Three Carrier Ambiguity Resolutions: Generalised Problems, Models and Solutions

Yanming Feng, Bofeng Li
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引用次数: 12

Abstract

In this paper, the problems of three carrier phase ambiguity resolution (TCAR) and position estimation (PE) are generalized as real time GNSS data processing problems for a continuously observing network on large scale. In order to describe these problems, a general linear equation system is presented to uniform various geometry-free, geometry-based and geometry-constrained TCAR models, along with state transition questions between observation times. With this general formulation, generalized TCAR solutions are given to cover different real time GNSS data processing scenarios, and various simplified integer solutions, such as geometry-free rounding and geometry-based LAMBDA solutions with single and multiple-epoch measurements. In fact, various ambiguity resolution (AR) solutions differ in the floating ambiguity estimation and integer ambiguity search processes, but their theoretical equivalence remains under the same observational systems models and statistical assumptions. TCAR performance benefits as outlined from the data analyses in some recent literatures are reviewed, showing profound implications for the future GNSS development from both technology and application perspectives.
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三种载波歧义解决:一般化的问题、模型和解决方案
本文将三载波相位模糊度求解(TCAR)和位置估计(PE)问题推广为大规模连续观测网络的实时GNSS数据处理问题。为了描述这些问题,提出了统一各种无几何、基于几何和有几何约束的TCAR模型的一般线性方程组,以及观测时间之间的状态转移问题。在此基础上,给出了涵盖不同实时GNSS数据处理场景的广义TCAR解,以及各种简化整数解,如单历元和多历元测量的无几何舍入和基于几何的LAMBDA解。事实上,各种模糊度解决方案在浮动模糊度估计和整数模糊度搜索过程中存在差异,但在相同的观测系统模型和统计假设下,它们的理论等效性仍然存在。回顾了最近一些文献中数据分析概述的TCAR性能优势,从技术和应用的角度显示了对未来GNSS发展的深远影响。
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