本文關鍵詞：GNSS整周模糊度估計方法研究　出處：《中國礦業(yè)大學(北京)》2016年博士論文　論文類型：學位論文

  更多相關文章： 全球導航衛(wèi)星系統(tǒng) 模糊度估計 模糊度搜索空間 整數(shù)最小二乘 模糊度搜索方法

【摘要】：隨著全球導航衛(wèi)星系統(tǒng)(Global Navigation Satellite System,GNSS)的建設和現(xiàn)代化發(fā)展,GNSS已廣泛應用于全球各領域中。這些應用對GNSS精度和可靠性的要求越來越高,有些應用需要近實時或實時定位。整周模糊度的快速、準確解算是實現(xiàn)和保證GNSS快速、高精度定位的關鍵因素之一,為此,本文著重對GNSS定位中整周模糊度的估計方法進行了深入研究。圍繞整周模糊度解算中搜索空間的確定和搜索策略進行了詳細分析和探討。依據(jù)GNSS整周模糊度估計問題與格上最近向量問題的等價性,將格中最近向量問題的搜索算法進行了改進和優(yōu)化,并應用于整周模糊度解算中,解決了整周模糊度快速解算問題。詳細討論了精密單點定位模糊度解算問題,分析了基于模糊度浮點解的靜態(tài)精密單點定位性能和應用效果。本文還對影響GNSS定位的電離層電子含量的計算作了一些介紹。主要的研究內(nèi)容及成果如下:(1)模糊度搜索空間的大小是影響模糊度解算效率的主要因素之一。針對傳統(tǒng)確定模糊度搜索空間的方法較為保守,致使搜索空間過大,提出了一種基于最小二乘模糊度降相關平差法(LAMBDA)的改進方法。首先,在介紹混合整數(shù)最小二乘方法的基礎上,以LAMBDA方法為例,對其搜索空間確定的三種方法進行詳細分析和對比,評價了這些經(jīng)典方法的優(yōu)缺點。然后,定義了搜索空間的一個影響因子,并結合LAMBDA方法提出了確定模糊度搜索空間的修正公式�；诜抡婧蛯崪y數(shù)據(jù)進行實驗,結果表明,該方法在保證獲得期望模糊度組數(shù)的前提下,其確定的模糊度搜索空間包含的整數(shù)點個數(shù)更小,可保證90%以上實際模糊度組數(shù)接近于期望值。(2)在模糊度域內(nèi)搜索的方法中,Bootstrapping方法解算效率高,但成功率偏低。整數(shù)最小二乘方法理論嚴密,模糊度解算成功率高,但解算效率相對較低。為保證整周模糊度的解算效率和成功率,綜合Bootstrapping方法和LAMBDA方法,提出一種以Bootstrapping成功率為約束條件,以R-Ratio檢驗為確認原則,基于部分搜索的模糊度解算方法。實驗分析表明,與原有算法相比,該算法在保證模糊度固定成功率滿足預設值的條件下,能更快速地固定模糊度,較適用于高維模糊度快速解算。(3)模糊度估計是混合整數(shù)最小二乘問題,實際上也是格中的最近向量問題。在簡要介紹解決最近向量問題的搜索算法基礎上,針對現(xiàn)有模糊度搜索方法仍不能很好滿足快速定位的需求,將M-VB搜索算法作了兩方面改進,并應用于模糊度解算中:一是優(yōu)化了該算法執(zhí)行過程中更新上界的問題;二是提出借助Bootstrapped估計值來確定其搜索空間半徑的方法�；诜抡鏀�(shù)據(jù)和實測數(shù)據(jù),分別在降相關和不降相關條件下,將上述改進方法與LAMBDA方法、MLAMBDA方法進行了對比分析。結果表明,改進的M-VB算法比另外兩種方法能更快固定整周模糊度。(4)以基于小數(shù)(Fractional Cycle Bias,FCBs)改正的模糊度固定方法為基礎,詳細介紹了靜態(tài)精密單點定位(Precise Point Positioning,PPP)模糊度固定的基本過程,并系統(tǒng)分析了基于模糊度固定解PPP定位的優(yōu)缺點。在此基礎上,利用Bernese 5.0軟件和CSRS(Canadian Spatial Reference System)PPP軟件定量分析了PPP浮點解參數(shù)估計值的精度及收斂時間等情況。最后,針對傳統(tǒng)測量方式布設近井點成本高、精度不統(tǒng)一等問題,提出利用精密軌道和星歷產(chǎn)品,采用PPP技術建立近井點。結果表明,點位精度優(yōu)于5 cm,靜態(tài)PPP技術可應用于近井點測量。(5)電離層總電子含量(Total Electron Content,TEC)是影響衛(wèi)星導航定位的主要誤差源之一。在詳細分析GNSS定位模型和定位誤差源后,介紹了一種簡單的電離層TEC計算方法。為驗證該方法的計算精度,分別利用太陽活動低年和太陽活動高年低、中、高維度的四個時段IGS數(shù)據(jù)進行了實驗分析,結果表明,該方法計算的TEC與IGS發(fā)布的TEC相差較小,約90%的殘差值在±3 TECU內(nèi),并且該方法在太陽活動低年的適用性更好。另外,與普通內(nèi)插方法相比,該方法計算的TEC精度更高。
[Abstract]:With the development of the global navigation satellite system (Global Navigation Satellite System (GNSS)), GNSS has been widely used in all fields of the world. These applications are becoming more and more demanding for GNSS accuracy and reliability, and some applications need near real-time or real-time positioning. The fast and accurate solution of integer ambiguity is one of the key factors to achieve and ensure the location of GNSS in a fast and high-precision way. Therefore, this paper focuses on the estimation of integer ambiguity in GNSS positioning. The determination and search strategy of the search space in the integer ambiguity resolution are analyzed and discussed in detail. On the basis of GNSS integer ambiguity estimation problem of equivalence theory and the closest vector problem, the search algorithm in the lattice closest vector problem is improved and optimized, and applied to the ambiguity solution, solves fast ambiguity resolution problem. The ambiguity resolution of precision single point positioning is discussed in detail, and the performance and application effect of static precision single point positioning based on Fuzzy floating-point solution are analyzed. The calculation of the ionospheric electron content which affects the GNSS positioning is also introduced in this paper. The main research contents and achievements are as follows: (1) the size of fuzzy search space is one of the main factors that affect the efficiency of ambiguity resolution. In view of the fact that the traditional method of determining ambiguity search space is conservative, resulting in too large search space, an improved method based on least squares fuzzy degree correlation correlation adjustment (LAMBDA) is proposed. First, on the basis of introducing the mixed integer least squares method, taking the LAMBDA method as an example, the three methods of determining the search space are analyzed and compared in detail, and the advantages and disadvantages of these classical