Employing machine learning techniques for estimating the differential code biases of GPS satellites
IF 1
4区 地球科学
Q4 GEOGRAPHY, PHYSICAL
引用次数: 0
Abstract
In this study, the capabilities of Machine Learning (ML) are exploited to predict the Differential Code Biases (DCBs) of Global Positioning System (GPS) satellites from the broadcast Total Group De...利用机器学习技术估算 GPS 卫星的差分代码偏差
在这项研究中，利用机器学习（ML）的功能，从广播的总群组偏差（Total Group De）中预测全球定位系统（GPS）卫星的差分码偏差（DCB）。
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来源期刊
Journal of Spatial Science
地学-地质学
CiteScore
5.00
自引率
5.30%
发文量
25
审稿时长
>12 weeks
期刊介绍：
The Journal of Spatial Science publishes papers broadly across the spatial sciences including such areas as cartography, geodesy, geographic information science, hydrography, digital image analysis and photogrammetry, remote sensing, surveying and related areas. Two types of papers are published by he journal: Research Papers and Professional Papers.
Research Papers (including reviews) are peer-reviewed and must meet a minimum standard of making a contribution to the knowledge base of an area of the spatial sciences. This can be achieved through the empirical or theoretical contribution to knowledge that produces significant new outcomes.
It is anticipated that Professional Papers will be written by industry practitioners. Professional Papers describe innovative aspects of professional practise and applications that advance the development of the spatial industry.
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