Abstract
Abstract. Once the unknown integer ambiguity values are resolved, the GPS carrier phase observation will be transformed into a millimeter-level precision measurement. However, GPS observation are prone to a variety of errors, making it a biased measurement. There are two components in identifying integer ambiguities: estimation and validation. The estimation procedure aims to determine the ambiguity's integer values, and the validation step checks whether the estimated integer value is acceptable. Even though the theory and procedures for ambiguity estimates are well known, the topic of ambiguity validation is still being researched. The dependability of computed coordinates will be reduced if a false fixed solution emerges from an incorrectly estimated ambiguity integer value. In this study, the reliability of the fixed solution obtained by using several base stations in GPS positioning was investigated, and the coordinates received from these bases were compared. In a conclusion, quality control measures such as employing several base stations will improve the carrier phase measurement's accuracy.
Highlights
Global Navigation Satellite System (GNSS) positioning, including Global Positioning System (GPS) is based on determining the distance between satellites and a receiver
Ambiguity validation is a process of applying an acceptance test to validate the reliability of an estimated integer ambiguity
Three (3) hypotheses are identified in validating the float and fixed solution; 1) assuming that all unknown parameter are real-valued, 2) integer constraint is considered by assuming that the correct integer values of the ambiguity are known, and 3) to not put any restriction on the integer value (Teunissen and Kleusberg 1998)
Summary
Global Navigation Satellite System (GNSS) positioning, including Global Positioning System (GPS) is based on determining the distance between satellites and a receiver. The carrier phase measurements are contaminated with many biases due to satellite, satellite to receiver, and receiver dependent errors. These errors complicate the process to estimate the integer number and it may lead to an incorrect integer value as well as wrong positioning results. The integer nature of the ambiguity is ignored, and a normal least-square adjustment is performed to output float solutions, i.e., real number of ambiguity value, and their variance covariance matrix. The real valued float solution of the ambiguity is further modified in the second phase to accommodate for the integer restriction. Because the statistical characteristics of ambiguity do not truly follow the normal distribution function, ambiguity validation remains an unresolved topic and further research is needed (Feng and Jokinen 2017; Verhagen 2016, 2004)
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