Pub Date : 2025-02-14DOI: 10.1109/JMASS.2025.3542124
Lifan Zhou;Xuanyu Zhou;Huanghao Feng;Wei Liu;Hao Liu
Monitoring and evaluating floods is crucial for geographic information systems (GISs). The low backscattering coefficient of flood surfaces makes them appear darker in synthetic aperture radar (SAR) images, which is advantageous for flood segmentation. In recent years, with the advancement of deep learning, semantic segmentation of flood regions in SAR images using convolutional neural networks (CNNs) has become a focal point in earth observation tasks. However, challenges, such as the similarity between the texture and shape of flood regions and the background in SAR images, the segmentation discontinuity at flood edges, the loss of information on small water bodies, and the variability of flood regions in different scales and morphologies, remain inadequately addressed. To tackle these issues, we propose a transformer model based on an encoder–decoder architecture for precise segmentation of flooded areas in SAR images. First, we utilize the mix transformer as the model’s encoder to compensate for CNNs’ limitations in global modeling, enhancing the discrimination of similar features in the image. Second, we introduce a noise filtering module (NFM) to filter redundant semantic information within low-level feature maps during the feature fusion process, thereby mitigating segmentation discontinuities at flood edges and the loss of small water body information. Finally, we design a multiscale depth-wise convolution module (MDCM) to boost the network’s multiscale feature representation capability, addressing issues arising from flood scale variability. Experimental results demonstrate that our method surpasses other mainstream approaches on the Sen1Floods11 dataset.
{"title":"Transformer-Based Semantic Segmentation for Flood Region Recognition in SAR Images","authors":"Lifan Zhou;Xuanyu Zhou;Huanghao Feng;Wei Liu;Hao Liu","doi":"10.1109/JMASS.2025.3542124","DOIUrl":"https://doi.org/10.1109/JMASS.2025.3542124","url":null,"abstract":"Monitoring and evaluating floods is crucial for geographic information systems (GISs). The low backscattering coefficient of flood surfaces makes them appear darker in synthetic aperture radar (SAR) images, which is advantageous for flood segmentation. In recent years, with the advancement of deep learning, semantic segmentation of flood regions in SAR images using convolutional neural networks (CNNs) has become a focal point in earth observation tasks. However, challenges, such as the similarity between the texture and shape of flood regions and the background in SAR images, the segmentation discontinuity at flood edges, the loss of information on small water bodies, and the variability of flood regions in different scales and morphologies, remain inadequately addressed. To tackle these issues, we propose a transformer model based on an encoder–decoder architecture for precise segmentation of flooded areas in SAR images. First, we utilize the mix transformer as the model’s encoder to compensate for CNNs’ limitations in global modeling, enhancing the discrimination of similar features in the image. Second, we introduce a noise filtering module (NFM) to filter redundant semantic information within low-level feature maps during the feature fusion process, thereby mitigating segmentation discontinuities at flood edges and the loss of small water body information. Finally, we design a multiscale depth-wise convolution module (MDCM) to boost the network’s multiscale feature representation capability, addressing issues arising from flood scale variability. Experimental results demonstrate that our method surpasses other mainstream approaches on the Sen1Floods11 dataset.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"6 3","pages":"222-229"},"PeriodicalIF":2.1,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144891025","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 : 2025-02-07DOI: 10.1109/JMASS.2025.3539951
Chen Qiu;Xianbin Wang;Weiming Shen
Uncrewed aerial vehicles (UAVs) have revolutionized various sectors, including remote sensing, surveillance, environmental monitoring, and disaster management. Rapid advancements in wireless communication technologies and situational awareness discovery capabilities present unprecedented opportunities to enhance the intelligence of UAV networks. This review defines UAV network intelligence as the convergence of situational awareness discovery, communication enhancement, and goal-driven intelligent decision-making. Guided by this definition, we explore the key enabling techniques for UAV network situational awareness discovery from UAV states to UAV network environments. To facilitate the awareness discovery, we investigate the integration of advancements in communication technologies, such as massive multiple-input–multiple-output, nonorthogonal multiple access, intelligent reflecting surface, and low-Earth orbit satellites. Based on the situational awareness and empowered by communication enhancement technologies, we emphasize the overall objective of UAV network intelligence: maximizing the value of goal-driven UAV network operations. This is achieved by exploring recent research efforts in three categories, including: 1) iterative optimization methods; 2) learning-based methods; and 3) heuristic methods. Finally, we discuss challenges and future research directions, contributing to the development of more resilient and adaptive UAV network solutions in increasingly complex and dynamic environments.
