This paper deals with system engineering and design methodology for super low altitude satel ites in the view of the com-putational mission analysis. Due to the slight advance of imaging instruments, such as the focus...This paper deals with system engineering and design methodology for super low altitude satel ites in the view of the com-putational mission analysis. Due to the slight advance of imaging instruments, such as the focus of camera and the image element of charge coupled device （CCD）, it is an innovative and economical way to improve the camera’s resolution to enforce the satel ite to fly on the lower altitude orbit. DFH-3, the mature satel ite bus de-veloped by Chinese Academy of Space Technology, is employed to define the mass and power budgets for the computational mis-sion analysis and the detailed engineering design for super low altitude satel ites. An effective iterative algorithm is proposed to solve the ergodic representation of feasible mass and power bud-gets at the flight altitude under constraints. Besides, boundaries of mass or power exist for every altitude, where the upper boundary is derived from the maximum power, while the minimum thrust force holds the lower boundary before the power reaching the initial value. What’s more, an analytical algorithm is employed to numerical y investigate the coverage percentage over the altitude, so that the nominal altitude could be selected from al the feasi-ble altitudes based on both the mass and power budgets and the repetitive ground traces. The local time at the descending node is chosen for the nominal sun-synchronous orbit based on the average evaluation function. After determining the key orbital ele-ments based on the computational mission analysis, the detailed engineering design on the configuration and other subsystems, like power, telemetry telecontrol and communication （TT＆amp;C）, and attitude determination and control system （ADCS）, is performed based on the benchmark bus, besides, some improvements to the bus are also implemented to accommodate the flight at a super low altitude. Two operation strategies, drag-free closed-loop mode and on/off open-loop mode, are presented to maintain the satel-lite’s altitude. Final y, a flight planning schedule for the satel ite is demonstrated from its launch into the initial altitude at the very beginning to its decay to death in the end.展开更多
By deploying the ubiquitous and reliable coverage of low Earth orbit(LEO)satellite networks using optical inter satel-lite link(OISL),computation offloading services can be provided for any users without proximal serv...By deploying the ubiquitous and reliable coverage of low Earth orbit(LEO)satellite networks using optical inter satel-lite link(OISL),computation offloading services can be provided for any users without proximal servers,while the resource limita-tion of both computation and storage on satellites is the impor-tant factor affecting the maximum task completion time.In this paper,we study a delay-optimal multi-satellite collaborative computation offloading scheme that allows satellites to actively migrate tasks among themselves by employing the high-speed OISLs,such that tasks with long queuing delay will be served as quickly as possible by utilizing idle computation resources in the neighborhood.To satisfy the delay requirement of delay-sensi-tive task,we first propose a deadline-aware task scheduling scheme in which a priority model is constructed to sort the order of tasks being served based on its deadline,and then a delay-optimal collaborative offloading scheme is derived such that the tasks which cannot be completed locally can be migrated to other idle satellites.Simulation results demonstrate the effective-ness of our multi-satellite collaborative computation offloading strategy in reducing task complement time and improving resource utilization of the LEO satellite network.展开更多
