Estimation of Scintillation Indices: A Novel Approach Based on Local Kernel Regression Methods

We present a comparative study of computational methods for estimation of ionospheric scintillation indices. First, we review the conventional approaches based on Fourier transformation and low-pass/high-pass frequency filtration. Next, we introduce a novel method based on nonparametric local regres...

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Bibliographic Details
Published in:International journal of navigation and observation 2016, Vol.2016, p.1-18
Main Authors: Ouassou, Mohammed, Kristiansen, Oddgeir, Gjevestad, Jon G. O., Jacobsen, Knut Stanley, Andalsvik, Yngvild L.
Format: Article
Language:English
Subjects:
Algorithms
Bias
Criteria
Datasets
Filtration
Fourier transformation
Ionosphere
Ionospherics
Kernels
Navigation
Regression
Satellites
Scintillation
Statistical analysis
Stochastic models
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Summary:We present a comparative study of computational methods for estimation of ionospheric scintillation indices. First, we review the conventional approaches based on Fourier transformation and low-pass/high-pass frequency filtration. Next, we introduce a novel method based on nonparametric local regression with bias Corrected Akaike Information Criteria (AICC). All methods are then applied to data from the Norwegian Regional Ionospheric Scintillation Network (NRISN), which is shown to be dominated by phase scintillation and not amplitude scintillation. We find that all methods provide highly correlated results, demonstrating the validity of the new approach to this problem. All methods are shown to be very sensitive to filter characteristics and the averaging interval. Finally, we find that the new method is more robust to discontinuous phase observations than conventional methods.
ISSN:1687-5990
1687-6008
DOI:10.1155/2016/3582176