{"title":"Maximize the Value of Goal-Driven UAV Network Operations Based on Network Intelligence: A Comprehensive Review","authors":"Chen Qiu;Xianbin Wang;Weiming Shen","doi":"10.1109/JMASS.2025.3539951","DOIUrl":"https://doi.org/10.1109/JMASS.2025.3539951","url":null,"abstract":"Uncrewed aerial vehicles (UAVs) have revolutionized various sectors, including remote sensing, surveillance, environmental monitoring, and disaster management. Rapid advancements in wireless communication technologies and situational awareness discovery capabilities present unprecedented opportunities to enhance the intelligence of UAV networks. This review defines UAV network intelligence as the convergence of situational awareness discovery, communication enhancement, and goal-driven intelligent decision-making. Guided by this definition, we explore the key enabling techniques for UAV network situational awareness discovery from UAV states to UAV network environments. To facilitate the awareness discovery, we investigate the integration of advancements in communication technologies, such as massive multiple-input–multiple-output, nonorthogonal multiple access, intelligent reflecting surface, and low-Earth orbit satellites. Based on the situational awareness and empowered by communication enhancement technologies, we emphasize the overall objective of UAV network intelligence: maximizing the value of goal-driven UAV network operations. This is achieved by exploring recent research efforts in three categories, including: 1) iterative optimization methods; 2) learning-based methods; and 3) heuristic methods. Finally, we discuss challenges and future research directions, contributing to the development of more resilient and adaptive UAV network solutions in increasingly complex and dynamic environments.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"6 3","pages":"198-208"},"PeriodicalIF":2.1,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144891099","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 : 2025-01-23DOI: 10.1109/JMASS.2025.3533018
Angela Cratere;M. Salim Farissi;Andrea Carbone;Marcello Asciolla;Maria Rizzi;Francesco Dell’Olio;Augusto Nascetti;Dario Spiller
We present the implementation of four FPGA-accelerated convolutional neural network (CNN) models for onboard cloud detection in resource-constrained CubeSat missions, leveraging Xilinx’s Vitis AI (VAI) framework and deep learning processing unit (DPU), a programmable engine with preimplemented, parameterizable IP cores optimized for deep neural networks, on a Zynq UltraScale+ MPSoC. This study explores both pixel-wise (Pixel-Net and Kernel-Net) and image-wise (U-Net and Patch-Net) models to benchmark tradeoffs in accuracy, latency, and model complexity. Applying channel pruning, we achieved substantial reductions in model parameters (up to 98.6%) and floating-point operations (up to 90.7%) with minimal accuracy loss. Furthermore, the VAI tool was used to quantize the models to 8-bit precision, ensuring optimized hardware performance with negligible impact on accuracy. All models retained high accuracy post-FPGA integration, with a cumulative maximum accuracy drop of only 0.6% after quantization and pruning. The image-wise Patch-Net and U-Net models demonstrated strong real-time inference capabilities, achieving frame rates per second of 57.14 and 37.45, respectively, with power consumption of around 2.5 W, surpassing state-of-the-art onboard cloud detection solutions. Our approach underscores the potential of DPU-based hardware accelerators to expand the processing capabilities of small satellites, enabling efficient and flexible onboard CNN-based applications.
