| 题名: | 基于星载高精度GPS观测数据的大气密度反演 |
| 其他题名: | Thermospheric density derived from onboard GPS observation data |
| 作者: | 苗娟; 任廷领; 龚建村; 刘四清; 李志涛
|
| 作者部门: | 空间环境部
|
| 通讯作者: | Gong, Jian-Cun (gongjc@nssc.ac.cn)
|
| 关键词: | GPS观测数据
; 平运动
; 反弹道系数
; 热层大气密
|
| 刊名: | 地球物理学报
|
| ISSN号: | 0001-5733
|
| 出版日期: | 2016
|
| 卷号: | 59, 期号:10, 页码:3566-3572 | | 收录类别: | SCI
; EI
; CSCD
|
| 项目资助者: | 宇航动力学国家重点实验室开放基金项目（2014ADL-DW0303，2016ADL-DW304）
; 国家863计划（2015AA7033102B）
|
| 中文摘要: | 星载高精度GPS观测数据可提供卫星速度和位置信息，而卫星的运行轨迹又与所处位置的大气密度紧密相关，因此可通过求解大气阻力微分方程，由高精度GPS观测数据反演出卫星运行轨迹上的热层大气密度.本文从星载高精度GPS观测数据出发，给出大气密度的反演方法，以及平均平动参数nM、反弹道系数B两个重要参数的解算过程，并以天宫一号为例，给出反演结果与天宫一号观测数据的比对.结果表明，反演结果与观测值符合很好，两者的均方差在2012年1月1日、2月24日分别为8.6%和8.4%，说明利用星载GPS观测数据反演大气密度是有效、可行的，可成为今后获取高精度大气密度的一种方法. |
| 英文摘要: | Onboard GPS observation data of a satellite includes accurate information of velocity and location, which are closely related to atmospheric density. Therefore, these GPS information can be used to derive thermospheric density through integration of differential equation. This paper presents a new method of deriving atmospheric density with a high temporal resolution from precise orbit data of low earth orbiting (LEO) space objects, and also presents the solution procedure of mean motion nMand the inverse ballistic coefficient B which are the two most important parameters for retrieving density. Tiangong-1 is taken as an example to evaluate the effectiveness of the method. The result shows that the GPS-derived density is in good agreement with observed density with the average error 8.6% and 8.4% respectively on 1st January and 24th February in 2012 for Tiangong-1. This result indicates the method provides an effective and reliable way to obtain extensive and accurate thermospheric density. © 2016, Science Press. All right reserved. |
| 语种: | 中文
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| Citation statistics: |
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| 内容类型: | 期刊论文
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| URI标识: | http://ir.nssc.ac.cn/handle/122/5639
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| Appears in Collections: | 空间环境部_期刊论文
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| 2016593566-3572.pdf（1586KB） | 期刊论文 | 作者接受稿 | 限制开放 | | View
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| Recommended Citation: | |
苗娟,任廷领,龚建村,等. 基于星载高精度GPS观测数据的大气密度反演[J]. 地球物理学报,2016,59(10):3566-3572.
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