A dynamic multi-beam resource allocation algorithm for large low Earth orbit(LEO)constellation based on on-board distributed computing is proposed in this paper.The allocation is a combinatorial optimization process u...A dynamic multi-beam resource allocation algorithm for large low Earth orbit(LEO)constellation based on on-board distributed computing is proposed in this paper.The allocation is a combinatorial optimization process under a series of complex constraints,which is important for enhancing the matching between resources and requirements.A complex algorithm is not available because that the LEO on-board resources is limi-ted.The proposed genetic algorithm(GA)based on two-dimen-sional individual model and uncorrelated single paternal inheri-tance method is designed to support distributed computation to enhance the feasibility of on-board application.A distributed system composed of eight embedded devices is built to verify the algorithm.A typical scenario is built in the system to evalu-ate the resource allocation process,algorithm mathematical model,trigger strategy,and distributed computation architec-ture.According to the simulation and measurement results,the proposed algorithm can provide an allocation result for more than 1500 tasks in 14 s and the success rate is more than 91%in a typical scene.The response time is decreased by 40%com-pared with the conditional GA.展开更多
随着低空经济与智能交通系统的快速发展,以无人机(Unmanned Aerial Vehicle,UAV)为核心的低空通信网络(Low-altitude Communication Networks,LACN)已成为车联网(Internet of Vehicles,IoV)智能化演进的关键支撑技术。通过融合5G-A通感...随着低空经济与智能交通系统的快速发展,以无人机(Unmanned Aerial Vehicle,UAV)为核心的低空通信网络(Low-altitude Communication Networks,LACN)已成为车联网(Internet of Vehicles,IoV)智能化演进的关键支撑技术。通过融合5G-A通感一体化、星地一体化网络及移动边缘计算等前沿技术,低空通信网络为车联网提供了高可靠、低时延、广覆盖的通信与计算能力,有效解决了传统地面网络在复杂交通场景下面临的通信盲区、服务质量瓶颈和算力不足等问题。综述了低空通信网络在车联网中的应用,沿着技术纵向演进与应用横向拓展两条主线,从移动边缘计算、协同定位与感知以及信息娱乐服务3个核心维度深入剖析了现有研究的技术脉络、核心挑战与发展趋势。通过梳理分析发现,当前研究呈现出两大趋势:一是从传统模型驱动优化向数据驱动的智能决策模式转变,深度强化学习等人工智能技术被广泛应用;二是从单点技术优化向“空-地-云”一体化协同架构演进,数字孪生、多无人机协作等成为研究热点。进一步指出,发展无需外部设施支持的自主协同网络、实现空地资源的智能一体化调度,是未来实现全域无缝高精度服务的关键突破口。展开更多
In this paper, a new partial transmit sequence（PTS）scheme with low computational complexity is proposed for the problems of high computational complexity in the conventional PTS method. By analyzing the relationship...In this paper, a new partial transmit sequence（PTS）scheme with low computational complexity is proposed for the problems of high computational complexity in the conventional PTS method. By analyzing the relationship of candidate sequences in the PTS method under the interleaved partition method, it has been discovered that some candidate sequences generated by phase factor sequences have the same peak average power ratio（PAPR）. Hence, phase factor sequences can be optimized to reduce their searching times. Then, the computational process of generating candidate sequences can be simplified by improving the utilization of data and minimizing the calculations of complex multiplication. The performance analysis shows that, compared with the conventional PTS scheme, the proposed approach significantly decreases the computational complexity and has no loss of PAPR performance.展开更多
为提升低空风切变预报精度,本文综合运用欧洲中期天气预报中心第五代再分析资料[European Centre for Medium-Range Weather Forecasts(ECMWF)fifth-generation reanalysis data,ERA5]和美国国家环境预报中心(National Centers for Envi...为提升低空风切变预报精度,本文综合运用欧洲中期天气预报中心第五代再分析资料[European Centre for Medium-Range Weather Forecasts(ECMWF)fifth-generation reanalysis data,ERA5]和美国国家环境预报中心(National Centers for Environmental Prediction,NCEP)的FNL全球再分析资料(Final Operational Global Analysis)、先进星载热发射和反射辐射仪全球数字高程模型以及兰州中川机场的实况观测资料,采用中尺度数值天气预报模式(Weather Research and Forecasting Model,WRF)、WRF结合计算流体动力学(Computational Fluid Dynamics,CFD)方法、长短期神经网络(Long Short-Term Memory,LSTM)方法,对2021年4月15-16日兰州中川机场的两次风切变过程进行模拟分析。结果表明:(1)在小于1 km的网格中使用大涡模拟,WRF模式在单个站点风速模拟任务中表现更好,但在近地面水平风场风速模拟效果上,不如WRF模式结合计算流体力学模型方案;(2)对于飞机降落过程中遭遇的两次低空风切变的模拟,WRF-LES和WRF-CFD两种模式都可以模拟出第一次低空风切变,而第二次受传入模式的WRF风速数据值较小的影响,两种模式风速差都没有达到阈值,需要在后续工作中进一步验证;(3)低风速条件(6 m·s^(-1))下,基于LSTM的单变量风速预测模型平均绝对误差基本维持在0.59 m·s^(-1),能较好地把握不同地形与环流背景条件下风速变化的非线性关系,虽然受到WRF误差和观测要素不全的限制,多变量风速预测能在保证平均绝对百分比误差小于6.60%的情况下,以更高的计算效率和泛化能力实现风速预测。本文不仅验证了WRF-CFD和WRF-LES耦合方案在风场和低空风切变预报中的差异,还探讨了基于LSTM的风速预测的可行性和准确性,期望为提高风场模拟精度,缩短精细风场模拟时间提供新的视角和方法。展开更多
基金supported by the National Natural Science Foundation of China(11172020)the Fundamental Research Funds for the Central Universities+1 种基金the Aerospace Science and Technology Innovation Foundation of China Aerospace Science Corporationthe Innovation Fund of China Academy of Space Technology