我们在Zynq UltraScale+ MPSoC上实现了四个fpga加速卷积神经网络（CNN）模型，用于资源受限的CubeSat任务中的板载云检测，利用Xilinx的Vitis AI （VAI）框架和深度学习处理单元（DPU），这是一个可编程引擎，具有针对深度神经网络优化的预实现的可参数化IP核。本研究探索了像素级（Pixel-Net和Kernel-Net）和图像级（U-Net和Patch-Net）模型，以在准确性、延迟和模型复杂性方面进行基准权衡。通过通道修剪，我们实现了模型参数（高达98.6%）和浮点操作（高达90.7%）的大幅减少，同时精度损失最小。此外，使用VAI工具将模型量化到8位精度，确保优化的硬件性能，对精度的影响可以忽略不计。所有模型在fpga集成后都保持了较高的精度，量化和修剪后的累计最大精度下降仅为0.6%。图像方面的Patch-Net和U-Net模型展示了强大的实时推断能力，每秒帧率分别为57.14帧和37.45帧，功耗约为2.5 W，超过了最先进的车载云检测解决方案。我们的方法强调了基于dpu的硬件加速器扩展小卫星处理能力的潜力，使基于cnn的机载应用高效灵活。
{"title":"Efficient FPGA-Accelerated Convolutional Neural Networks for Cloud Detection on CubeSats","authors":"Angela Cratere;M. Salim Farissi;Andrea Carbone;Marcello Asciolla;Maria Rizzi;Francesco Dell’Olio;Augusto Nascetti;Dario Spiller","doi":"10.1109/JMASS.2025.3533018","DOIUrl":"https://doi.org/10.1109/JMASS.2025.3533018","url":null,"abstract":"We present the implementation of four FPGA-accelerated convolutional neural network (CNN) models for onboard cloud detection in resource-constrained CubeSat missions, leveraging Xilinx’s Vitis AI (VAI) framework and deep learning processing unit (DPU), a programmable engine with preimplemented, parameterizable IP cores optimized for deep neural networks, on a Zynq UltraScale+ MPSoC. This study explores both pixel-wise (Pixel-Net and Kernel-Net) and image-wise (U-Net and Patch-Net) models to benchmark tradeoffs in accuracy, latency, and model complexity. Applying channel pruning, we achieved substantial reductions in model parameters (up to 98.6%) and floating-point operations (up to 90.7%) with minimal accuracy loss. Furthermore, the VAI tool was used to quantize the models to 8-bit precision, ensuring optimized hardware performance with negligible impact on accuracy. All models retained high accuracy post-FPGA integration, with a cumulative maximum accuracy drop of only 0.6% after quantization and pruning. The image-wise Patch-Net and U-Net models demonstrated strong real-time inference capabilities, achieving frame rates per second of 57.14 and 37.45, respectively, with power consumption of around 2.5 W, surpassing state-of-the-art onboard cloud detection solutions. Our approach underscores the potential of DPU-based hardware accelerators to expand the processing capabilities of small satellites, enabling efficient and flexible onboard CNN-based applications.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"6 3","pages":"187-197"},"PeriodicalIF":2.1,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144891098","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 : 2025-01-20DOI: 10.1109/JMASS.2025.3532076
Yuvraj B. Dhanade;Amalendu Patnaik
The unique wavefronts of the radio vortex beams carrying orbital angular momentum (OAM) make them well utilized in various space applications, e.g., local satellite-based navigation and CubeSat systems. Traditionally, these OAM beams in the radio domain are generated by uniform circular arrays (UCAs), which suffer from their complex structures mostly because of the complex feeding scheme. This article presents a slotted waveguide antenna (SWA) array for circularly polarized OAM beam generation, offering a simpler and more practical structure by eliminating the need for a complex feed network. The proposed antenna is designed using a WR-90 rectangular waveguide with slots on its broad wall and is designed for a 10-GHz resonance frequency. It achieves a high realized gain of 11.1 dBi and a narrow divergence angle of ±16° in the far-field radiation pattern. Most importantly, the generated OAM beams by the proposed SWA have a high-mode purity of 87%, which is crucial in terms of OAM generation. Moreover, the antenna characteristics are verified experimentally on a laboratory prototype that agrees well with the simulation.
