IEEE Journal on Miniaturization for Air and Space Systems最新文献

The Journal of Miniaturized Air and Space Systems 小型化航空航天系统杂志

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2025-03-30 DOI: 10.1109/JMASS.2025.3571345

引用次数: 0

Value-of-Information Optimization for Object Detection-Driven Joint Video Transmission and Processing in UAV-Enabled Wireless Networks 无人机无线网络中目标检测驱动的联合视频传输与处理的信息价值优化

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2025-03-06 DOI: 10.1109/JMASS.2025.3567087

Nan Cheng;Haoran Chen;Ruijin Sun;Longfei Ma;Conghao Zhou;Yuan Zhang;Yilong Hui

{"title":"Value-of-Information Optimization for Object Detection-Driven Joint Video Transmission and Processing in UAV-Enabled Wireless Networks","authors":"Nan Cheng;Haoran Chen;Ruijin Sun;Longfei Ma;Conghao Zhou;Yuan Zhang;Yilong Hui","doi":"10.1109/JMASS.2025.3567087","DOIUrl":"https://doi.org/10.1109/JMASS.2025.3567087","url":null,"abstract":"In the wake of disasters, rapid and efficient search and rescue operations are essential. Uncrewed aerial vehicles (UAVs) have become instrumental in such scenarios, providing real-time video streaming that can be used for object detection to locate survivors. This technology, however, faces significant challenges due to the limited communication and onboard computational resources, which are critical for processing and transmitting high-quality video data. To address these issues, this article proposes a novel approach that leverages the concept of the value of information (VoI) to optimize the tradeoff between the accuracy of object detection and the associated communication costs. By dynamically adjusting the video stream’s quality, the proposed system aims to ensure that the most valuable information is transmitted within the constraints of bandwidth and computational power. To operationalize this concept, we introduce a deep reinforcement learning (DRL) algorithm that employs the soft actor-critic (SAC) method. The algorithm benefits from the integration of object features and contextual information extracted by ResNet50, which is then processed through a cross-attention structure within the critic network. Our simulation results indicate that our approach significantly enhances the VoI, achieving higher accuracy in object detection with better resource management compared to traditional strategies.","PeriodicalId":100624,"journal":{"name":"IEEE Journal on Miniaturization for Air and Space Systems","volume":"6 2","pages":"59-69"},"PeriodicalIF":0.0,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144179104","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}

引用次数: 0

The Journal of Miniaturized Air and Space Systems 小型化航空航天系统杂志

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2025-02-24 DOI: 10.1109/JMASS.2025.3539903

引用次数: 0

On the Analysis of Multisource Cooperative Network Assisted by UAV Relays With Co-Channel Interference 具有同信道干扰的无人机中继辅助多源协同网络分析

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2025-01-02 DOI: 10.1109/JMASS.2024.3519344

Haiyan Huang;Yuhao Wei;Linlin Liang;Zhisheng Yin;Nina Zhang

{"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}

引用次数: 0

A Wideband Flat Gain Circularly Polarized Transmitarray Utilizing LP-to-CP Converter for Ka-Band CubeSat Applications 一种用于ka波段立方体卫星的基于lp - cp转换器的宽带平增益圆极化发射阵列

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2024-12-23 DOI: 10.1109/JMASS.2024.3521979

Javid Ahmad Ganie;Kushmanda Saurav

{"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}

引用次数: 0

An Assisted Method for Multitemporal SAR Image Registration 多时相SAR图像配准辅助方法

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2024-12-17 DOI: 10.1109/JMASS.2024.3519174

Zhengyu Chen;Ruya Xiao;Xiaoyuan Gao;Dong Liang;Dezhi Zhang;Jingyi Sun

{"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}

引用次数: 0

Deep Reinforcement Learning for Task Offloading and Resource Allocation in UAV Cluster-Assisted Mobile-Edge Computing 无人机集群辅助移动边缘计算中任务卸载和资源分配的深度强化学习

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2024-12-16 DOI: 10.1109/JMASS.2024.3518576

Zhijuan Hu;Shuangyu Liu;Dongsheng Zhou;Fei Xu;Jiajun Ma;Xin Ning

{"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}

引用次数: 0

Task Collaborative Offloading for UAV-Assisted Edge Computing With Dynamic Pricing 基于动态定价的无人机辅助边缘计算任务协同卸载

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2024-12-16 DOI: 10.1109/JMASS.2024.3516312

Jindou Xie;Mengqi Shi;Yixuan Liu

引用次数: 0

Multiagent Reinforcement Learning-Based Resource Sharing in Multi-UAV Wireless Networks 基于多智能体强化学习的多无人机无线网络资源共享

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2024-12-04 DOI: 10.1109/JMASS.2024.3510808

Yaxiu Zhang;Mingan Luan;Zheng Chang;Timo Hämäläinen

引用次数: 0

Fragility-Rejection UAV Flight Control With Discrete-Time Constrained Dynamics Endowing Preselected Qualities 具有预选特性的离散时间约束动力学的抗脆弱无人机飞行控制

IEEE Journal on Miniaturization for Air and Space Systems Pub Date : 2024-11-27 DOI: 10.1109/JMASS.2024.3507735

Xiangwei Bu;Ruining Luo;Jiaxi Chen;Humin Lei

引用次数: 0