本文選題：GPS　切入點：動態(tài)變形監(jiān)測　出處：《中南大學》2013年碩士論文　論文類型：學位論文

【摘要】：對大型結構建筑物進行變形監(jiān)測是把握其在施工運營階段穩(wěn)定性的必要措施,GPS由于定位精度高,測站之間無需通視,全天候觀測,自動化程度高等優(yōu)勢,己成為當今最先進、使用最廣泛的變形監(jiān)測手段之一。在變形監(jiān)測中,一般基線長度較短,電離層延遲等公共誤差可以通過差分技術消除,但多路徑效應在基線兩端不具有相關性,無法通過差分技術消除,因此多路徑效應是制約GPS變形監(jiān)測精度的關鍵因素之一。針對此問題,本文主要從以下幾個方面進行了研究： (1)研究了GPS多路徑效應的產生機理,對GPS載波相位多路徑效應的影響幅值、影響頻率等特性進行了系統(tǒng)的分析。 (2)對比了多路徑效應周日重復性周期的幾種計算方法,實驗結果表明,廣播星歷法、互相關系數最大法及均方根誤差最小法三種方法計算得到的多路徑效應周期具有一致性,采用實際計算得到的多路徑重復周期進行恒星日濾波結果要優(yōu)于標準恒星時周期。 (3)針對GPS高頻動態(tài)變形監(jiān)測中多路徑效應誤差存在很強的時間相關性的特點,給出一種基于一階高斯馬爾科夫過程的觀測噪聲函數模型估計方法,并推出基于此模型的擴充狀態(tài)向量法和相鄰時間組差法兩種改進卡爾曼濾波方法,分別采用這兩種方法及標準卡爾曼濾波處理一組GPS模擬動態(tài)數據,對結果進行了對比分析,實驗結果表明這兩種改進方法的去噪效果均優(yōu)于標準卡爾曼濾波法,均能有效地削弱多路徑效應的影響,提高定位精度。 (4)提出了基于小波與PCA相結合的GPS噪聲改正方法。該方法先通過小波對坐標序列進行多尺度分解,對高頻部分進行閡值化處理,削弱高頻隨機噪聲,再采用PCA方法對相關性較強的多路徑效應進行提取和消除。實測數據分析表明,該組合方法能有效地削弱多路徑效應及高頻隨機噪聲,較單一濾波方法具有一定的優(yōu)越性。圖28幅,表12個,參考文獻61篇。
[Abstract]:Deformation monitoring of large structural buildings is a necessary measure to grasp its stability in construction and operation. GPS has become the most advanced because of its high positioning accuracy, no need for common viewing between stations, all-weather observation, high degree of automation, and so on. One of the most widely used deformation monitoring methods. In deformation monitoring, common errors such as short baseline length, ionospheric delay and other common errors can be eliminated by differential technique, but the multipath effect is not relevant at both ends of the baseline. The multipath effect is one of the key factors that restrict the accuracy of GPS deformation monitoring. In order to solve this problem, this paper mainly studies the following aspects:. 1) the mechanism of GPS multipath effect is studied, and the influence of GPS carrier phase multipath effect on amplitude and frequency is analyzed systematically. The experimental results show that the multipath effect periods calculated by the broadcast ephemeris method, the maximum correlation number method and the root mean square error method are consistent. The calculated multipath repeated period is better than the standard star time period for star day filtering. In view of the strong time correlation of the multipath effect error in the dynamic deformation monitoring of GPS, a method for estimating the observation noise function model based on the first-order Gao Si Markov process is presented. Two improved Kalman filtering methods, the extended state vector method based on this model and the adjacent time component difference method, are presented. The two methods and the standard Kalman filter are used to process a set of GPS simulation dynamic data respectively, and the results are compared and analyzed. The experimental results show that the two improved methods are better than the standard Kalman filter, which can effectively reduce the effect of the multipath effect and improve the positioning accuracy. (4) A method of GPS noise correction based on wavelet and PCA is proposed. Firstly, the coordinate sequence is decomposed by wavelet, and the high frequency part is treated with threshold value, which weakens the random noise of high frequency. Then the PCA method is used to extract and eliminate the multipath effect which has strong correlation. The analysis of the measured data shows that the combined method can effectively reduce the multipath effect and the high frequency random noise. Compared with the single filtering method, there are 28 figs, 12 tables and 61 references.
【學位授予單位】：中南大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：P228.4;TU196.1

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