{"title":"Highly Pure OAM Beams Using Slotted Waveguide Antenna for Various Space Applications","authors":"Yuvraj B. Dhanade;Amalendu Patnaik","doi":"10.1109/JMASS.2025.3532076","DOIUrl":"https://doi.org/10.1109/JMASS.2025.3532076","url":null,"abstract":"The unique wavefronts of the radio vortex beams carrying orbital angular momentum (OAM) make them well utilized in various space applications, e.g., local satellite-based navigation and CubeSat systems. Traditionally, these OAM beams in the radio domain are generated by uniform circular arrays (UCAs), which suffer from their complex structures mostly because of the complex feeding scheme. This article presents a slotted waveguide antenna (SWA) array for circularly polarized OAM beam generation, offering a simpler and more practical structure by eliminating the need for a complex feed network. The proposed antenna is designed using a WR-90 rectangular waveguide with slots on its broad wall and is designed for a 10-GHz resonance frequency. It achieves a high realized gain of 11.1 dBi and a narrow divergence angle of ±16° in the far-field radiation pattern. Most importantly, the generated OAM beams by the proposed SWA have a high-mode purity of 87%, which is crucial in terms of OAM generation. Moreover, the antenna characteristics are verified experimentally on a laboratory prototype that agrees well with the simulation.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"6 3","pages":"181-186"},"PeriodicalIF":2.1,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144891274","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 : 2025-01-14DOI: 10.1109/JMASS.2025.3529713
Anil Kumar Nayak;Aijaz M. Zaidi;Anuradha Sonker;Amalendu Patnaik
A wideband, reduced loss, and high figure-of-merit (FOM) substrate integrated waveguide (SIW), termed corrugated SIW (CSIW), is introduced in this article along with the transition for this 2-D transmission line from the coaxial line for overall miniaturization of 3-D metallic waveguide-based transmission lines in space systems. By placing two longitudinal aperture-coupling feeds into the coaxial line-to-CSIW transition, high coupling near the aperture is achieved to improve the bandwidth with a low insertion loss. In addition, the corrugated via-wall concept is introduced in the traditional SIW to reduce the overall losses. A laboratory prototype of a back-to-back transition is designed, fabricated, and validated experimentally. The proposed transition achieves a measured 10-dB return loss fractional impedance bandwidth (FIBW) of 114% and a 15-dB FIBW of 107%. However, the design achieved an insertion loss of 0.29–1.02 dB in the 19.14–65-GHz frequency range. The experimental results match the simulation results well. Furthermore, the FOM is introduced for the transition for a fair comparison of its performance with the state of the art in this large frequency range. The proposed transition shows excellent performance in port insertion loss, impedance bandwidth [FIBW and absolute impedance bandwidth (AIBW)], and FOM (3299–3515), making it suitable for space applications
{"title":"High Figure-of-Merit Broadband Transition From Coaxial Line to Corrugated SIW for mm-Wave Applications","authors":"Anil Kumar Nayak;Aijaz M. Zaidi;Anuradha Sonker;Amalendu Patnaik","doi":"10.1109/JMASS.2025.3529713","DOIUrl":"https://doi.org/10.1109/JMASS.2025.3529713","url":null,"abstract":"A wideband, reduced loss, and high figure-of-merit (FOM) substrate integrated waveguide (SIW), termed corrugated SIW (CSIW), is introduced in this article along with the transition for this 2-D transmission line from the coaxial line for overall miniaturization of 3-D metallic waveguide-based transmission lines in space systems. By placing two longitudinal aperture-coupling feeds into the coaxial line-to-CSIW transition, high coupling near the aperture is achieved to improve the bandwidth with a low insertion loss. In addition, the corrugated via-wall concept is introduced in the traditional SIW to reduce the overall losses. A laboratory prototype of a back-to-back transition is designed, fabricated, and validated experimentally. The proposed transition achieves a measured 10-dB return loss fractional impedance bandwidth (FIBW) of 114% and a 15-dB FIBW of 107%. However, the design achieved an insertion loss of 0.29–1.02 dB in the 19.14–65-GHz frequency range. The experimental results match the simulation results well. Furthermore, the FOM is introduced for the transition for a fair comparison of its performance with the state of the art in this large frequency range. The proposed transition shows excellent performance in port insertion loss, impedance bandwidth [FIBW and absolute impedance bandwidth (AIBW)], and FOM (3299–3515), making it suitable for space applications","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"6 3","pages":"175-180"},"PeriodicalIF":2.1,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144891097","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 rapid growth in the number of communication devices, there is a sharp increase in the demand for quality of service in wireless networks. To meet