重力梯度力矩作用下近地卫星自旋运动规律分析

为研究近地卫星自旋运动规律,建立了近地卫星在受摄动影响的轨道上运行并受重力梯度力矩作用下的姿态运动模型,推导了自旋角速率满足一定条件下自旋运动的进动角、章动角、自旋角的解析解,对重力梯度作用下的自旋姿态运动规律进行了仿真分析,并用仿真计算结果验证了解析解的正确性。在轨道面缓慢进动情况下,当卫星绕最大主惯量轴自旋时,给出了自旋角速率取值范围表达式,在该取值范围内卫星自旋运动能够跟随轨道面一起进动,自旋轴以恒定的平均角速率进动,章动角在小范围内波动。建立的自旋姿态运动模型和分析结论可用于近地卫星姿态失控后的姿态确定和预测、在轨姿态设计及在轨备份等。     

MEO/LEO双层卫星网络中层间链路的连接度分析

作为未来卫星移动通信系统的一个重要的研究方向,提出了一种由MEO卫星和LEO卫星共同组成的双层卫星网络(Double-Layer Satellite Network,DLSN),以更好为用户提供多媒体服务.作为多层卫星网络的一个重要的研究内容,连接不同高度上卫星的层间链路(Inter-Orbit-Links,IOLs)的特性对于整个DLSN网络的性能会有很大的影响.根据所设计的多层卫星网络的星座参数,通过对层间链路几何特性的研究,分析了多层卫星网络中MEO卫星与LEO卫星的连接度性能.采用计算机仿真的方法,给出了层间链路连接度的特性.结果表明,为了提高网络性能,在多层卫星网络中应按照一定参数有选择的建立层间链路,而不是简单的采用视距可见原则建立层间链路.     

近地轨道飞行器的光辐射背景环境

文章简要介绍了在可见光和红外波段深空和地球高层大气的光辐射源和辐射特性,包括辐射机制和强度、辐射的各向异性等,通过比较表明空间红外波段的背景辐射明显高出可见光波段近1个数量级;分析了在地球大气外进行对地观测时大气辉光辐射的角分布,指出了辐射的临边增亮特性。以上研究对于研制和开发新型航天器、利用太空资源以及未来的深空探测都具有实用价值。     

具有优先级的LEO卫星网络路由研究

文章提出了带有优先级的最短时延卫星路由策略,将业务分为话音业务和数据业务,根据业务时延要求的不同,优先处理话音业务,再根据源卫星、目的卫星的位置,计算路径延时的度量标准,以此得到经过优劣排序的候选路径集合,并对最佳路径进行计算。仿真结果表明,算法显著降低了话音业务的时延水平,有效提高通话质量。     

空间太阳能电站经济性分析

空间太阳能电站作为一项在空间进行大规模太阳能收集、转化并通过无线方式将电能传输到地面电网的宏伟航天工程,其经济可行性是决定其能否大规模发展的主要因素之一。本文基于多旋转关节空间太阳能电站方案,提出空间太阳能电站全生命周期阶段划分和成本分析流程,初步分析得到空间太阳能电站的全部成本大约为2 500亿元,对应全寿命周期的发电量约为2 400亿度电,得到的单位电量的成本约为1元/度电。     

适于低轨卫星IP网络的单核共享树组播算法(英文)

为了解决低轨卫星IP网络中现有典型源组播算法的信道资源浪费问题,本文提出了一套单核共享树组播算法,即核心群合并共享树(CCST)和加权核心群合并共享树(w-CCST)算法。CCST 算法包括动态近似中心(DAC)选核方法和核心群合并组播路径构建方法。DAC方法专为周期、规律运动的低轨卫星网络提出,不需要复杂的星上计算。在核心群合并方法中,以核节点作为初始核心群,通过核心群和剩余组成员的最短路径方法逐步扩展直至整棵组播树构建完成,从而使得组播树的树代价最小,大大提高了网络的带宽利用率和组播传输效率。w-CCST 算法中所提出的加权因子可以调整树代价和端到端传播时延之间的折衷程度,因此,可以通过调整加权因子来适度增大树代价、降低端到端传播时延以支持某些端到端时延要求苛刻的实时组播业务。最后,与低轨卫星 IP 网络中典型算法进行了性能比较,仿真结果说明,CCST 算法的平均树代价比其它算法显著降低,w-CCST 算法的平均端到端传播时延小于 CCST 算法。     

