HOI延迟对LEO卫星简化动力学POD的影响

通常使用无电离层(IF)线性组合(LC)消除低地球轨道(LEO)卫星简化动力学精密定轨(POD)一阶电离层延迟误差,忽略了高阶电离层(HOI)延迟误差。随着LEO卫星POD技术的发展,计算不同轨道高度的HOI延迟并探索其变化已成为进一步提高POD精度的重要手段。首先,使用国际参考电离层-2016(IRI-2016)和国际地磁参考场第13代(IGRF-13)模型,计算电离层穿刺点(IPP)位置和地磁场强度。其次,使用平滑星载GNSS数据计算电离层斜路径总电子含量(STEC)。然后,分别计算GOCE、GRACE-A和SWARM-A/B卫星的二阶和三阶电离层延迟。最后,评估了HOI延迟对LEO卫星重叠轨道分析、卫星激光测距(SLR)检核和精密科学轨道(PSO)比较结果的影响。实验结果表明:HOI延迟对LEO卫星简化动力学POD的影响大约在毫米至厘米的数量级上;HOI延迟对LEO卫星简化动力学POD外符合精度的影响分别达到0.92,0.22,0.21和0.18 mm;随着LEO卫星轨道高度的增加,HOI延迟对LEO卫星简化动力学POD的影响减小。

LEO卫星系统对GSO卫星系统干扰规避技术研究

近年,低地轨道(Low Earth Orbit,LEO)卫星星座繁荣发展,LEO卫星系统和地球静止轨道(Geosynchronous Orbit,GSO)卫星系统同频共用情况非常普遍,同频段内LEO卫星系统需要规避GSO卫星系统的上下行干扰。LEO卫星系统对GSO卫星系统干扰规避方法和策略包含调整指向、更改频率、降低功率和关闭波束。在对系统干扰规避模式及干扰区域情况进行仿真基础上,结合LEO卫星系统特点,提出经过规避区域时切换信关站或者馈电链路关闭下行波束的方案。用户链路结合相控阵天线特点,信令波束通过上注星载相控阵天线波位表实现干扰规避;业务波束通过上注干扰规避区域对应的地面网格编码实现干扰规避,提出不同链路干扰规避实施方案和实现流程。

巨型LEO星座的时不变拓扑与航点路由设计

LEO卫星网是6G空地一体通信的重要组成部分,在带来低成本广覆盖等应用优势的同时,面临高动态和快切换等技术挑战。虽然卫星规律运动,星座图时变性也有章可循,但天基网的规模远高于地面网,不能简单延用因特网现有路由技术。综合应用快照变换和虚拟节点法,以卫星及星际链路为参考系,通过3步位置变换和极区收缩处理,得到巨型LEO星座的时不变拓扑,证明完全格网的适用性,并应用航点路由机制设计了本地卫星固定式路由算法,进一步给出了格网星座与循环图的同构性以及结构优化的探索方向。

LEO-RAN切片场景联合用户关联和动态资源分配算法

为了解决6G天地一体化网络的资源高效利用问题,提出了一种面向高密度低地球轨道卫星-无线接入网(LEO-RAN)切片场景的联合用户关联和动态资源分配算法。考虑不同切片的最小速率、最大时延及资源比例等约束,以频谱效率(SE)和不同切片服务水平协议(SLA)满意率(SSR)的加权和作为优化目标,建立用户关联和资源分配的联合优化问题。首先设计基于多智能体深度确定性策略梯度(MADDPG)的网络切片算法确定切片资源比例,然后采用基于拉格朗日对偶的用户关联算法确定最优的用户关联策略,最后通过轮询调度机制将资源分配给用户。仿真结果表明,所提算法在满足不同切片差异化SLA的同时能够有效提高SE。与基于MADDPG-RA、MATD3-LG、MATD3-RA、MASAC-LG和MASAC-RA算法相比,所提算法系统效用分别提升了2.0%、2.3%、5.7%、8.7%和9.4%。

Cooperative User-Scheduling and Resource Allocation Optimization for Intelligent Reflecting Surface Enhanced LEO Satellite Communication