the requirements of high stability, low latency, and high reliability in wireless communications, uncrewed aerial vehicle (UAV) communication has become a critical solution for enhancing performance of future wireless networks. Addressing the demands for fast response of communication devices and flexible coverage in complex, diverse, and flexible emerging communication scenarios, a multisource multi-UAV cooperative relay communication system with co-channel interference is studied in the presence of direct links between source nodes and destination nodes. To enhance the interference resilience for the system understudy, two receiver diversity combining techniques, namely maximum ratio combining (MRC) and selection combining (SC), are proposed to combine the signals received by the direct link and UAV link at the destination node. Based on the two-step source-relay selection protocol, optimal source node is first selected to broadcast signals to multiple UAV relays and destination nodes, and then the optimal UAV relay is selected according to the selection cooperation scheme for improving the robustness of UAV cooperative relay systems. Performance analysis of considering multisource multi-UAV cooperative communication system is conducted by providing closed-form expressions for the exact outage probability, asymptotic outage probability, and ergodic capacity. Numerical simulations are provided to validate the theoretical analysis, and the results show that the multiple user diversity gain and cooperative diversity cannot be obtained due to the presence of co-channel interference. However, the damage caused by co-channel interference to the communication system can be compensated by increasing the number of source nodes or UAV relays.
{"title":"On the Analysis of Multisource Cooperative Network Assisted by UAV Relays With Co-Channel Interference","authors":"Haiyan Huang;Yuhao Wei;Linlin Liang;Zhisheng Yin;Nina Zhang","doi":"10.1109/JMASS.2024.3519344","DOIUrl":"https://doi.org/10.1109/JMASS.2024.3519344","url":null,"abstract":"With the rapid growth in the number of communication devices, there is a sharp increase in the demand for quality of service in wireless networks. To meet the requirements of high stability, low latency, and high reliability in wireless communications, uncrewed aerial vehicle (UAV) communication has become a critical solution for enhancing performance of future wireless networks. Addressing the demands for fast response of communication devices and flexible coverage in complex, diverse, and flexible emerging communication scenarios, a multisource multi-UAV cooperative relay communication system with co-channel interference is studied in the presence of direct links between source nodes and destination nodes. To enhance the interference resilience for the system understudy, two receiver diversity combining techniques, namely maximum ratio combining (MRC) and selection combining (SC), are proposed to combine the signals received by the direct link and UAV link at the destination node. Based on the two-step source-relay selection protocol, optimal source node is first selected to broadcast signals to multiple UAV relays and destination nodes, and then the optimal UAV relay is selected according to the selection cooperation scheme for improving the robustness of UAV cooperative relay systems. Performance analysis of considering multisource multi-UAV cooperative communication system is conducted by providing closed-form expressions for the exact outage probability, asymptotic outage probability, and ergodic capacity. Numerical simulations are provided to validate the theoretical analysis, and the results show that the multiple user diversity gain and cooperative diversity cannot be obtained due to the presence of co-channel interference. However, the damage caused by co-channel interference to the communication system can be compensated by increasing the number of source nodes or UAV relays.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"6 2","pages":"144-156"},"PeriodicalIF":0.0,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144179128","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}
A new adaptive control method is designed for a class of pure-feedback nonlinear systems with prespecified tracking accuracy. The system functions of pure-feedback nonlinear systems are allowed to be semi-bounded and continuous. As for the system functions and complicated differential terms, some compact sets are constructed to obtain their bounds on these sets. Therefore, with the help of these bounds, the complicated functions of the system are tackled very well without using approximators, and the “explosion of complexity” inherently in backstepping-based methods are perfectly avoided without using any filters. Furthermore, it is proved that the designed method can guarantee the boundedness of all the closed-loop system signals and the convergence of the tracking error to arbitrarily prespecified small neighborhood of the origin. Finally, a practical simulation example of high-maneuver fighter flight control are given to verify the proposed method.
