scholarly journals A local Multivariate Polynomial Regression approach for ionospheric delay estimation of single-frequency NavIC receiver

2020 ◽  
Vol 2 (9) ◽  
Author(s):  
Mehul V. Desai ◽  
Shweta N. Shah
Keyword(s):  
Polynomial Regression ◽  
Ionospheric Delay ◽  
Delay Estimation ◽  
Single Frequency ◽  
Multivariate Polynomial ◽  
Regression Approach

scholarly journals Assessing the quality of ionospheric models through GNSS positioning error: methodology and results

GPS Solutions ◽  
2019 ◽  
Vol 24 (1) ◽  
Author(s):  
Adrià Rovira-Garcia ◽  
Deimos Ibáñez-Segura ◽  
Raul Orús-Perez ◽  
José Miguel Juan ◽  
Jaume Sanz ◽  
...  
Keyword(s):  
Satellite System ◽  
Ionospheric Delay ◽  
Single Frequency ◽  
Positioning Error ◽  
Dual Frequency ◽  
Error Sources ◽  
Ionospheric Models ◽  
Evaluation Metric ◽  
Global Navigation Satellite

Abstract Single-frequency users of the global navigation satellite system (GNSS) must correct for the ionospheric delay. These corrections are available from global ionospheric models (GIMs). Therefore, the accuracy of the GIM is important because the unmodeled or incorrectly part of ionospheric delay contributes to the positioning error of GNSS-based positioning. However, the positioning error of receivers located at known coordinates can be used to infer the accuracy of GIMs in a simple manner. This is why assessment of GIMs by means of the position domain is often used as an alternative to assessments in the ionospheric delay domain. The latter method requires accurate reference ionospheric values obtained from a network solution and complex geodetic modeling. However, evaluations using the positioning error method present several difficulties, as evidenced in recent works, that can lead to inconsistent results compared to the tests using the ionospheric delay domain. We analyze the reasons why such inconsistencies occur, applying both methodologies. We have computed the position of 34 permanent stations for the entire year of 2014 within the last Solar Maximum. The positioning tests have been done using code pseudoranges and carrier-phase leveled (CCL) measurements. We identify the error sources that make it difficult to distinguish the part of the positioning error that is attributable to the ionospheric correction: the measurement noise, pseudorange multipath, evaluation metric, and outliers. Once these error sources are considered, we obtain equivalent results to those found in the ionospheric delay domain assessments. Accurate GIMs can provide single-frequency navigation positioning at the decimeter level using CCL measurements and better positions than those obtained using the dual-frequency ionospheric-free combination of pseudoranges. Finally, some recommendations are provided for further studies of ionospheric models using the position domain method.

scholarly journals On Global Ionospheric Maps based winter-time GPS ionospheric delay with reference to the Klobuchar model

Pomorstvo ◽  
2019 ◽  
Vol 33 (2) ◽  
pp. 210-221
Author(s):  
David Brčić ◽  
Renato Filjar ◽  
Serdjo Kos ◽  
Marko Valčić
Keyword(s):  
Ionospheric Delay ◽  
Single Frequency ◽  
Electron Content ◽  
Ground Truth Data ◽  
Local Pattern ◽  
Satellite Positioning ◽  
Klobuchar Model ◽  
Global Ionospheric Maps ◽  
Winter Time ◽  
Delay Correction

Modelling of the ionospheric Total Electron Content (TEC) represents a challenging and demanding task in Global Navigation Satellite Systems (GNSS) positioning performance. In terms of satellite Positioning, Navigation and Timing (PNT), TEC represents a significant cause of the satellite signal ionospheric delay. There are several approaches to TEC estimation. The Standard (Klobuchar) ionospheric delay correction model is the most common model for Global Positioning System (GPS) single-frequency (L1) receivers. The development of International GNSS Service (IGS) Global Ionospheric Maps (GIM) has enabled the insight into global TEC dynamics. GIM analyses in the Northern Adriatic area have shown that, under specific conditions, local ionospheric delay patterns differ from the one defined in the Klobuchar model. This has been the motivation for the presented research, with the aim to develop a rudimentary model of the TEC estimation, with emphasis on areas where ground truth data are not available. The local pattern of the ionospheric delay has been modelled with wave functions based on the similarity of waveforms, considering diurnal differences in TEC behavior from defined TEC patterns. The model represents a spatiotemporal winter-time ionospheric delay correction with the Klobuchar model as a basis. The evaluation results have shown accurate approximation of the local pattern of the ionospheric delay. The model was verified in the same seasonal period in 2007, revealing it successfulness under pre-defined conditions. The presented approach represents a basis for the further work on the local ionospheric delay modelling, considering local ionospheric and space weather conditions, thus improving the satellite positioning performance for single-frequency GNSS receivers.

