GPS基線計算之對流層延遲修正研究

Abstract

對流延遲效應可分為乾、溼對流層延遲效應二種,由於地面氣象資料無法 有效描述溼對流層之變化,造成溼對流層延遲效應難以有效修正;其對基線 成果之影響,分為絕對與相對二種,絕對誤差影響基線尺度,相對誤差影響 基線高程,其中以相對誤差對高程之影響較大 ,使得全球定位系統高程誤 差約為水平誤差之2∼3倍。因為對流層修正模式頗多 ,不同之計算軟體使 用不同之修正模式,究竟不同模式是否會對基線產生不同的結果,在不同之 測區使用何種模式較適切,以及就目前較佳之計算方法能達到何種等級之 精度 ,為本研究之主要目標。在本研究中,吾人從中央研究院地球科學研 究所設立之GPS連續記錄固定站之資料,選擇二條不同距離及高程差之基 線(S01R-S101 ,S105-S104),針對Saastamoinen、Modified Hopfield、 Essen-Froome三種常用之修正模式及測站附加參數法與實測地面氣象資料 、標準氣象模式加以分析比較。基本上,Saastamoinen與Modified Hopfield二種模式之差異極微,在基線較長時宜利用實測地面氣象資料,可 獲得較佳之成果 ,在高差較大時,宜選用Essen-Froome模式,所得成果較精 確,利用實測地面氣象資料和測站附加參數法吸收對流層殘餘誤差 ,則可 使相對高程精度達到2公分以內,為目前較佳之處理方法。 The tropospheric delay can be divied into the "dry" delay and the "wet" delay, owing to the wet term is more spatially and temporal varying than the dry term, thus is more difficult to model from surface meteorological data. The infiuences on GPS baseline result can be divied into two classes, the abso- lute and the relative tropospheric biases. The relative tropo- spheric biases introduce the height's biases into GPS baseline result, and is bigger than the absolute term in GPS relative positioning. Hence, the precision in height is 2-3 times the horizontial on Global Positioning System. Many troposphere models had been proposed, and different model in different GPS processing software. Which model will better fit in different case, and which order of precision in ifferent model, it is the aims in our study. We choose two baseline in different length and height from continuous-moni- toring GPS stations in the the Insititude of Earth Sciences, Academia Sinica. Three models for the troposphere,Saastamoinen、Modified Hopfield、Essen-Froome, will be tested using meteo data of observed and extrapolated from standard meteo model, and analyze the parameters estimated method for the tropo- spheric delay. Basically, the model of Saastamoinen and Modified Hopfield are almost identical. Using surface meteo data wwill get a better accuracy result in longer baseline; The Essen-Froome's model is more suitable in larger height difference's baseline. We obtain an magnitude of about 2cm in GPS height's precision by using parameters with observed meteo data to absorb the residual error of tropospheric delay.