文摘This paper deals with system engineering and design methodology for super low altitude satel ites in the view of the com-putational mission analysis. Due to the slight advance of imaging instruments, such as the focus of camera and the image element of charge coupled device （CCD）, it is an innovative and economical way to improve the camera’s resolution to enforce the satel ite to fly on the lower altitude orbit. DFH-3, the mature satel ite bus de-veloped by Chinese Academy of Space Technology, is employed to define the mass and power budgets for the computational mis-sion analysis and the detailed engineering design for super low altitude satel ites. An effective iterative algorithm is proposed to solve the ergodic representation of feasible mass and power bud-gets at the flight altitude under constraints. Besides, boundaries of mass or power exist for every altitude, where the upper boundary is derived from the maximum power, while the minimum thrust force holds the lower boundary before the power reaching the initial value. What’s more, an analytical algorithm is employed to numerical y investigate the coverage percentage over the altitude, so that the nominal altitude could be selected from al the feasi-ble altitudes based on both the mass and power budgets and the repetitive ground traces. The local time at the descending node is chosen for the nominal sun-synchronous orbit based on the average evaluation function. After determining the key orbital ele-ments based on the computational mission analysis, the detailed engineering design on the configuration and other subsystems, like power, telemetry telecontrol and communication （TT＆amp;C）, and attitude determination and control system （ADCS）, is performed based on the benchmark bus, besides, some improvements to the bus are also implemented to accommodate the flight at a super low altitude. Two operation strategies, drag-free closed-loop mode and on/off open-loop mode, are presented to maintain the satel-lite’s altitude. Final y, a flight planning schedule for the satel ite is demonstrated from its launch into the initial altitude at the very beginning to its decay to death in the end.
基金This work was supported by the National Key Research and Development Program of China(2021YFB2900600)the National Natural Science Foundation of China(61971041+2 种基金62001027)the Beijing Natural Science Foundation(M22001)the Technological Innovation Program of Beijing Institute of Technology(2022CX01027).
文摘By deploying the ubiquitous and reliable coverage of low Earth orbit(LEO)satellite networks using optical inter satel-lite link(OISL),computation offloading services can be provided for any users without proximal servers,while the resource limita-tion of both computation and storage on satellites is the impor-tant factor affecting the maximum task completion time.In this paper,we study a delay-optimal multi-satellite collaborative computation offloading scheme that allows satellites to actively migrate tasks among themselves by employing the high-speed OISLs,such that tasks with long queuing delay will be served as quickly as possible by utilizing idle computation resources in the neighborhood.To satisfy the delay requirement of delay-sensi-tive task,we first propose a deadline-aware task scheduling scheme in which a priority model is constructed to sort the order of tasks being served based on its deadline,and then a delay-optimal collaborative offloading scheme is derived such that the tasks which cannot be completed locally can be migrated to other idle satellites.Simulation results demonstrate the effective-ness of our multi-satellite collaborative computation offloading strategy in reducing task complement time and improving resource utilization of the LEO satellite network.
基金This work was supported by the National Key Research and Development Program of China(2021YFB2900603)the National Natural Science Foundation of China(61831008).
文摘A dynamic multi-beam resource allocation algorithm for large low Earth orbit(LEO)constellation based on on-board distributed computing is proposed in this paper.The allocation is a combinatorial optimization process under a series of complex constraints,which is important for enhancing the matching between resources and requirements.A complex algorithm is not available because that the LEO on-board resources is limi-ted.The proposed genetic algorithm(GA)based on two-dimen-sional individual model and uncorrelated single paternal inheri-tance method is designed to support distributed computation to enhance the feasibility of on-board application.A distributed system composed of eight embedded devices is built to verify the algorithm.A typical scenario is built in the system to evalu-ate the resource allocation process,algorithm mathematical model,trigger strategy,and distributed computation architec-ture.According to the simulation and measurement results,the proposed algorithm can provide an allocation result for more than 1500 tasks in 14 s and the success rate is more than 91%in a typical scene.The response time is decreased by 40%com-pared with the conditional GA.
