PPP-AR reference satellite selection based on the observation quality factors

选择(遗传算法) 卫星 质量(理念) 遥感 计算机科学 环境科学 地质学 航空航天工程 人工智能 物理 量子力学 工程类
作者
Mengyuan Li,Guanwen Huang,Le Wang,Wei Xie
出处
期刊:Measurement Science and Technology [IOP Publishing]
卷期号:35 (6): 066309-066309
标识
DOI:10.1088/1361-6501/ad35dc
摘要

Abstract Precise point positioning ambiguity resolution (PPP-AR) can effectively improve positioning accuracy and convergence time. In PPP-AR, the double-difference ambiguity between satellite pairs must be fixed. Therefore, it requires the selection of one satellite as a reference to conduct single-difference observations. Usually, the satellite with the highest elevation is selected as the reference satellite, however, once this satellite has a cycle slip or signal interference, its ambiguity will be reinitialized, resulting in the calculated wide-lane and narrow-lane ambiguities are not accurate enough, which further affects all the ambiguities fixed rates and positioning accuracies. In this contribution, we propose a multi-indicators comprehensive evaluation method of the global navigation satellite system (GNSS) based on entropy weight-grey correlation analysis for reference satellite selection of PPP-AR. The comprehensive evaluation includes the observations index selection, the index normalization, the calculation of index entropy weight and the grey correlation analysis. According to the new method, the quality ranking of satellite observations for each epoch can be obtained, and the observation value with the highest ranking is used as the reference satellite during the PPP-AR. One-week observations from 243 multi-GNSS experiment stations are selected to conduct GPS-only, Galileo-only and BDS-3-only kinematic PPP-AR, and the reference satellite selection method using the highest-elevation and the proposed method is applied, respectively. The results show that the PPP performance for the new method can be improved in the positioning accuracies, convergence time and ambiguity fixed rates. The positioning accuracies of three-dimensional directions can be improved by about 5.54%, 8.81% and 6.02% for GPS, BDS-3 and Galileo, respectively. The average improvements of convergence time in the east, north and up directions are 4.67%, 2% and 4% for GPS, BDS-3 and Galileo, respectively. The ambiguity fixed rates are improved by 7.31%, 6.89% and 1.45% for GPS, BDS-3 and Galileo between the 80%-100% range, respectively.
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