A Method for the Ionospheric Delay Estimation and Interpolation in a Local GPS Network

2005 ◽  
Vol 49 (1) ◽  
pp. 63-84 ◽  
Author(s):  
M.C. deLacy ◽  
F. Sans� ◽  
A.J. Gil ◽  
G. Rodr�guez-Caderot
Keyword(s):  
Ionospheric Delay ◽  
Delay Estimation ◽  
Gps Network

scholarly journals Regiomontan: A Regional High Precision Ionosphere Delay Model and Its Application in Precise Point Positioning

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2845
Author(s):  
Janina Boisits ◽  
Marcus Glaner ◽  
Robert Weber
Keyword(s):  
Precise Point Positioning ◽  
Ionospheric Delay ◽  
Single Frequency ◽  
External Information ◽  
Delay Model ◽  
Dual Frequency ◽  
Propagation Delays ◽  
Point Positioning ◽  
The Difference ◽  
High Level

Propagation delays of GNSS signals caused by the ionosphere can range up to several meters in zenith direction and need to be corrected. Geodetic receivers observing at two or more frequencies allow the mitigation of the ionospheric effects by forming linear combinations. However, single frequency users depend on external information. The ionosphere delay model Regiomontan developed at TU Wien is a regional ionospheric delay model providing high accuracy information with a latency of only a few hours. The model is based on dual-frequency phase observations of a regional network operated by EPOSA (Echtzeit Positionierung Austria) and partners. The corrections cover a geographical extent for receiver positions within Austria and are provided in the standardized IONEX format. The performance of Regiomontan as well as its application in Precise Point Positioning (PPP) were tested with our in-house PPP software raPPPid using the so-called uncombined model with ionospheric constraint. Various tests, e.g., analyzing the coordinate convergence behavior or the difference between estimated and modeled ionospheric delay, proving the high level of accuracy provided with Regiomontan. We conclude that Regiomontan performs at a similar level of accuracy as IGS final TEC maps, but with explicitly reduced latency.

scholarly journals On the properties of the classifier in case of small deviations of blood parameters from the norm

2021 ◽  
pp. 1-26
Author(s):  
Boris Mikhailovich Gavrikov ◽  
Mikhail Borisovich Gavrikov ◽  
Nadezhda Vladimirovna Pesryakova
Keyword(s):  
Mathematical Model ◽  
Human Health ◽  
Peripheral Blood ◽  
Polynomial Regression ◽  
Numerical Study ◽  
Small Deviation ◽  
Blood Parameters ◽  
Statistical Classification ◽  
Small Deviations ◽  
Regression Approach

A mathematical model is described and implemented, intended for the numerical study of the ability of the statistical classification method to interpolate and extrapolate. The classifier developed by the authors is based on the polynomial-regression approach and has probabilistic estimates. It is used to assess the state of human health based on the parameters of laboratory analysis of peripheral blood. The blood base is considered with a small deviation from the norm.

scholarly journals On regression approach to forecasting passenger demand in railway transport

2021 ◽  
Vol 80 (1) ◽  
pp. 45-52
Author(s):  
G. L. VENEDIKTOV ◽  
V. M. KOCHETKOV
Keyword(s):  
Polynomial Regression ◽  
Arima Model ◽  
Forecast Accuracy ◽  
Railway Transport ◽  
Specific Design ◽  
Passenger Traffic ◽  
Passenger Demand ◽  
Regression Approach ◽  
The Time Domain ◽  
Main Factor

Due to the fact that the autocorrelation of time series of passenger demand under normal conditions is, as a rule, practically undeveloped, traditional forecasting methods based on taking into account autocorrelation dependences are not effective enough. The article proposes a direct accounting of the main factor affecting the accuracy of forecasting, namely the factor of seasonal heterogeneity of demand. This accounting is made on the basis of polynomial regression for the time dependence of demand. A specific design example demonstrates the comparative advantages of this approach to assessing the forecast of demand for rail transport.The regression approach is applied to the weekly averaged demand metrics for the time domain, where these metrics are considered known from the sales history. If there is a weekly demand heterogeneity in the forecast zone, an algorithm is proposed to restore such heterogeneity from the initial data.The forecast accuracy based on the proposed method is compared with the results achieved on the basis of the ARIMA model, which reveals, according to preliminary estimates, fairly high accuracy parameters. It is shown on the calculated examples that for the series of demand, which can be considered typical for the sphere of passenger traffic, the regression approach gives the forecast accuracy higher than the ARIMA model. The reasons are considered, due to which, for typical series of passenger demand, the regression approach can be considered as more promising than methods that include taking into account autocorrelation.

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