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Cycle-slip Detection of GPS Carrier Phase with Methodology of SA4 Multi-wavelet Transform

机译:SA4多小波变换方法在GPS载波相位的周跳检测中

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摘要

That cycle-slips remain undetected will significantly degrade the accuracy of the navigation solution when using carrier phase measurements in global positioning system (GPS).In this paper,an algorithm based on length-4 symmetric/anti-symmetrc (SA4) orthogonal multi-wavelet is presented to detect and identify cycle-slips in the context of the feature of the GPS zero-differential carrier phase measurements.Associated with the local singularity detection principle,cycle-slips can be detected and located precisely through the modulus maxima of the coefficients achieved by the multi-wavelet transform.Firstly,studies are focused on the feasibility of the algorithm employing the orthogonal multi-wavelet system such as Geronimo-Hardin-Massopust (GHM),Chui-Lian (CL) and SA4.Moreover,the mathematical characterization of singularities with Lipschitz exponents is explained,the modulus maxima from wavelet to multi-wavelet domain is extended and a localization formula is provided from the modulus maxima of the coefficients to the original observation.Finally,field experiments with real receiver are presented to demonstrate the effectiveness of the proposed algorithm.Because SA4 possesses the specific nature of good multi-filter properties (GMPs),it is superior to scalar wavelet and other orthogonal multi-wavelet candidates distinctly,and for the half-cycle slip,it also remains better detection,location ability and the equal complexity of wavelet transform.
机译:当在全球定位系统(GPS)中使用载波相位测量时,仍未检测到周跳会大大降低导航解决方案的准确性。本文基于长度4对称/反对称(SA4)正交多提出了基于GPS零差分载波相位测量特征的小波检测和识别周期滑移。结合局部奇异性检测原理,可以通过系数的模极大值来检测并精确定位周期滑移首先,研究了采用Geronimo-Hardin-Massopust(GHM),Chui-Lian(CL)和SA4等正交多小波系统的算法的可行性。解释了用Lipschitz指数描述奇异点的特性,扩展了从小波到多小波域的模极大值,并提供了由模m最后,通过真实接收器的野外实验证明了该算法的有效性。由于SA4具有良好的多滤波器特性(GMP)的特殊性质,因此优于标量小波和与其他正交多小波候选者相比,它具有明显的优势,并且对于半周期滑移,它还具有更好的检测,定位能力和相等的小波变换复杂度。

著录项

  • 来源
    《中国航空学报(英文版)》 |2012年第2期|227-235|共9页
  • 作者

    HUO Guoping; MIAO Lingjuan;

  • 作者单位

    School of Automation, Beijing Institute of Technology, Beijing 100081, China;

    Key Laboratory of Intelligent Control and Decision of Complex Systems, Beijing 100081, China;

    School of Automation, Beijing Institute of Technology, Beijing 100081, China;

    Key Laboratory of Intelligent Control and Decision of Complex Systems, Beijing 100081, China;

  • 收录信息 中国科学引文数据库(CSCD);中国科技论文与引文数据库(CSTPCD);
  • 原文格式 PDF
  • 正文语种 chi
  • 中图分类
  • 关键词

  • 入库时间 2024-01-27 11:52:14
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