Fast error analysis of continuous GNSS observations with missing data

By Machiel Simon Bos, Rui Fernandes, Simon D. P. Williams, Luísa Ferreira Bastos. Journal of Geodesy, 2013

427 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Atomic and Molecular Physics, and Optics, Oceanography

View Paper: https://www.semanticscholar.org/paper/8e3df306ee0c5996891206677096ca95a82d622e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. Janusz Bogusz
2. Anna Klos
3. Machiel Simon Bos

In Oceanography

1. Janusz Bogusz
2. Yunzhong Shen
3. Anna Klos
4. Machiel Simon Bos

Citations in the corpus

• Spatiotemporal filtering of regional GNSS network’s position time series with missing data using principle component analysis (2013, background): “However, most GNSS position time series contain missing data (Bos et al. 2013), since the GNSS stations may be built at different times and may stop collecting data for certain periods due to various reasons such as physical disturbance, equipment failure and replacement as well as data loss.”
• Detecting time-varying seasonal signal in GPS position time series with different noise levels (2017, methodology): “Parameters describing the initial position, velocity, seasonal signals, and combination of power-law and white noise model were estimated using Maximum Likelihood Estimation (MLE) as implemented in the Hector software (Bos et al. 2013).”