.png){kind=icon}
返回
Geometric precision evaluation methodology of multiple reference station network algorithms
.png){kind=icon}
PRE
AI
DOI：10.1007/s11771-013-1468-0.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
To evaluate the performance of real time kinematic (RTK) network algorithms without applying actual measurements, a new method called geometric precision evaluation methodology (GPEM) based on covariance analysis was presented. Three types of multiple reference station interpolation algorithms, including partial derivation algorithm (PDA), linear interpolation algorithms (LIA) and least squares condition (LSC) were discussed and analyzed. The geometric dilution of precision (GDOP) was defined to describe the influence of the network geometry on the interpolation precision, and the different GDOP expressions of above-mentioned algorithms were deduced. In order to compare geometric precision characteristics among different multiple reference station network algorithms, a simulation was conducted, and the GDOP contours of these algorithms were enumerated. Finally, to confirm the validation of GPEM, an experiment was conducted using data from Unite State Continuously Operating Reference Stations (US-CORS), and the precision performances were calculated according to the real test data and GPEM, respectively. The results show that GPEM generates very accurate estimation of the performance compared to the real data test.
Keyword:
network DGPS algorithms
geometric precision evaluation
covariance analysis
partial derivation algorithm
linear interpolation algorithm
least squares collocation
期刊
IF:
4.4
论文数:
5.2K
被引数:
1.0W
机构
引用论文
K antigens of Escherichia coli and virulence in urinary-tract infection: studies in a mouse model
OAAI
OAAI分享收藏分享收藏Differential acidity tolerance of tropical legumes grown for green manure in acid sulfate soils
PREAI
分享收藏Criterios de clasificación de la vivienda informal: una revisión sistemática PRISMA como herramienta para establecimiento y análisis de categorías.png)
rita_
OAAI
rita_IF0
OAAI分享收藏 没有更多内容
没有更多内容