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地基GPS可降水量反演的测站相关性研究 被引量:2

Research on correlation of observation station in inverting of precipitable water vapor based on ground-based GPS
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摘要 地基GPS反演可降水量的基本原理是通过监测观测站上空天顶方向水汽总量,将观测中的“观测噪声”转变为需要的大气参数,而地基GPS局域网中相近测站的卫星高度角几乎相同,受到的大气延迟量则几近相同,因此局域网中的相邻测站上空的天顶延迟量有很强的相关性,而利用GAMIT等软件解算出的大气可降水量虽能消除相关性,却会呈现一定的系统偏差,为了获得测站上空的绝对大气可降水量,通过引入网外长基线IGS参考站的方法消除系统偏差,并得出结论只要引入2~3个网外IGS参考站就可确保测站的绝对可降水量精度. The basic principle of inverting precipitalbe water vapor using ground-based GPS data is to transform"observation noise"into atmospheric parameters needed by monitoring the total amount of water vapor in zenith direction above the observatory,but the elevation angles of satellites are almost the same in the adjacent observation station in LAN of groundbased GPS and its atmospheric delay is nearly the same, so the delay over adjacent observation station of LAN has a strong correlation, we can eliminate the correlation by using software GAMIT, but it brings in system error. In order to get absolute atmospheric precipitation over the station,this paper brings in 2-3 IGS reference stations which is longbase line outside of the network to eliminate the system error, finally it concludes that we can ensure the accuracy of absolute precipitation over adjacent observation station by bringing in 2-3 IGS reference stations.
出处 《电子测量技术》 2014年第6期85-88,共4页 Electronic Measurement Technology
基金 上海市科委科技攻关计划(11511501902)支持
关键词 地基GPS 局域网 GAMIT软件 IGS参考站 可降水量 ground-based GPS LAN software GAMIT IGS reference station precipitable water vapor
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  • 1杨青,魏文寿,李军.塔克拉玛干沙漠及周边地区大气水汽量的时空变化[J].科学通报,2008,53(S2):62-68. 被引量:18
  • 2胡士强,敬忠良.粒子滤波算法综述[J].控制与决策,2005,20(4):361-365. 被引量:291
  • 3陈添宇,李照荣,陈乾,李宝梓.用GMS5卫星反演水汽场分析中国西北地区大气水汽分布的气候特征[J].大气科学,2005,29(6):864-871. 被引量:18
  • 4叶林,周弘,张洪,张杰.相位差的几种测量方法和测量精度分析[J].电测与仪表,2006,43(4):11-14. 被引量:53
  • 5徐淑英.我国的水汽输送和水分平衡[J].气象学报,1958,28:33-43.
  • 6TORREA D, GHINAMO G, DETOMA E, et al. Analysis of the accuracy of indoor GNSS measurements and positioning solution [C]. Toulouse: The European Navigation Conference-Global Navigation Satellite Systems, ENCGNSS, 2008: 22-25.
  • 7ARULAMPALAM S, MASKELL S, GORDON N, et al. A tutorial on particle filters for on-line non-linear/non-gaussian bayesian tracking [J]. IEEE Transactions on Signal Processing, 2002, 50(2): 174-188.
  • 8AGGARWAL P, SYED Z., ELSHEIMY N. Hybrid extended particle filter (HEPF) for integrated civilian navigation system[C]. Monterey: Position, Location and Navigation Symposium, IEEE/ION, 2008: 984-992.
  • 9BOLIC M, DJURIC P M, HONG S. Resampling algorithms for particle filters: A computational complexity perspective[J]. EURASIP Journal on Applied Signal Processing, 2004, 2004(15): 2267-2277.
  • 10BROWN R G, HWANG P Y C. Introduction to random signals and applied kalman filtering [M]. New York: John Wiley & Sons, Inc., 1997.438-457.

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