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Statistical Characterisation of GNSS Data for a Stationary Receiver using Non-Gaussian Distributions Cover

Statistical Characterisation of GNSS Data for a Stationary Receiver using Non-Gaussian Distributions

By: Abu Bantu and  Józef Wiora  
Open Access
|Dec 2025

Figures & Tables

Fig. 1.

Probability density function (a) and cumulative distribution function (b) for latitude data with fitted distributions using weighted MLE.

Fig. 2.

Residual analysis of the selected distributions using P–P plot.

Estimated parameters with 95 % CIs and performance metrics for the fitted models applied to GNSS latitude data_

ModelParametersCI*AICBICRMSE
μ*σναλβ
×10−5×10−5×103 ×106×106×106
Laplace86420[805; 924]1.16−2.33−2.333.5 · 10−4
Skew-normal857210.50[825; 904]1.13−2.27−2.272.5 · 10−4
GH8450.060.051.390.43[841; 917]1.20−2.40−2.402.8 · 10−4
Skew-t861145.0[825; 897]1.16−2.32−2.322.6 · 10−4
Language: English
Page range: 338 - 346
Submitted on: Jun 26, 2025
|
Accepted on: Oct 29, 2025
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Published on: Dec 23, 2025
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open

© 2025 Abu Bantu, Józef Wiora, published by Slovak Academy of Sciences, Institute of Measurement Science
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.