文摘随着低空经济与智能交通系统的快速发展,以无人机(Unmanned Aerial Vehicle,UAV)为核心的低空通信网络(Low-altitude Communication Networks,LACN)已成为车联网(Internet of Vehicles,IoV)智能化演进的关键支撑技术。通过融合5G-A通感一体化、星地一体化网络及移动边缘计算等前沿技术,低空通信网络为车联网提供了高可靠、低时延、广覆盖的通信与计算能力,有效解决了传统地面网络在复杂交通场景下面临的通信盲区、服务质量瓶颈和算力不足等问题。综述了低空通信网络在车联网中的应用,沿着技术纵向演进与应用横向拓展两条主线,从移动边缘计算、协同定位与感知以及信息娱乐服务3个核心维度深入剖析了现有研究的技术脉络、核心挑战与发展趋势。通过梳理分析发现,当前研究呈现出两大趋势:一是从传统模型驱动优化向数据驱动的智能决策模式转变,深度强化学习等人工智能技术被广泛应用;二是从单点技术优化向“空-地-云”一体化协同架构演进,数字孪生、多无人机协作等成为研究热点。进一步指出,发展无需外部设施支持的自主协同网络、实现空地资源的智能一体化调度,是未来实现全域无缝高精度服务的关键突破口。
基金supported by the National Natural Science Foundation of China(6167309361370152)the Science and Technology Project of Shenyang(F16-205-1-01)
文摘In this paper, a new partial transmit sequence（PTS）scheme with low computational complexity is proposed for the problems of high computational complexity in the conventional PTS method. By analyzing the relationship of candidate sequences in the PTS method under the interleaved partition method, it has been discovered that some candidate sequences generated by phase factor sequences have the same peak average power ratio（PAPR）. Hence, phase factor sequences can be optimized to reduce their searching times. Then, the computational process of generating candidate sequences can be simplified by improving the utilization of data and minimizing the calculations of complex multiplication. The performance analysis shows that, compared with the conventional PTS scheme, the proposed approach significantly decreases the computational complexity and has no loss of PAPR performance.
文摘为提升低空风切变预报精度,本文综合运用欧洲中期天气预报中心第五代再分析资料[European Centre for Medium-Range Weather Forecasts(ECMWF)fifth-generation reanalysis data,ERA5]和美国国家环境预报中心(National Centers for Environmental Prediction,NCEP)的FNL全球再分析资料(Final Operational Global Analysis)、先进星载热发射和反射辐射仪全球数字高程模型以及兰州中川机场的实况观测资料,采用中尺度数值天气预报模式(Weather Research and Forecasting Model,WRF)、WRF结合计算流体动力学(Computational Fluid Dynamics,CFD)方法、长短期神经网络(Long Short-Term Memory,LSTM)方法,对2021年4月15-16日兰州中川机场的两次风切变过程进行模拟分析。结果表明:(1)在小于1 km的网格中使用大涡模拟,WRF模式在单个站点风速模拟任务中表现更好,但在近地面水平风场风速模拟效果上,不如WRF模式结合计算流体力学模型方案;(2)对于飞机降落过程中遭遇的两次低空风切变的模拟,WRF-LES和WRF-CFD两种模式都可以模拟出第一次低空风切变,而第二次受传入模式的WRF风速数据值较小的影响,两种模式风速差都没有达到阈值,需要在后续工作中进一步验证;(3)低风速条件(6 m·s^(-1))下,基于LSTM的单变量风速预测模型平均绝对误差基本维持在0.59 m·s^(-1),能较好地把握不同地形与环流背景条件下风速变化的非线性关系,虽然受到WRF误差和观测要素不全的限制,多变量风速预测能在保证平均绝对百分比误差小于6.60%的情况下,以更高的计算效率和泛化能力实现风速预测。本文不仅验证了WRF-CFD和WRF-LES耦合方案在风场和低空风切变预报中的差异,还探讨了基于LSTM的风速预测的可行性和准确性,期望为提高风场模拟精度,缩短精细风场模拟时间提供新的视角和方法。
