导航定位学报
導航定位學報
도항정위학보
Journal of Navigation and Positioning
2015年
3期
79-84
,共6页
对流层%时间序列%组合%抗差Kalman滤波%最小二乘方差分量估计
對流層%時間序列%組閤%抗差Kalman濾波%最小二乘方差分量估計
대류층%시간서렬%조합%항차Kalman려파%최소이승방차분량고계
troposphere%time series%combination%robust Kalman filtering%least-squares variances component estimation
由于目前 IGS 提供的对流层最终产品滞后约一星期到四星期,即使是超快速产品也滞后约3小时,这严重影响了目前实时气象的应用与需求,而且对流层产品的连续和实时组合的相关研究较少,大多集中在欧洲的试点项目。基于此,本文主要研究了一种对流层时间序列的短期高精度连续组合方法,利用各个分析中心给出的对流层时间序列,利用抗差 Kalman 滤波和最小二乘方差分量估计的原理,进行 GPS 或 VLBI 的短期时间序列的实时的或事后的连续组合。先估计各个分析中心产品偏差,同时计算出其权因子,然后利用 Kalman 滤波技术进行产品组合可以获得滞后的或实时的组合解及其标准差,组合解的平均精度达到0.85 mm。
由于目前 IGS 提供的對流層最終產品滯後約一星期到四星期,即使是超快速產品也滯後約3小時,這嚴重影響瞭目前實時氣象的應用與需求,而且對流層產品的連續和實時組閤的相關研究較少,大多集中在歐洲的試點項目。基于此,本文主要研究瞭一種對流層時間序列的短期高精度連續組閤方法,利用各箇分析中心給齣的對流層時間序列,利用抗差 Kalman 濾波和最小二乘方差分量估計的原理,進行 GPS 或 VLBI 的短期時間序列的實時的或事後的連續組閤。先估計各箇分析中心產品偏差,同時計算齣其權因子,然後利用 Kalman 濾波技術進行產品組閤可以穫得滯後的或實時的組閤解及其標準差,組閤解的平均精度達到0.85 mm。
유우목전 IGS 제공적대류층최종산품체후약일성기도사성기,즉사시초쾌속산품야체후약3소시,저엄중영향료목전실시기상적응용여수구,이차대류층산품적련속화실시조합적상관연구교소,대다집중재구주적시점항목。기우차,본문주요연구료일충대류층시간서렬적단기고정도련속조합방법,이용각개분석중심급출적대류층시간서렬,이용항차 Kalman 려파화최소이승방차분량고계적원리,진행 GPS 혹 VLBI 적단기시간서렬적실시적혹사후적련속조합。선고계각개분석중심산품편차,동시계산출기권인자,연후이용 Kalman 려파기술진행산품조합가이획득체후적혹실시적조합해급기표준차,조합해적평균정도체도0.85 mm。
as the final troposphere products provided by IGS were delayed for at least one week,even though the ultro-rap-id products also delayed for three hours,they all affected the real-time meteorological application,and also it’s rare to see the research papers on sequential or real-time combination for troposphere time series,most were focused on the experimental pro-jects in Europe.Thus,on this paper the method of high precision and sequential combination for short-term troposphere time series provided by several analysis centers was discussed in detail,with the technique of robust Kalman filter and least-squares variances component estimation,a real-time or lagging sequential combination of GPS or VLBI short-term time series can be manipulated.First the bias and weight factor for each analysis center solution were estimated,and then the combined solution and its standard deviation can be obtained by Kalman filtering,the average accuracy can approach 0.85mm.