{"title":"Adaptive Control for a Class of Uncertain Pure-Feedback Systems With Prescribed Tracking Accuracy","authors":"Zongcheng Liu;Yujuan Cui;Qiuni Li;Chongchong Han;Yong Chen","doi":"10.1109/JMASS.2024.3478747","DOIUrl":"https://doi.org/10.1109/JMASS.2024.3478747","url":null,"abstract":"A new adaptive control method is designed for a class of pure-feedback nonlinear systems with prespecified tracking accuracy. The system functions of pure-feedback nonlinear systems are allowed to be semi-bounded and continuous. As for the system functions and complicated differential terms, some compact sets are constructed to obtain their bounds on these sets. Therefore, with the help of these bounds, the complicated functions of the system are tackled very well without using approximators, and the “explosion of complexity” inherently in backstepping-based methods are perfectly avoided without using any filters. Furthermore, it is proved that the designed method can guarantee the boundedness of all the closed-loop system signals and the convergence of the tracking error to arbitrarily prespecified small neighborhood of the origin. Finally, a practical simulation example of high-maneuver fighter flight control are given to verify the proposed method.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"6 3","pages":"167-174"},"PeriodicalIF":2.1,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144891270","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 : 2024-12-23DOI: 10.1109/JMASS.2024.3521979
Javid Ahmad Ganie;Kushmanda Saurav
This article presents a wideband millimeter-wave circularly polarized (CP) transmitarray utilizing the linear-to-circular polarization (LP-to-CP) converter for Ka-band CubeSat applications. The present design aims at combining the multiple band antennas into a single wideband design. The LP-to-CP converter employs a single-layer substrate, providing angular stability up to 50° and achieving a 3-dB axial ratio bandwidth of 29% over the frequency range of 29.5–39.5 GHz. The dimensions of the unit cell are $0.38lambda times 0.38lambda times 0.15lambda $ , where $lambda $ corresponds to a frequency of 30 GHz. A wideband 2-bit phase-quantized transmitarray is integrated with the proposed polarization converter, achieving the configuration of CP wideband transmitarray. The CP transmitarray is illuminated by a wideband linearly polarized (LP) Vivaldi antenna. The transmitarray surface consists of polarization rotating elements sized at $0.3lambda times 0.3lambda times 0.15lambda $ ($lambda $ corresponding to a frequency of 30 GHz). This CP transmitarray antenna demonstrates an axial ratio and 1-dB gain bandwidth of 27.3% (29.5–39.5 GHz) and 24.5%(30–38.5 GHz), respectively, with a maximum gain of 21.4 dBic. Fabrication and measurements of both the LP-to-CP converter and the integrated CP transmitarray have been done. The simulated outcomes align well with the measured results.