Core-based Shared Tree Multicast Routing Algorithms for LEO Satellite IP Networks

A new core-based shared tree algorithm, viz core-cluster combination-based shared tree （CCST） algorithm and the weighted version （i.e. w-CCST algorithm） are proposed in order to resolve the channel resources waste problem in typical source-based multicast routing algorithms in low earth orbit （LEO） satellite IP networks. The CCST algorithm includes the dynamic approximate center （DAC） core selection method and the core-cluster combination multicast route construction scheme. Without complicated onboard computation, the DAC method is uniquely developed for highly dynamic networks of periodical and regular movement. The core-cluster combination method takes core node as the initial core-cluster, and expands it stepwise to construct an entire multicast tree at the lowest tree cost by a shortest path scheme between the newly-generated core-cluster and surplus group members, which results in great bandwidth utilization. Moreover, the w-CCST algorithm is able to strike a balance between performance of tree cost and that of end-to-end propagation delay by adjusting the weighted factor to meet strict end-to-end delay requirements of some real-time multicast services at the expense of a slight increase in tree cost. Finally, performance comparison is conducted between the proposed algorithms and typical algorithms in LEO satellite IP networks. Simulation results show that the CCST algorithm significantly decreases the average tree cost against to the others, and also the average end-to-end propagation delay ofw-CCST algorithm is lower than that of the CCST algorithm.     

Measuring atmospheric density using GPS–LEO tracking data

We present a method to estimate the total neutral atmospheric density from precise orbit determination of Low Earth Orbit (LEO) satellites. We derive the total atmospheric density by determining the drag force acting on the LEOs through centimeter-level reduced-dynamic precise orbit determination (POD) using onboard Global Positioning System (GPS) tracking data. The precision of the estimated drag accelerations is assessed using various metrics, including differences between estimated along-track accelerations from consecutive 30-h POD solutions which overlap by 6 h, comparison of the resulting accelerations with accelerometer measurements, and comparison against an existing atmospheric density model, DTM-2000. We apply the method to GPS tracking data from CHAMP, GRACE, SAC-C, Jason-2, TerraSAR-X and COSMIC satellites, spanning 12 years (2001–2012) and covering orbital heights from 400 km to 1300 km. Errors in the estimates, including those introduced by deficiencies in other modeled forces (such as solar radiation pressure and Earth radiation pressure), are evaluated and the signal and noise levels for each satellite are analyzed. The estimated density data from CHAMP, GRACE, SAC-C and TerraSAR-X are identified as having high signal and low noise levels. These data all have high correlations with anominal atmospheric density model and show common features in relative residuals with respect to the nominal model in related parameter space. On the contrary, the estimated density data from COSMIC and Jason-2 show errors larger than the actual signal at corresponding altitudes thus having little practical value for this study. The results demonstrate that this method is applicable to data from a variety of missions and can provide useful total neutral density measurements for atmospheric study up to altitude as high as 715 km, with precision and resolution between those derived from traditional special orbital perturbation analysis and those obtained from onboard accelerometers.     

中低纬地区混合LEO星座增强GNSS UPPP收敛性能评估

针对全球卫星导航系统(GNSS)精密单点定位(PPP)收敛时间过长的问题,提出了利用低轨卫星(LEO)几何结构变化快的优势,增强GNSS非差非组合PPP(UPPP)的收敛性能。选取中低纬度地区28个能接收GPS、GALILEO和BDS3信号的测站观测数据,比较了极轨和混合LEO星座的增强效果。结果表明：混合LEO星座增强GPS、GALILEO和BDS组合系统时,各测站收敛时间减少60%～80%,70%的测站收敛速度优于极轨星座。当混合LEO星座增强单BDS时,CL和GCL组合系统的收敛时间相当,ENU方向定位误差变化基本一致。收敛时间从10～20 min下降至3 min以内,原因是混合LEO增强BDS定位时,大大改善了卫星的空间结构。     

近地卫星星历的高精度星载算法研究

随着星载计算机系统结构和性能的改善,利用星载计算机实现高精度的星历计算成为可能。本文针对近地轨道卫星提出了一种适合星上轨道预报的数值算法。通过采用简化的动力学模型和一种嵌套插值算法的积分器,有效提高了计算效率,降低了对星载计算系统的性能要求,从而实现高精度的卫星星历星载计算。该算法在星载计算机系统平台上进行仿真验证的结果表明,对于某飞行器可实现轨道预报1天优于1km的星历计算。