精密單點定位相關(guān)技術(shù)問題研究
發(fā)布時間：2018-08-02 14:49
【摘要】：GPS精密單點定位一直是一個熱門話題,從它的出現(xiàn)到之后的發(fā)展,許多的學(xué)者都在進(jìn)行研究,由于該技術(shù)的應(yīng)用越加的廣泛,該定位方法具有操作簡便,不依賴其他參考站的特點,在近地衛(wèi)星定軌,國土調(diào)查等領(lǐng)域都應(yīng)很好的應(yīng)用,因此,研究精密單點定位具有很好的理論意義和實用價值。精密單點定位要求得到精密的衛(wèi)星軌道和衛(wèi)星鐘差信息通過IGS提供,進(jìn)一步需要進(jìn)行星歷內(nèi)插和鐘差內(nèi)插,以得到所需時刻的信息,目前已經(jīng)可以采用多種方法進(jìn)行內(nèi)插,并能達(dá)到比較高的精度,在衛(wèi)星距離求解中需要得到精確的衛(wèi)星距離,這需要考慮測站相關(guān)誤差、衛(wèi)星相關(guān)誤差影響以及傳播路徑相關(guān)誤差,需要進(jìn)行地球自轉(zhuǎn)改正、對流層延遲改正、衛(wèi)星天線相位偏差、電離層延遲改正等多種誤差改正。另外,由于信號在傳播過程中可能發(fā)生周跳,或者出現(xiàn)比較大的粗差,因此,必須對數(shù)據(jù)進(jìn)行預(yù)處理,以獲得更好的數(shù)據(jù)源。在精密單點定位中,還要涉及到參數(shù)估計,其目的是解算待求參數(shù),目前有卡爾曼濾波,最小二乘、序貫平差等多種方法。在學(xué)習(xí)了精密單點定位的理論基礎(chǔ)知識后,通過對整個流程的仔細(xì)分析,梳理,開始了對GPS精密單點定位的研究,本文的主要研究內(nèi)容如下： 第一：探討了用于精密單點定位的三種定位模型：傳統(tǒng)模型、UofC模型、無模糊度模型,并分析了進(jìn)行精密單點定位需要進(jìn)行的誤差改正模型,研究了數(shù)據(jù)預(yù)處理的方法,對參數(shù)估計方法進(jìn)行了介紹和比較。 第二：運用高次差法,相位減偽距法、寬巷相位減窄巷偽距法,消電離層法四種方法進(jìn)行周跳探測實驗,比較分析了四種方法在數(shù)據(jù)預(yù)處理方面的精度和使用范圍上的優(yōu)缺點。并提出在本文使用寬巷相位減窄巷相位與電離層殘差法聯(lián)合進(jìn)行數(shù)據(jù)與處理能較好的探測出周跳。 第三：結(jié)合實驗數(shù)據(jù)分析了地球自轉(zhuǎn)模型改正、相對論效應(yīng),對流層延遲等的改正大小,并研究了影響誤差大小的主要因素。 第四：比較不同濾波初值對卡爾曼濾波的影響,根據(jù)實驗數(shù)據(jù),研究了噪聲陣、過程噪聲矩陣、增益矩陣、預(yù)測協(xié)方差陣之間的關(guān)系。 第五：本文以matlab7.0作為編程工具分別使用最小二乘平差方法和卡爾曼濾波算法對數(shù)據(jù)進(jìn)行處理,卡爾曼濾波解算精度高,并且在收斂后單歷元解算精度高,因此不僅適合靜態(tài)單點定位還適合動態(tài)單點定位。分別使用快速星歷和最終星歷進(jìn)行卡爾曼濾波計算,對兩種星歷進(jìn)行比較。
[Abstract]:GPS precise single point positioning is a hot topic all the time. From its appearance to its development, many scholars are studying it. Because of the wide application of this technology, the method is easy to operate. Independent of the characteristics of other reference stations, it should be well applied in the field of near-Earth satellite orbit determination, land survey and so on. Therefore, the study of precise single-point positioning has good theoretical significance and practical value. Precise single point positioning requires precise satellite orbit and satellite clock difference information to be provided through IGS. It is further necessary to carry out ephemeris and clock difference interpolation to get the required time information. At present, many methods can be used to interpolate the satellite orbit and satellite clock difference. The accuracy of satellite distance should be obtained in the solution of satellite distance. It is necessary to take into account the errors of station correlation, satellite correlation error and propagation path, and to correct the rotation of the earth. Tropospheric delay correction, satellite antenna phase deviation, ionospheric delay correction and so on. In addition, due to the possibility of cycle slip or large gross error in the process of signal propagation, the data must be preprocessed to obtain a better data source. In precise single point positioning, parameter estimation is also involved, and its purpose is to calculate the parameters to be solved. At present, there are many methods such as Kalman filter, least square, sequential adjustment and so on. After studying the basic theoretical knowledge of precise single point positioning, through the careful analysis of the whole process and combing, the research on GPS precision single point positioning is started. The main contents of this paper are as follows: first, three kinds of positioning models for precise single point positioning are discussed: the traditional model of UofC, the model of no ambiguity, The error correction model of precision single point positioning is analyzed, the method of data preprocessing is studied, and the method of parameter estimation is introduced and compared. Second, four methods are used to detect cycle slips, such as high-order difference method, phase de-pseudo-range method, wide-lane phase de-pseudo-range method, and ionospheric elimination method. The advantages and disadvantages of the four methods in data preprocessing accuracy and application range are compared and analyzed. It is also proposed that the data processing and data processing by using the wide lane phase to reduce the narrow lane phase and the ionospheric residuals can detect the cycle slip well in this paper. Third, the correction magnitude of the Earth rotation model correction, relativistic effect and tropospheric delay are analyzed based on the experimental data, and the main factors affecting the error are studied. Fourthly, the effects of different initial filtering values on Kalman filtering are compared. Based on the experimental data, the relationships among noise matrix, process noise matrix, gain matrix and prediction covariance matrix are studied. Fifthly, this paper uses matlab7.0 as programming tool to process the data using least square adjustment method and Kalman filter algorithm, which has high accuracy and high precision of single epoch solution after convergence. Therefore, it is not only suitable for static single point positioning, but also suitable for dynamic single point positioning. The fast ephemeris and the final ephemeris are used to calculate the Kalman filter, and the two ephemeris are compared.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：P228.4