{"title":"A Wideband Flat Gain Circularly Polarized Transmitarray Utilizing LP-to-CP Converter for Ka-Band CubeSat Applications","authors":"Javid Ahmad Ganie;Kushmanda Saurav","doi":"10.1109/JMASS.2024.3521979","DOIUrl":"https://doi.org/10.1109/JMASS.2024.3521979","url":null,"abstract":"This article presents a wideband millimeter-wave circularly polarized (CP) transmitarray utilizing the linear-to-circular polarization (LP-to-CP) converter for Ka-band CubeSat applications. The present design aims at combining the multiple band antennas into a single wideband design. The LP-to-CP converter employs a single-layer substrate, providing angular stability up to 50° and achieving a 3-dB axial ratio bandwidth of 29% over the frequency range of 29.5–39.5 GHz. The dimensions of the unit cell are <inline-formula> <tex-math>$0.38lambda times 0.38lambda times 0.15lambda $ </tex-math></inline-formula>, where <inline-formula> <tex-math>$lambda $ </tex-math></inline-formula> corresponds to a frequency of 30 GHz. A wideband 2-bit phase-quantized transmitarray is integrated with the proposed polarization converter, achieving the configuration of CP wideband transmitarray. The CP transmitarray is illuminated by a wideband linearly polarized (LP) Vivaldi antenna. The transmitarray surface consists of polarization rotating elements sized at <inline-formula> <tex-math>$0.3lambda times 0.3lambda times 0.15lambda $ </tex-math></inline-formula> (<inline-formula> <tex-math>$lambda $ </tex-math></inline-formula> corresponding to a frequency of 30 GHz). This CP transmitarray antenna demonstrates an axial ratio and 1-dB gain bandwidth of 27.3% (29.5–39.5 GHz) and 24.5%(30–38.5 GHz), respectively, with a maximum gain of 21.4 dBic. Fabrication and measurements of both the LP-to-CP converter and the integrated CP transmitarray have been done. The simulated outcomes align well with the measured results.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"6 1","pages":"44-52"},"PeriodicalIF":0.0,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143480793","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 : 2024-12-17DOI: 10.1109/JMASS.2024.3519174
Zhengyu Chen;Ruya Xiao;Xiaoyuan Gao;Dong Liang;Dezhi Zhang;Jingyi Sun
Precise registration of multitemporal synthetic aperture radar (SAR) images is a crucial step in Interferometric SAR (InSAR) data processing and serves as the foundation for high-precision interferometric measurements. Regular SAR image registration methods rely on the coherence between images. However, when faced with decorrelation issues, these methods often fail to yield high-precision registration results, adversely affecting subsequent data processing and interferogram quality. In this article, we propose an assisted method for multitemporal SAR image registration that addresses the challenge. By introducing auxiliary scenes with favorable coherence conditions alongside the primary and secondary images, we establish a mathematical model for the assisted registration method based on geometric relationships. The registration precision of the assisted registration method is evaluated using three indicators: 1) consistency checks; 2) interferogram fringe quality; and 3) coherence coefficient distribution. Sentinel-1 SAR images of the mountainous area in southeastern China were used for the experiment, and results show that the offsets calculated using assisted registration method exhibit greater concentration, and root mean square errors (RMSEs) demonstrate improved accuracy in both range and azimuth directions compared to the regular method, with enhancements of 25.6% and 23.3%, respectively. Additionally, interferograms obtained from the assisted registration show clearer and more complete fringes in regions with low coherence. Notably, the number of samples with coherence coefficients exceeding 0.4 increased significantly by 58.1% in the assisted registration results. While the accuracy of the proposed assisted registration method is comparable to that of regular methods under high-quality conditions, it shows marked advantages in scenarios characterized by severe decorrelation.
