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}
Pub Date : 2024-12-16DOI: 10.1109/JMASS.2024.3516312
Jindou Xie;Mengqi Shi;Yixuan Liu
With the demand for real-time data processing in mobile environments has surged, uncrewed aerial vehicle (UAVs) are regrading as flying base stations (BSs) for real-time application and emergency communication. In this article, we investigate a task collaborative offloading in UAV-assisted edge computing environments, integrating dynamic pricing mechanisms and UAVS group formation to optimize resource allocation. We explore the challenges posed by the heterogeneity of UAVs and the dynamic workload distribution. Our proposed system leverages a multiagent deep reinforcement learning framework to intelligently assist computing UAVs to form a collaborative group, considering the constraints of latency, service budget, and computational capacity. The dynamic pricing model incentivizes leading UAV to help efficient task offloading by task collaborative scheduling within groups and task relaying to BS. Through extensive simulations, we demonstrate that our approach significantly enhances the overall system performance, reduces task completion time, and optimizes resource utilization.
{"title":"Task Collaborative Offloading for UAV-Assisted Edge Computing With Dynamic Pricing","authors":"Jindou Xie;Mengqi Shi;Yixuan Liu","doi":"10.1109/JMASS.2024.3516312","DOIUrl":"https://doi.org/10.1109/JMASS.2024.3516312","url":null,"abstract":"With the demand for real-time data processing in mobile environments has surged, uncrewed aerial vehicle (UAVs) are regrading as flying base stations (BSs) for real-time application and emergency communication. In this article, we investigate a task collaborative offloading in UAV-assisted edge computing environments, integrating dynamic pricing mechanisms and UAVS group formation to optimize resource allocation. We explore the challenges posed by the heterogeneity of UAVs and the dynamic workload distribution. Our proposed system leverages a multiagent deep reinforcement learning framework to intelligently assist computing UAVs to form a collaborative group, considering the constraints of latency, service budget, and computational capacity. The dynamic pricing model incentivizes leading UAV to help efficient task offloading by task collaborative scheduling within groups and task relaying to BS. Through extensive simulations, we demonstrate that our approach significantly enhances the overall system performance, reduces task completion time, and optimizes resource utilization.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"6 2","pages":"157-164"},"PeriodicalIF":0.0,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144179143","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}
This article investigates the resource sharing problem in a multiuncrewed aerial vehicle (UAV) wireless network by utilizing the multiagent reinforcement learning (MARL) method. Specifically, the considered multi-UAV system involves two transmission modes, i.e., UAV-to-device (U2D) mode and UAV-to-network (U2N) mode, in which the U2D mode is allowed to reuse the spectrum of U2N mode to improve the spectrum efficiency. Then, we formulate an optimization problem to maximize the throughput of U2D links by jointly optimizing the channel allocation, power level selection, and UAV trajectory, while ensuring the communication quality of U2N links. Due to the highly complex and dynamic nature, as well as the challenging nonconvex objective function and constraints, the resulting problem is hard to address. Accordingly, we propose a novel multiagent deep deterministic policy gradient (MADDPG)-based resource allocation and multi-UAV trajectory optimization policy. Simulation results illustrate the efficacy of our method in improving the system transmission rate.
{"title":"Multiagent Reinforcement Learning-Based Resource Sharing in Multi-UAV Wireless Networks","authors":"Yaxiu Zhang;Mingan Luan;Zheng Chang;Timo Hämäläinen","doi":"10.1109/JMASS.2024.3510808","DOIUrl":"https://doi.org/10.1109/JMASS.2024.3510808","url":null,"abstract":"This article investigates the resource sharing problem in a multiuncrewed aerial vehicle (UAV) wireless network by utilizing the multiagent reinforcement learning (MARL) method. Specifically, the considered multi-UAV system involves two transmission modes, i.e., UAV-to-device (U2D) mode and UAV-to-network (U2N) mode, in which the U2D mode is allowed to reuse the spectrum of U2N mode to improve the spectrum efficiency. Then, we formulate an optimization problem to maximize the throughput of U2D links by jointly optimizing the channel allocation, power level selection, and UAV trajectory, while ensuring the communication quality of U2N links. Due to the highly complex and dynamic nature, as well as the challenging nonconvex objective function and constraints, the resulting problem is hard to address. Accordingly, we propose a novel multiagent deep deterministic policy gradient (MADDPG)-based resource allocation and multi-UAV trajectory optimization policy. Simulation results illustrate the efficacy of our method in improving the system transmission rate.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"6 2","pages":"103-112"},"PeriodicalIF":0.0,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144179130","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 : 2024-11-27DOI: 10.1109/JMASS.2024.3507735
Xiangwei Bu;Ruining Luo;Jiaxi Chen;Humin Lei
Our objective is to explore a finite-time tracking control protocol with fragility-rejection for discrete-time systems subject to saturation constrained dynamics, specifically in the field of UAV flight control. This protocol is capable of imposing desired transient and steady-state behaviors on tracking errors, while introducing transformed errors utilizing finite-time performance functions and stabilizing them indirectly through feedback terms developed using these functions in a back-stepping-like control design. Our approach introduces a structure that distinguishes it from existing transformed-error-stabilization-based prescribed performance control (PPC) methods. Furthermore, we propose a compensated system to modify the final feedback term and address actuator saturation, effectively resolving the challenging fragility issue associated with existing PPC approaches caused by error fluctuation due to actuator saturation in discrete-time systems. Finally, comparative simulation results obtained for flight control applications validate the effectiveness of our design.