Lower Earth Orbit(LEO) satellite becomes an important part of complementing terrestrial communication due to its lower orbital altitude and smaller propagation delay than Geostationary satellite. However, the LEO satellite communication system cannot meet the requirements of users when the satellite-terrestrial link is blocked by obstacles. To solve this problem, we introduce Intelligent reflect surface(IRS) for improving the achievable rate of terrestrial users in LEO satellite communication. We investigated joint IRS scheduling, user scheduling, power and bandwidth allocation(JIRPB) optimization algorithm for improving LEO satellite system throughput.The optimization problem of joint user scheduling and resource allocation is formulated as a non-convex optimization problem. To cope with this problem, the nonconvex optimization problem is divided into resource allocation optimization sub-problem and scheduling optimization sub-problem firstly. Second, we optimize the resource allocation sub-problem via alternating direction multiplier method(ADMM) and scheduling sub-problem via Lagrangian dual method repeatedly.Third, we prove that the proposed resource allocation algorithm based ADMM approaches sublinear convergence theoretically. Finally, we demonstrate that the proposed JIRPB optimization algorithm improves the LEO satellite communication system throughput.

基于区块链的GEO/LEO卫星网络安全认证技术研究

由于卫星网络高暴露、高时延的特点,不同系统星座组网进行遥控指令发布及遥测信息回传时,容易受到其他卫星恶意接入导致信息泄露。卫星网络安全认证成为天基测控实现过程中必须解决的技术问题。面向高轨和低轨双层卫星网络场景下的安全组网需求,提出了一种基于区块链的星间组网认证技术,该技术包括基于区块链的卫星身份认证和星间消息认证。研究设计将卫星临时身份登记上区块链,通过比对链上信息完成卫星的身份认证。为进一步增强消息传输安全性,采用椭圆曲线数字签名算法对星间消息进行签名验证。通过仿真分析,验证了所提技术能够以较小的时间开销满足卫星在组网认证阶段的多种安全需求。

OFDMA-Based Unsourced Random Access in LEO Satellite Internet of Things

This paper investigates the low earth orbit(LEO)satellite-enabled coded compressed sensing(CCS)unsourced random access(URA)in orthogonal frequency division multiple access(OFDMA)framework,where a massive uniform planar array(UPA)is equipped on the satellite.In LEO satellite communications,unavoidable timing and frequency offsets cause phase shifts in the transmitted signals,substantially diminishing the decoding performance of current terrestrial CCS URA receiver.To cope with this issue,we expand the inner codebook with predefined timing and frequency offsets and formulate the inner decoding as a tractable compressed sensing(CS)problem.Additionally,we leverage the inherent sparsity of the UPA-equipped LEO satellite angular domain channels,thereby enabling the outer decoder to support more active devices.Furthermore,the outputs of the outer decoder are used to reduce the search space of the inner decoder,which cuts down the computational complexity and accelerates the convergence of the inner decoding.Simulation results verify the effectiveness of the proposed scheme.

Big Data Application Simulation Platform Design for Onboard Distributed Processing of LEO Mega-Constellation Networks

Due to the restricted satellite payloads in LEO mega-constellation networks(LMCNs),remote sensing image analysis,online learning and other big data services desirably need onboard distributed processing(OBDP).In existing technologies,the efficiency of big data applications(BDAs)in distributed systems hinges on the stable-state and low-latency links between worker nodes.However,LMCNs with high-dynamic nodes and long-distance links can not provide the above conditions,which makes the performance of OBDP hard to be intuitively measured.To bridge this gap,a multidimensional simulation platform is indispensable that can simulate the network environment of LMCNs and put BDAs in it for performance testing.Using STK's APIs and parallel computing framework,we achieve real-time simulation for thousands of satellite nodes,which are mapped as application nodes through software defined network(SDN)and container technologies.We elaborate the architecture and mechanism of the simulation platform,and take the Starlink and Hadoop as realistic examples for simulations.The results indicate that LMCNs have dynamic end-to-end latency which fluctuates periodically with the constellation movement.Compared to ground data center networks(GDCNs),LMCNs deteriorate the computing and storage job throughput,which can be alleviated by the utilization of erasure codes and data flow scheduling of worker nodes.

Covert LEO Satellite Communication Aided by Generative Adversarial Network Based Cooperative UAV Jamming

In this paper,we study the covert performance of the downlink low earth orbit(LEO)satellite communication,where the unmanned aerial vehicle(UAV)is employed as a cooperative jammer.To maximize the covert rate of the LEO satellite transmission,a multi-objective problem is formulated to jointly optimize the UAV’s jamming power and trajectory.For practical consideration,we assume that the UAV can only have partial environmental information,and can’t know the detection threshold and exact location of the eavesdropper on the ground.To solve the multiobjective problem,we propose the data-driven generative adversarial network(DD-GAN)based method to optimize the power and trajectory of the UAV,in which the sample data is collected by using genetic algorithm(GA).Simulation results show that the jamming solution of UAV generated by DD-GAN can achieve an effective trade-off between covert rate and probability of detection errors when only limited prior information is obtained.

