区域卫星导航系统GEO卫星定轨观测模型

根据GEO导航卫星的轨道特性，给出了数学上严密的卫星伪距观测和载波相位观测模型，讨论了GEO卫星轨道和卫星钟差的解算条件以及单星定轨、多星组差定轨的可行性。     

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National indicators for observing ecosystem service change

Earth’s life-support systems are in rapid decline, yet we have few metrics or indicators with which to track these changes. The world’s governments are calling for biodiversity and ecosystem-service monitoring to guide and evaluate international conservation policy as well as to incorporate natural capital into their national accounts. The Group on Earth Observations Biodiversity Observation Network (GEO BON) has been tasked with setting up this monitoring system. Here we explore the immediate feasibility of creating a global ecosystem-service monitoring platform under the GEO BON framework through combining data from national statistics, global vegetation models, and production function models. We found that nine ecosystem services could be annually reported at a national scale in the short term: carbon sequestration, water supply for hydropower, and non-fisheries marine products, crop, livestock, game meat, fisheries, mariculture, and timber production. Reported changes in service delivery over time reflected ecological shocks (e.g., droughts and disease outbreaks), highlighting the immediate utility of this monitoring system. Our work also identified three opportunities for creating a more comprehensive monitoring system. First, investing in input data for ecological process models (e.g., global land-use maps) would allow many more regulating services to be monitored. Currently, only 1 of 9 services that can be reported is a regulating service. Second, household surveys and censuses could help evaluate how nature affects people and provides non-monetary benefits. Finally, to forecast the sustainability of service delivery, research efforts could focus on calculating the total remaining biophysical stocks of provisioning services. Regardless, we demonstrated that a preliminary ecosystem-service monitoring platform is immediately feasible. With sufficient international investment, the platform could evolve further into a much-needed system to track changes in our planet's life-support systems.     

GEO空间碎片光度测量标定方法的研究

基于GEO卫星、太阳和观测站的空间几何关系,建立了消除太阳赤纬角对地球同步轨道( Geostationary Orbit,GEO)卫星光学特性的影响的方法.以三轴稳定GEO盒状卫星缩比模型为研究样本,在不同太阳赤纬角下进行仿真实验光度测量,研究太阳赤纬角和相位角的空间几何关系,得出消除太阳赤纬角对其辐亮度值以及以相位角...     

顾及系统误差的GEO卫星几何法定轨PDOP值分析

针对GEO卫星几何法定轨中系统误差对PDOP值的影响进行研究,首先回顾了经典几何法定轨的基本原理,然后根据顾及系统误差的几何法定轨原理推导出PDOP值计算公式,并利用5个跟踪站的模拟数据,计算了多种系统误差情况下PDOP值。结果表明：系统误差对GEO卫星几何法定轨的PDOP值影响很大;采用顾及系统误差的几何法定轨方法可以较好地削弱系统误差对PDOP值的影响;国外布设跟踪站比仅在中国布设跟踪站能更好地削弱系统误差对PDOP值的影响。     

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基于全球MGEX数据的北斗导航星座精密轨道确定

利用全球分布的MGEX站观测数据,使用"两步法"以双差方式对北斗卫星进行精密定轨。主要研究北斗卫星轨道确定的处理策略,重点分析轨道确定的流程,并通过实验评价了3种不同类型轨道的精度。结果显示,MEO和IGSO卫星的定轨内符合精度优于0.2m,其中径向优于10cm,外符合精度优于30cm;GEO(以C05号为例)卫星外符合精度优于0.7m,且径向优于10cm。     

高轨卫星轨道预报中神经网络模型优化设计

高轨卫星是我国卫星导航系统的重要组成部分。提升该类卫星的轨道预报精度有利于用户定位精度的提高。提出了一种改进高轨卫星轨道预报精度的新方法。该方法避开了精化动力学模型的困难,尝试从轨道预报误差的规律中寻找突破。利用神经网络作为建立预报模型的工具,将某历史时刻的轨道预报误差作为训练样本,利用训练好的神经网络模型补偿当前时刻的预报轨道以提高轨道预报精度。对影响神经网络模型补偿效果的各因素进行了详细分析,制定了适应于高轨卫星短期、中期和长期预报的神经网络最优模型。利用实测数据进行了试验分析,结果表明:预报8,15及30 d应选择的训练步长分别为10,20及25 min;轨道预报8~30 d时,训练噪声均选取0.01。神经网络模型有效地改进了高轨卫星的轨道预报精度,预报4~30 d,轨道精度提高幅度为34.67%~82.37%不等。     

基于不同轨道高度iHCO通信卫星的CAPS星座优化研究

基于通信卫星的导航系统可以利用比地球静止轨道（Geostationary Earth Orbit,GEO）高约200 km的倾斜高圆轨道（inclined Highly Circular Orbit,iHCO）通信卫星组成导航星座.结合两种轨道高度的倾斜高圆轨道通信卫星,仿真分析了利用倾斜高圆轨道卫星组成的中国区域定位系统（Chinese Area Positioning System,CAPS）的导航性能,并讨论了利用倾斜高圆轨道卫星组成的中国区域定位系统实现中国区域覆盖的最佳星座布局.     

用基于Givens变换的QR分解计算类GPS广播星历参数

分析研究类GPS广播星历参数拟合算法的必要性,来介绍可用于解最小二乘问题的Givens变换,讨论使用Givens变换计算MEO和小倾角GEO卫星的类GPS广播星历参数的适用性,并用模拟数据进行验证。