Modified three carrier ambiguity resolution method for Beidou RTK

ZHANG Guan-xian; WANG Ling; HUANG Wen-de

doi:10.13873/j.1000-9787(2018)06-0048-04

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Modified three carrier ambiguity resolution method for Beidou RTK

更新时间：2025-09-11

- Modified three carrier ambiguity resolution method for Beidou RTK
- Issue 6, Pages: 48-51+55(2018)
- 作者机构：
  
  1. 湖南大学电气与信息工程学院
  2. 国防科技大学机电工程与自动化学院
- 作者简介：
- 基金信息：
- DOI：10.13873/j.1000-9787(2018)06-0048-04
  CLC： P228.4
- Published：2018
- 稿件说明：
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ZHANG Guan-xian, WANG Ling, HUANG Wen-de. Modified three carrier ambiguity resolution method for Beidou RTK[J]. 2018, (6): 48-51+55.
DOI：

ZHANG Guan-xian, WANG Ling, HUANG Wen-de. Modified three carrier ambiguity resolution method for Beidou RTK[J]. 2018, (6): 48-51+55. DOI： 10.13873/j.1000-9787(2018)06-0048-04.

摘要

针对实时动态(RTK)载波相位差分技术中常用的几何模型和无几何模型模糊度解算方法分别存在的搜索效率低和固定成功率低等问题

通过综合分析两种模型的特点

提出了一种三频模糊度解算的改进方法(MTCAR)。选取了2个特性较优的超宽巷组合

采用无几何模型对二者进行模糊度固定

线性组合出误差特性更好的宽巷模糊度;在宽巷距离量的约束下

采用几何模型

对窄巷进行求解;还原出各原始载波的模糊度。通过北斗三频实测数据进行实验分析

结果表明:MTCAR方法的模糊度固定成功率优于几何模型的最小二乘模糊解相关平差(LAMBDA)方法和无几何模型的TCAR方法

且在解算效率上较应用最广的LAMBDA法提高了60%左右。

Abstract

Aiming at the problem of low searching efficiency and fixing success ratio exits in the methods for ambiguity resolution commonly used in geometry-based and geometry-free model

a modified three carrier ambiguity resolution method

MTCAR is proposed. The new method selects two combinations of extra wide lane which have excellent characteristics. The geometry-free model is used to fix their ambiguity

and on this basis

ambiguity of wide lane which has better error characteristics can be obtained. The ambiguity of narrow lane is fixed by using geometry-based model with the help of the wide lane. The ambiguity of each original carrier can be restored. Experimental analysis is carried out by Beidou triple-frequency measured data. Experimental result shows that the ambiguity fixing success rate of MTCAR is prior to LAMBDA of geometry-based model and TCAR of geometry-free model. Resolving efficiency is improved by about 60 % compared with the most commonly used LAMBDA algorithm.

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