کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8132515 | 1523279 | 2017 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Parallel resolution of large-scale GNSS network un-difference ambiguity
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
علوم فضا و نجوم
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چکیده انگلیسی
To increase redundant observations and estimate fractional cycle bias (FCB) in a global network and whole session, hundreds of globally distributed Global Navigation Satellite System (GNSS) tracking stations are required in the server side. However, the improvement of computational efficiency for FCB estimation and un-difference ambiguity fixing is a critical issue. In this paper, using a multi-node and multi-core platform based on Task Parallel Library, a strategy for multi-core un-difference parallel resolution is proposed. Based on MapReduce, a workflow for multi-node FCB parallel estimation and un-difference ambiguity parallel fixing is developed. As a result, the efficiency of FCB estimating and ambiguity fixing is improved significantly. Data from global International GNSS Service (IGS) tracking stations are used in the experiment. In the server side, the speed-up ratio of FCB estimation using a six-node and four-core platform reaches 14.76 times. In the user side, globally distributed user stations are applied to parallel ambiguity fixing, whereupon the speed-up ratio under the same platform is improved to 12.33 times. In addition, the average accuracy of static hourly solutions for 16 user stations improves from 2.50, 3.12 and 0.99Â cm to 1.30, 0.77 and 0.65Â cm in the vertical, east and north components, respectively.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Advances in Space Research - Volume 60, Issue 12, 15 December 2017, Pages 2637-2647
Journal: Advances in Space Research - Volume 60, Issue 12, 15 December 2017, Pages 2637-2647
نویسندگان
Linyang Li, Zhiping Lu, Yang Cui, Yupu Wang, Xian Huang,