基于北斗的定位算法研究

发布时间：2018-07-25 13:29

【摘要】：随着我国航天事业的发展和北斗卫星导航系统的逐渐成熟,我国自主建设的卫星系统——北斗卫星导航系统的定位研究受到了越来越多学者的关注。本文针对北斗二代卫星系统利用载波相位差分技术(Real-time kinematic,RTK)进行了定位解算研究。但在定位解算中存在整周模糊度解算的问题。目前,较为流行的模糊度解算方法是最小二乘降相关算法(Least-squares Ambiguity Decorrelated Adjustment,LAMBDA),其包括模糊度降相关和模糊度搜索两个步骤。针对模糊度降相关,分析了两种算法——LLL(A.K.Lenstra,H.W.Lenstra,L.Lovasz)算法和逆整数C holesky算法。针对LLL算法耗时长的问题进行了改进,并将改进LLL算法与上述两种算法进行了性能对比。实验结果表明,改进LLL算法与LLL算法的降相关效果明显比逆整数Cholesky算法好,但在耗时方面改进LLL算法与逆整数Cholesky算法较优。综合上述实验结果,本文采用改进LLL算法进行模糊度降相关。在模糊度搜索中,本文采用了人工鱼群算法(Artificial Fish Swarm Algorithm,AFSA)进行模糊度的搜索,并根据模糊度为整数的特点对其进行了改进。实验部分分别采用LAMBDA算法与改进AFSA算法对同一组卫星观测数据进行位置解算。结果表明,改进AFSA算法比LAMBDA算法的模糊度搜索准确性更高,解算时间更短。
[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.
【学位授予单位】：华北电力大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN967.1

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