發(fā)布時(shí)間：2018-07-25 13:29

【摘要】：隨著我國航天事業(yè)的發(fā)展和北斗衛(wèi)星導(dǎo)航系統(tǒng)的逐漸成熟,我國自主建設(shè)的衛(wèi)星系統(tǒng)——北斗衛(wèi)星導(dǎo)航系統(tǒng)的定位研究受到了越來越多學(xué)者的關(guān)注。本文針對北斗二代衛(wèi)星系統(tǒng)利用載波相位差分技術(shù)(Real-time kinematic,RTK)進(jìn)行了定位解算研究。但在定位解算中存在整周模糊度解算的問題。目前,較為流行的模糊度解算方法是最小二乘降相關(guān)算法(Least-squares Ambiguity Decorrelated Adjustment,LAMBDA),其包括模糊度降相關(guān)和模糊度搜索兩個(gè)步驟。針對模糊度降相關(guān),分析了兩種算法——LLL(A.K.Lenstra,H.W.Lenstra,L.Lovasz)算法和逆整數(shù)C holesky算法。針對LLL算法耗時(shí)長的問題進(jìn)行了改進(jìn),并將改進(jìn)LLL算法與上述兩種算法進(jìn)行了性能對比。實(shí)驗(yàn)結(jié)果表明,改進(jìn)LLL算法與LLL算法的降相關(guān)效果明顯比逆整數(shù)Cholesky算法好,但在耗時(shí)方面改進(jìn)LLL算法與逆整數(shù)Cholesky算法較優(yōu)。綜合上述實(shí)驗(yàn)結(jié)果,本文采用改進(jìn)LLL算法進(jìn)行模糊度降相關(guān)。在模糊度搜索中,本文采用了人工魚群算法(Artificial Fish Swarm Algorithm,AFSA)進(jìn)行模糊度的搜索,并根據(jù)模糊度為整數(shù)的特點(diǎn)對其進(jìn)行了改進(jìn)。實(shí)驗(yàn)部分分別采用LAMBDA算法與改進(jìn)AFSA算法對同一組衛(wèi)星觀測數(shù)據(jù)進(jìn)行位置解算。結(jié)果表明,改進(jìn)AFSA算法比LAMBDA算法的模糊度搜索準(zhǔn)確性更高,解算時(shí)間更短。
[Abstract]:With the development of China's aerospace industry and the gradual maturity of Beidou satellite navigation system, more and more scholars pay attention to the research on the positioning of Beidou satellite navigation system, which is a self-built satellite system in China. In this paper, the location solution of Beidou second generation satellite system using Real-time phase difference technique is studied. However, there is a problem of integer ambiguity resolution in the location solution. At present, the popular ambiguity resolution method is the least squares correlation algorithm (Least-squares Ambiguity Decorrelated adjustment Lambda), which consists of two steps: ambiguity reduction correlation and ambiguity search. Aiming at ambiguity reduction correlation, two algorithms, LLL (A.K. Lenstra-H.W. LenstraL.Lovasz) algorithm and inverse integer C holesky algorithm, are analyzed. In order to solve the problem of time-consuming LLL algorithm, the performance of the improved LLL algorithm is compared with the two algorithms mentioned above. The experimental results show that the improved LLL algorithm and the LLL algorithm have better correlation reduction effect than the inverse integer Cholesky algorithm, but the improved LLL algorithm and the inverse integer Cholesky algorithm are better in the aspect of time consuming. Based on the above experimental results, the improved LLL algorithm is used for ambiguity reduction correlation. In this paper, the artificial fish swarm algorithm (Artificial Fish Swarm algorithm) is used to search the ambiguity, and it is improved according to the integer ambiguity. In the experiment part, LAMBDA algorithm and improved AFSA algorithm are used to calculate the position of the same group of satellite observation data. The results show that the improved AFSA algorithm has higher accuracy and shorter solution time than the LAMBDA algorithm.
【學(xué)位授予單位】：華北電力大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TN967.1

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