本文選題：大地測量反演 + 加權(quán)總體最小二乘��； 參考：《武漢大學(xué)學(xué)報(bào)(信息科學(xué)版)》2017年10期

【摘要】：針對(duì)地殼應(yīng)變參數(shù)反演模型中系數(shù)矩陣含隨機(jī)和非隨機(jī)元素及觀測數(shù)據(jù)存在相關(guān)性等情況,以部分變量誤差(partial-errors-in-variables,PEIV)模型為基礎(chǔ),采用了地殼應(yīng)變參數(shù)反演的加權(quán)總體最小二乘算法,該算法不受系數(shù)矩陣和權(quán)矩陣結(jié)構(gòu)的限制,能夠快速、有效解決系數(shù)矩陣含有隨機(jī)誤差的模型問題。結(jié)合推導(dǎo)得到的最小二乘改正項(xiàng)公式,對(duì)地殼反演模型中坐標(biāo)點(diǎn)誤差對(duì)反演參數(shù)求解的影響進(jìn)行了分析。通過對(duì)模擬數(shù)據(jù)和川滇地區(qū)的實(shí)際數(shù)據(jù)進(jìn)行處理,得出系數(shù)矩陣誤差對(duì)地殼應(yīng)變參數(shù)反演的影響主要受GPS站點(diǎn)坐標(biāo)值量級(jí)以及應(yīng)變參數(shù)量級(jí)的牽制。
[Abstract]:In view of the correlation between the coefficient matrix and the observed data in the inversion model of crustal strain parameters, based on the partial variable error partial-errors-in-variablespev model, the weighted global least square algorithm for the inversion of crustal strain parameters is adopted. This algorithm is not limited by the structure of coefficient matrix and weight matrix, and it can solve the model problem with random error in coefficient matrix quickly and effectively. Based on the derived formula of least square correction, the influence of coordinate point error on the solution of inversion parameters in crustal inversion model is analyzed. By processing the simulated data and the actual data in Sichuan-Yunnan area, it is concluded that the influence of coefficient matrix error on the inversion of crustal strain parameters is mainly controlled by the magnitude of coordinate values and strain parameters of GPS stations.
【作者單位】： 東華理工大學(xué)測繪工程學(xué)院;流域生態(tài)與地理環(huán)境監(jiān)測國家測繪地理信息局重點(diǎn)實(shí)驗(yàn)室;武漢大學(xué)測繪學(xué)院;
【基金】：國家自然科學(xué)基金(41664001,41204003) 江西省杰出青年人才資助計(jì)劃(20162BCB23050) 測繪地理信息公益性行業(yè)科研專項(xiàng)(201512026) 國家重點(diǎn)研發(fā)計(jì)劃(2016YFB0501405) 江西省教育廳科技項(xiàng)目(GJJ150595) 流域生態(tài)與地理環(huán)境監(jiān)測國家測繪地理信息局重點(diǎn)實(shí)驗(yàn)室開放基金(WE2015005) 對(duì)地觀測技術(shù)國家測繪地理信息局重點(diǎn)實(shí)驗(yàn)室開放基金(K201502) 東華理工大學(xué)博士科研啟動(dòng)基金(DHBK201113)~~
【分類號(hào)】：P207.1;P228

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