methods are evaluated. Then, an influence factor of the search space is defined, and a modified formula for determining the ambiguity search space is proposed with the LAMBDA method. Experiments based on simulated and measured data show that the proposed algorithm ensures smaller number of integer points in the fuzzy search space, while ensuring the expected number of fuzzy sets. It ensures that the number of 90% actual fuzzy sets is close to the expected value. (2) in the method of searching in the fuzzy domain, the efficiency of the Bootstrapping method is high, but the success rate is low. The theory of integer least squares is strict, and the success rate of ambiguity resolution is high, but the efficiency of calculation is relatively low. In order to ensure the efficiency and success rate of integer ambiguity resolution, a method of ambiguity resolution based on partial search is proposed, which takes Bootstrapping success rate as constraint condition and R-Ratio test as the recognition principle by combining the LAMBDA method and the Bootstrapping method. The experimental analysis shows that compared with the original algorithm, the algorithm can more quickly fix the fuzzy degree under the condition that the fixed rate of success of the ambiguity satisfies the preset value, and it is more suitable for the fast solution of high dimension ambiguity. (3) the fuzzy estimation is a mixed integer least square problem, and in fact it is also the nearest vector problem in the lattice. The basic search algorithm to solve the closest vector problem in brief, aiming at the existing ambiguity search method are still not very good to meet the rapid positioning needs, M-VB search algorithm has been improved in two aspects, and applied to the ambiguity: one is to optimize the implementation of the algorithm update the upper bound of the problem in the process; two is presented by using Bootstrapped estimation method to determine the radius of the search space. Based on the simulated data and measured data, the above improved methods are compared with the LAMBDA method and the MLAMBDA method respectively under the condition of correlation and no drop correlation. The results show that the improved M-VB algorithm can fix the whole week ambiguity faster than the other two methods. (4) based on the decimal (Fractional Cycle Bias, FCBs) based on correction of ambiguity fixing method, introduces the static precise point positioning (Precise Point Positioning, PPP) the basic process of fixing ambiguity, ambiguity and systematic analysis of the advantages and disadvantages of PPP positioning solution based on. On this basis, the accuracy and convergence time of PPP floating point parameter estimation are quantitatively analyzed by using Bernese 5 software and CSRS (Canadian Spatial Reference System) PPP software. Finally, aiming at the problems of high cost and unequal accuracy in the traditional measurement method, a precise wellbore and ephemeris product and PPP technology are used to establish near wellbore points. The results show that the point position accuracy is better than 5 cm, and the static PPP technology can be applied to the near well point measurement. (5) the total electron content of the ionosphere (Total Electron Content, TEC) is one of the main error sources affecting the navigation and positioning of the satellite. After a detailed analysis of the GNSS location model and the location error source, a simple method for calculating the ionosphere TEC is introduced. For the accuracy of the method is verified, using solar activity four hours IGS data in low and high solar activity is low, medium and high dimensions were analyzed. The results show that TEC and IGS calculated by this method is the release of TEC is small, the residual value of about 90% in 3 TECU, and this method has better applicability in the years of low solar activity. In addition, compared with the common interpolation method, the proposed method has higher TEC accuracy.
【學位授予單位】：中國礦業(yè)大學(北京)
【學位級別】：博士
【學位授予年份】：2016
【分類號】：P228.4

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