计算机工程

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考虑敏感因子奇异值分解的北斗周跳探测方法

牟竹青 1,2,黄国勇 1,2,吴建德 1,2   

  1. (1.昆明理工大学 信息工程与自动化学院,昆明 650500; 2.云南省矿物管道输送工程技术研究中心,昆明 650500)
  • 收稿日期:2016-05-30 出版日期:2017-08-15 发布日期:2017-08-15
  • 作者简介:牟竹青(1991—),女,硕士研究生,主研方向为信号处理、GNSS精密定位;黄国勇(通信作者),副教授、博士;吴建德,教授、博士。
  • 基金项目:
    国家自然科学基金(61563024);云南省科技计划项目(2015ZC005,2013DH034)。

BeiDou Cycle-slip Detection Method Considering Sensitive Factor Signular Value Decomposition

MU Zhuqing 1,2,HUANG Guoyong 1,2,WU Jiande 1,2   

  1. (1.Faculty of Information Engineering and Automation,Kunming University of Science and Technology,Kunming 650500,China; 2.Yunnan Province Engineering Technology Research Center for Mineral Pipeline Transportation,Kunming 650500,China)
  • Received:2016-05-30 Online:2017-08-15 Published:2017-08-15

摘要: 针对北斗导航系统中信噪比较高的周跳信号难以提取和定位的问题,提出一种基于敏感因子的奇异值分解(SVD)方法对周跳信号进行探测。利用相位减伪距法构造周跳检测量进行初步探测,对选取的周跳信号建立Hankel矩阵并做SVD分解,利用敏感因子在得到的分量信号中找出敏感分量,通过定位因子选择敏感分量所对应的奇异值进行信号重构,重构信号中的突变位置即发生周跳信号的历元。仿真结果表明,该方法较传统SVD方法能够更准确地定位发生周跳信号的历元。

关键词: 奇异值分解, 相位, 周跳检测量, 敏感因子, 定位因子

Abstract: In BeiDou Navigation Satellite Systen(BDS),the cycle-slip signal with high Signal to Noise Ratio(SNR) is difficult to be extracted and located.In order to solve this problem,the Singular Value Decomposition(SVD) method based on sensitive factor is used to detect the cycle-slip signal.The phase minus pseudorange method is used to construct the cycle-slip detection variable.The selected cycle-slip signal is used to construct the Hankel matrix and perform SVD.The component signal obtained by decomposition is used to find the sensitive component by using the sensitivity factor,and the signal is reconstructed by selecting the singular value corresponding to the sensitive component by the positioning factor.The abrupt position in the reconstructed signal is the epoch that generates the cycle-slip signal.Simulation results show that this method can locate the epoch which generates the cycle-slip signal more accurately than traditional SVD method.

Key words: Singular Value Decomposition(SVD), phase, cycle-slip detection variable, sensitive factor, positioning factor

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