arrow
Return

Improving DCB Estimation Using Uncombined PPP

delete2017-10-26
delete32
PRE
AI
项艳 (Yan Xiang) *
高阳 (Yang Gao)
DOI:10.1002/navi.207delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Differential Code Biases (DCBs) are much more relevant when GNSS data processing with code measurements is involved, such as in ionospheric sensing, positioning, and timing. The current approach to estimate DCBs is based on carrier-phase smoothed code observations together with ionospheric modeling. A limiting factor of the method is the effect of the leveling errors from the smoothing process on the DCB estimate. To reduce the leveling errors, a new DCB estimation method based on an Uncombined Precise Point Positioning (UPPP) model is proposed. A month's data from a global network in a high solar activity year from May 1 to 31, 2014 are processed to validate the method. The results show that most satellite DCB estimates are found to be more stable than when using the smoothed code method. The improvement can be up to about 0.22ns. The stability and accuracy of the receiver DCB estimates is also enhanced. Copyright (C) 2017 Institute of Navigation
Keywords:
DIFFERENTIAL CODE BIASES
GPS DATA
TIME
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Navigation-Journal of the Institute of Navigation cover
Navigation-Journal of the Institute of Navigation
IF:
2
Papers:
554
Citations:
1.6K

Organization

U
University of Calgary
Scholars:
3.8W
Papers: 3.3W
Citations: 52