Multi-network-region traffic cooperative scheduling in large-scale LEO satellite networks

A low-Earth-orbit(LEO)satellite network can provide full-coverage access services worldwide and is an essential candidate for future 6G networking.However,the large variability of the geographic distribution of the Earth’s population leads to an uneven service volume distribution of access service.Moreover,the limitations on the resources of satellites are far from being able to serve the traffic in hotspot areas.To enhance the forwarding capability of satellite networks,we first assess how hotspot areas under different load cases and spatial scales significantly affect the network throughput of an LEO satellite network overall.Then,we propose a multi-region cooperative traffic scheduling algorithm.The algorithm migrates low-grade traffic from hotspot areas to coldspot areas for forwarding,significantly increasing the overall throughput of the satellite network while sacrificing some latency of end-to-end forwarding.This algorithm can utilize all the global satellite resources and improve the utilization of network resources.We model the cooperative multi-region scheduling of large-scale LEO satellites.Based on the model,we build a system testbed using OMNET++to compare the proposed method with existing techniques.The simulations show that our proposed method can reduce the packet loss probability by 30%and improve the resource utilization ratio by 3.69%.

For LEO Satellite Networks: Intelligent Interference Sensing and Signal Reconstruction Based on Blind Separation Technology

In LEO satellite communication networks,the number of satellites has increased sharply, the relative velocity of satellites is very fast, then electronic signal aliasing occurs from time to time. Those aliasing signals make the receiving ability of the signal receiver worse, the signal processing ability weaker,and the anti-interference ability of the communication system lower. Aiming at the above problems, to save communication resources and improve communication efficiency, and considering the irregularity of interference signals, the underdetermined blind separation technology can effectively deal with the problem of interference sensing and signal reconstruction in this scenario. In order to improve the stability of source signal separation and the security of information transmission, a greedy optimization algorithm can be executed. At the same time, to improve network information transmission efficiency and prevent algorithms from getting trapped in local optima, delete low-energy points during each iteration process. Ultimately, simulation experiments validate that the algorithm presented in this paper enhances both the transmission efficiency of the network transmission system and the security of the communication system, achieving the process of interference sensing and signal reconstruction in the LEO satellite communication system.

基于状态转移张量的LEO目标短期误差传播及碰撞概率计算

目前低轨区域空间目标数量不断增加且航天器轨道机动能力越来越强。结合LEO机动目标快速碰撞预警对于计算效率和计算精度的需求,在J2模型假设下,提出了一种基于状态转移张量的短期状态误差传播方法。该方法从航天器相对运动的角度,引入二阶状态转移张量来描述误差传播的非线性特征,给出了误差传播的近似解析表达式,在此基础上完成了碰撞概率计算。仿真结果表明:提出的方法对于LEO目标短期误差传播及碰撞概率计算具有良好的计算效率和计算精度。

Dynamic access task scheduling of LEO constellation based on space-based distributed computing

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.

Delay-optimal multi-satellite collaborative computation offloading supported by OISL in LEO satellite network

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.

Survivability model of LEO satellite constellation based on GERT with limited backup resources

Survivability is used to evaluate the ability of the satellite to complete the mission after failure,while the duration of maintaining performance is often ignored.An effective backup strategy can restore the constellation performance timely,and maintain good network communication performance in case of satellite failure.From the perspective of network utility,the low Earth orbit(LEO)satellite constellation survivable graphical eva-luation and review technology(GERT)network with backup satel-lites is constructed.A network utility transfer function algorithm based on moment generating function and Mason formula is proposed,the network survivability evaluation models of on-orbit backup strategy and ground backup strategy are established.The survivable GERT model can deduce the expected mainte-nance time of LEO satellite constellation under different fault states and the network utility generated during the state mainte-nance period.The case analysis shows that the proposed surviv-able GERT model can consider the satellite failure rate,backup satellite replacement rate,maneuver control replacement ability and life requirement,and effectively determine the optimal sur-vivable backup strategy for LEO satellite constellation with limi-ted resources according to the expected network utility.