{"title":"Fragility-Rejection UAV Flight Control With Discrete-Time Constrained Dynamics Endowing Preselected Qualities","authors":"Xiangwei Bu;Ruining Luo;Jiaxi Chen;Humin Lei","doi":"10.1109/JMASS.2024.3507735","DOIUrl":"https://doi.org/10.1109/JMASS.2024.3507735","url":null,"abstract":"Our objective is to explore a finite-time tracking control protocol with fragility-rejection for discrete-time systems subject to saturation constrained dynamics, specifically in the field of UAV flight control. This protocol is capable of imposing desired transient and steady-state behaviors on tracking errors, while introducing transformed errors utilizing finite-time performance functions and stabilizing them indirectly through feedback terms developed using these functions in a back-stepping-like control design. Our approach introduces a structure that distinguishes it from existing transformed-error-stabilization-based prescribed performance control (PPC) methods. Furthermore, we propose a compensated system to modify the final feedback term and address actuator saturation, effectively resolving the challenging fragility issue associated with existing PPC approaches caused by error fluctuation due to actuator saturation in discrete-time systems. Finally, comparative simulation results obtained for flight control applications validate the effectiveness of our design.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"6 1","pages":"27-35"},"PeriodicalIF":0.0,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143480792","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 : 2024-11-25DOI: 10.1109/JMASS.2024.3504992
{"title":"2024 Index IEEE Journal on Miniaturization for Air and Space Systems Vol. 5","authors":"","doi":"10.1109/JMASS.2024.3504992","DOIUrl":"https://doi.org/10.1109/JMASS.2024.3504992","url":null,"abstract":"","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"5 4","pages":"274-281"},"PeriodicalIF":0.0,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10766876","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142713831","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 : 2024-11-20DOI: 10.1109/JMASS.2024.3496303
{"title":"The Journal of Miniaturized Air and Space Systems","authors":"","doi":"10.1109/JMASS.2024.3496303","DOIUrl":"https://doi.org/10.1109/JMASS.2024.3496303","url":null,"abstract":"","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"5 4","pages":"C2-C2"},"PeriodicalIF":0.0,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10759326","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142679265","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 : 2024-11-05DOI: 10.1109/JMASS.2024.3491319
Shilpi Singh;Shakti Singh Chauhan;Ananjan Basu
This article presents a dual circularly polarized slotted waveguide leaky wave antenna for CubeSat communications at W-band. The proposed fully metallic, low profile, and high-performing antenna offers wideband operating bandwidth, which makes it suitable for space applications. To achieve circular polarization, an array of circular holes is perforated at an offset position from the narrow wall of the WR-10 waveguide. The prototype antenna provides a wide axial ratio bandwidth of 13% and an average half-power beamwidth of 4.5° on the elevation plane. At high frequencies, the thickness of the slot affects the emission through the slot, which is not typically encountered at low frequencies. Therefore, to increase the magnitude of the radiated power, the wall thickness of the hole is reduced. The proposed circular hole slotted waveguide antenna design provides superior tolerance, accuracy, and precision compared to any other structures. These characteristics eliminate fabrication challenges, especially within the W-band, and can seamlessly extend into the sub-THz domain as well. The proposed antenna is robust, easy to fabricate, and appropriate for integration into CubeSat. It can be adapted for W-band CubeSat LEO, intersatellite, and constellation missions.
{"title":"A Low Profile Wideband Circularly Polarized Slotted Waveguide Antenna for W-Band CubeSat Data-Links","authors":"Shilpi Singh;Shakti Singh Chauhan;Ananjan Basu","doi":"10.1109/JMASS.2024.3491319","DOIUrl":"https://doi.org/10.1109/JMASS.2024.3491319","url":null,"abstract":"This article presents a dual circularly polarized slotted waveguide leaky wave antenna for CubeSat communications at W-band. The proposed fully metallic, low profile, and high-performing antenna offers wideband operating bandwidth, which makes it suitable for space applications. To achieve circular polarization, an array of circular holes is perforated at an offset position from the narrow wall of the WR-10 waveguide. The prototype antenna provides a wide axial ratio bandwidth of 13% and an average half-power beamwidth of 4.5° on the elevation plane. At high frequencies, the thickness of the slot affects the emission through the slot, which is not typically encountered at low frequencies. Therefore, to increase the magnitude of the radiated power, the wall thickness of the hole is reduced. The proposed circular hole slotted waveguide antenna design provides superior tolerance, accuracy, and precision compared to any other structures. These characteristics eliminate fabrication challenges, especially within the W-band, and can seamlessly extend into the sub-THz domain as well. The proposed antenna is robust, easy to fabricate, and appropriate for integration into CubeSat. It can be adapted for W-band CubeSat LEO, intersatellite, and constellation missions.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"6 1","pages":"19-26"},"PeriodicalIF":0.0,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143480775","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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