{"title":"An Assisted Method for Multitemporal SAR Image Registration","authors":"Zhengyu Chen;Ruya Xiao;Xiaoyuan Gao;Dong Liang;Dezhi Zhang;Jingyi Sun","doi":"10.1109/JMASS.2024.3519174","DOIUrl":"https://doi.org/10.1109/JMASS.2024.3519174","url":null,"abstract":"Precise registration of multitemporal synthetic aperture radar (SAR) images is a crucial step in Interferometric SAR (InSAR) data processing and serves as the foundation for high-precision interferometric measurements. Regular SAR image registration methods rely on the coherence between images. However, when faced with decorrelation issues, these methods often fail to yield high-precision registration results, adversely affecting subsequent data processing and interferogram quality. In this article, we propose an assisted method for multitemporal SAR image registration that addresses the challenge. By introducing auxiliary scenes with favorable coherence conditions alongside the primary and secondary images, we establish a mathematical model for the assisted registration method based on geometric relationships. The registration precision of the assisted registration method is evaluated using three indicators: 1) consistency checks; 2) interferogram fringe quality; and 3) coherence coefficient distribution. Sentinel-1 SAR images of the mountainous area in southeastern China were used for the experiment, and results show that the offsets calculated using assisted registration method exhibit greater concentration, and root mean square errors (RMSEs) demonstrate improved accuracy in both range and azimuth directions compared to the regular method, with enhancements of 25.6% and 23.3%, respectively. Additionally, interferograms obtained from the assisted registration show clearer and more complete fringes in regions with low coherence. Notably, the number of samples with coherence coefficients exceeding 0.4 increased significantly by 58.1% in the assisted registration results. While the accuracy of the proposed assisted registration method is comparable to that of regular methods under high-quality conditions, it shows marked advantages in scenarios characterized by severe decorrelation.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"6 1","pages":"36-43"},"PeriodicalIF":0.0,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143480769","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 : 2024-12-16DOI: 10.1109/JMASS.2024.3518576
Zhijuan Hu;Shuangyu Liu;Dongsheng Zhou;Fei Xu;Jiajun Ma;Xin Ning
The combination of mobile-edge computing (MEC) and uncrewed aerial vehicles (UAVs) has important implications for the future development of the Internet of Things (IoT). Additional computing power and extensive network coverage enable users to experience better quality of service even when terrestrial base stations (BSs) scarce or destroyed. In this article, computational offloading and resource allocation for a UAV cluster-assisted MEC system are investigated. The cluster consists of a mobile UAV as the cluster head (ACH) and multiple fixed-position UAVs as cluster members (ACMs), where the ACH offloads the computational tasks generated by BS and assigns them to the ACM for collaborative processing. Since the positions of user equipment (UE) and UAV, as well as the speed and angle of ACH flight, are highly continuous, we construct a Markov decision process (MDP) and propose an offloading algorithm that combines a deep deterministic policy gradient algorithm with a priority experience replay mechanism (PER-DDPG) in order to jointly optimize the user association and UE task offloading rate to minimize the system cost. Simulation results show that compared with the computational unloading algorithms based on actor-critical (AC), deep Q network (DQN), and deep deterministic policy gradient (DDPG), respectively, the proposed PER-DDPG algorithm has good convergence and robustness, and can obtain an optimal unloading strategy with low latency and low power consumption.
{"title":"Deep Reinforcement Learning for Task Offloading and Resource Allocation in UAV Cluster-Assisted Mobile-Edge Computing","authors":"Zhijuan Hu;Shuangyu Liu;Dongsheng Zhou;Fei Xu;Jiajun Ma;Xin Ning","doi":"10.1109/JMASS.2024.3518576","DOIUrl":"https://doi.org/10.1109/JMASS.2024.3518576","url":null,"abstract":"The combination of mobile-edge computing (MEC) and uncrewed aerial vehicles (UAVs) has important implications for the future development of the Internet of Things (IoT). Additional computing power and extensive network coverage enable users to experience better quality of service even when terrestrial base stations (BSs) scarce or destroyed. In this article, computational offloading and resource allocation for a UAV cluster-assisted MEC system are investigated. The cluster consists of a mobile UAV as the cluster head (ACH) and multiple fixed-position UAVs as cluster members (ACMs), where the ACH offloads the computational tasks generated by BS and assigns them to the ACM for collaborative processing. Since the positions of user equipment (UE) and UAV, as well as the speed and angle of ACH flight, are highly continuous, we construct a Markov decision process (MDP) and propose an offloading algorithm that combines a deep deterministic policy gradient algorithm with a priority experience replay mechanism (PER-DDPG) in order to jointly optimize the user association and UE task offloading rate to minimize the system cost. Simulation results show that compared with the computational unloading algorithms based on actor-critical (AC), deep Q network (DQN), and deep deterministic policy gradient (DDPG), respectively, the proposed PER-DDPG algorithm has good convergence and robustness, and can obtain an optimal unloading strategy with low latency and low power consumption.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"6 2","pages":"92-102"},"PeriodicalIF":0.0,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144178861","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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