LEO-5G下行同步FPGA设计与实现

随着低地球轨道卫星通信系统和第五代移动通信技术的融合,全球高速、低延迟的通信服务成为可能。本文主要分析了现场可编程门阵列(Field-Programmable Gate Array,FPGA)在LEO-5G下行同步中的应用需求,提出了基于FPGA的LEO-5G下行同步方案,展示技术测试结果验证了所提方案的有效性,为LEO-5G通信系统的下行同步提供了可行的技术路径。

LEO航天器太阳电池阵激光诱导电弧放电试验与分析

基于太阳电池阵空间电弧放电理论,对纳秒脉冲激光诱导太阳电池阵电弧放电机理进行分析,采用空间放电模拟试验系统,试验研究了低地球轨道(LEO)等离子体环境下纳秒脉冲激光诱导太阳电池阵电弧放电的功率密度阈值及其放电特性。试验结果表明:LEO等离子体环境下激光诱导太阳电池阵电弧放电的功率密度阈值约为1.08×10^(8)W/cm^(2),与无激光诱导相比,放电持续时间增加了20%,且每施加1次纳秒脉冲激光诱导电弧放电概率约为60%。对比分析不同工况下的太阳电池阵损伤效应可得:纳秒脉冲激光诱导电弧放电破坏绝缘层最严重,容易造成太阳电池阵中部分PN结短路失效,其损坏程度远远大于空间环境太阳电池串间电弧放电烧蚀损坏效应和盖玻片表面热应力损伤造成的PN结断路失效。此结论可为航天器太阳电池阵放电试验的措施及试验参数选取提供参考。

LEO星载GPS实时精密定轨伪模糊度随机过程参数优化

提出在定轨策略及其他变量不变的情况下,使用一种数值步进的搜索比较方法,以确定伪模糊度随机过程参数的最优设置。使用GRACE-C、SWARM-A两颗LEO卫星2021年doy92~101共10 d的GPS数据及同时段的CNT、MADOCA两种实时精密星历产品,以模拟在轨实时精密定轨的方式,对伪模糊度随机过程参数开展优化实验。结果表明,在伪模糊度参数最优值方案下,两颗LEO卫星的实时精密定轨三维位置误差(RMS)约为4.62~7.56 cm,相比于传统模糊度浮点解方案,使用CNT和MADOCA产品的实时定轨精度分别平均提升约39.15%和29.61%。

LEO卫星通信终端的RTT定位技术

低地球轨道(LEO)卫星通信互联网是未来满足万物智联、天空地一体化网络连接的6G移动通信网络重要组成部分。LEO卫星通信终端的移动性管理是LEO卫星网络运行管理的基本功能,而获取卫星终端的位置是实现移动性管理的基础。目前,全球卫星导航系统(GNSS)能够提供比较高的定位精度,但是当GNSS位置服务在受到环境遮蔽、外部干扰时可能失效,因此卫星通信终端需要一种独立于外部GNSS服务的自主定位方案。以未来LEO卫星互联网的通信信号为背景,提出一种基于往返时延(Round Trip Time,RTT)测量的LEO卫星通信终端自主定位体制,对OFDM卫星互联网信号的时延估计算法精度以及定位误差进行了理论计算和数字仿真,获得了本定位方案的均方根误差(RMSE)和几何稀度因子(GDOP),计算结果表明可以实现百米量级的快速定位,满足了移动性管理所需的千米量级位置信息的应用需求。

LEO卫星网络切换判决方法研究综述

低地球轨道(Low Earth Orbit,LEO)卫星网络因轨道高度低、传输时延小,可实现全球范围内全天时全天候无缝覆盖,在应急通信、情报侦查和灾害救援等领域得到了广泛应用。然而,由于LEO卫星与终端之间的高速相对运动导致频繁的切换问题,切换判决作为切换中的关键环节,直接影响切换是否能够成功以及切换性能的好坏,是实现可靠平滑切换的重要前提。结合LEO卫星网络切换判决方法研究进展,综述了基于单属性决策和多属性决策的2类切换判决方法;归纳了常用的图论模型切换判决方法;总结了机器学习在LEO卫星网络切换判决中的应用;结合常用评价性能指标对不同切换判决方法进行了对比分析;对未来LEO卫星网络切换研究值得关注的问题进行了展望,为后续相关研究提供解决思路。