本文編號：2159785
[Abstract]:GPS precise single point positioning is a hot topic all the time. From its appearance to its development, many scholars are studying it. Because of the wide application of this technology, the method is easy to operate. Independent of the characteristics of other reference stations, it should be well applied in the field of near-Earth satellite orbit determination, land survey and so on. Therefore, the study of precise single-point positioning has good theoretical significance and practical value. Precise single point positioning requires precise satellite orbit and satellite clock difference information to be provided through IGS. It is further necessary to carry out ephemeris and clock difference interpolation to get the required time information. At present, many methods can be used to interpolate the satellite orbit and satellite clock difference. The accuracy of satellite distance should be obtained in the solution of satellite distance. It is necessary to take into account the errors of station correlation, satellite correlation error and propagation path, and to correct the rotation of the earth. Tropospheric delay correction, satellite antenna phase deviation, ionospheric delay correction and so on. In addition, due to the possibility of cycle slip or large gross error in the process of signal propagation, the data must be preprocessed to obtain a better data source. In precise single point positioning, parameter estimation is also involved, and its purpose is to calculate the parameters to be solved. At present, there are many methods such as Kalman filter, least square, sequential adjustment and so on. After studying the basic theoretical knowledge of precise single point positioning, through the careful analysis of the whole process and combing, the research on GPS precision single point positioning is started. The main contents of this paper are as follows: first, three kinds of positioning models for precise single point positioning are discussed: the traditional model of UofC, the model of no ambiguity, The error correction model of precision single point positioning is analyzed, the method of data preprocessing is studied, and the method of parameter estimation is introduced and compared. Second, four methods are used to detect cycle slips, such as high-order difference method, phase de-pseudo-range method, wide-lane phase de-pseudo-range method, and ionospheric elimination method. The advantages and disadvantages of the four methods in data preprocessing accuracy and application range are compared and analyzed. It is also proposed that the data processing and data processing by using the wide lane phase to reduce the narrow lane phase and the ionospheric residuals can detect the cycle slip well in this paper. Third, the correction magnitude of the Earth rotation model correction, relativistic effect and tropospheric delay are analyzed based on the experimental data, and the main factors affecting the error are studied. Fourthly, the effects of different initial filtering values on Kalman filtering are compared. Based on the experimental data, the relationships among noise matrix, process noise matrix, gain matrix and prediction covariance matrix are studied. Fifthly, this paper uses matlab7.0 as programming tool to process the data using least square adjustment method and Kalman filter algorithm, which has high accuracy and high precision of single epoch solution after convergence. Therefore, it is not only suitable for static single point positioning, but also suitable for dynamic single point positioning. The fast ephemeris and the final ephemeris are used to calculate the Kalman filter, and the two ephemeris are compared.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：P228.4
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