":"Wei Jiaju;Hua Wenqiang;Wang Xinlei;Xue Jing","doi":"10.1109/JMASS.2025.3639630","DOIUrl":"https://doi.org/10.1109/JMASS.2025.3639630","url":null,"abstract":"With the continuous development of deep learning technology, polarimetric synthetic aperture radar (PolSAR) image interpretation based on deep learning methods has been proved to have better performance. It can automatically extract features, and the advanced features automatically extracted are more distinguishable than the features manually extracted, which can well represent the discrimination ability of images. However, most of the existing PolSAR classification methods based on deep learning usually ignore the potential physical characteristics of PolSAR and rely heavily on training data in the training process. To solve this problem, this article proposes a PolSAR image classification model based on physical scattering mechanism. By combining physical scattering and data-driven method, the complementary information of the two is fully utilized to improve the classification accuracy of PolSAR images, so as to reduce the dependence on labeled data in the training process. The overall classification accuracy on the real Flevoland I and Flevoland II datasets is 96.11% and 96.41%, which indicates that the proposed method significantly improves the classification accuracy and is significantly superior to other methods. In addition, when the number of samples is small, the proposed method also has high classification accuracy.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"7 1","pages":"57-63"},"PeriodicalIF":2.1,"publicationDate":"2025-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146778942","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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