scholarly journals Estimation and Analysis of IRNSS Satellites Differential Code Biases using Real Data

2019 ◽  
Vol 8 (3) ◽  
pp. 740-743
Keyword(s):  
Navigation System ◽  
Precise Measurement ◽  
Real Data ◽  
Electron Content ◽  
Total Electron ◽  
Precise Position ◽  
Indian Space Research Organization ◽  
Differential Code Biases ◽  
Receiver Dcb ◽  
The Many

IRNSS is a regional navigation system developed by the Indian Space Research Organization (ISRO) for precise position and navigation services over the Indian sub-continent. However, the IRNSS measurements are being affected by the many residuals or biases. Differential Code Biases (DCB) are very significant in the precise measurement of ionosphere Total Electron Content (TEC). In this paper, DCB of all available IRNSS satellites and receiver is derived from the pseudorange measurements of IRNSS on L5 and S-band signals. Results show that the estimated daily mean DCB of IRNSS satellites is in the range between -0.60 nanoseconds(ns) and 0.606 ns. Further, the receiver DCB is obtained as 7.904 ns.

scholarly journals Estimation and Analysis of GNSS Differential Code Biases (DCBs) Using a Multi-Spacing Software Receiver

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 443
Author(s):  
Ye Wang ◽  
Lin Zhao ◽  
Yang Gao
Keyword(s):  
Primary Source ◽  
Intermediate Frequency ◽  
Global Navigation Satellite Systems ◽  
Electron Content ◽  
Software Receiver ◽  
International Gnss Service ◽  
Total Electron ◽  
Satellite Systems ◽  
Differential Code Biases ◽  
Gnss Observations

In the use of global navigation satellite systems (GNSS) to monitor ionosphere variations by estimating total electron content (TEC), differential code biases (DCBs) in GNSS measurements are a primary source of errors. Satellite DCBs are currently estimated and broadcast to users by International GNSS Service (IGS) using a network of GNSS hardware receivers which are inside structure fixed. We propose an approach for satellite DCB estimation using a multi-spacing GNSS software receiver to analyze the influence of the correlator spacing on satellite DCB estimates and estimate satellite DCBs based on different correlator spacing observations from the software receiver. This software receiver-based approach is called multi-spacing DCB (MSDCB) estimation. In the software receiver approach, GNSS observations with different correlator spacings from intermediate frequency datasets can be generated. Since each correlator spacing allows the software receiver to output observations like a local GNSS receiver station, GNSS observations from different correlator spacings constitute a network of GNSS receivers, which makes it possible to use a single software receiver to estimate satellite DCBs. By comparing the MSDCBs to the IGS DCB products, the results show that the proposed correlator spacing flexible software receiver is able to predict satellite DCBs with increased flexibility and cost-effectiveness than the current hardware receiver-based DCB estimation approach.

scholarly journals New GGOS JWG3 on Improved understanding of space weather events and their monitoring

2020 ◽  
Author(s):  
Alberto Garcia-Rigo ◽  
Benedikt Soja
Keyword(s):  
Electron Density ◽  
Space Weather ◽  
International Association ◽  
Real Data ◽  
Weather Conditions ◽  
Electron Content ◽  
Vertical Total Electron Content ◽  
Total Electron ◽  
Weather Events ◽  
Space Geodetic Techniques

<p>Multiple space geodetic techniques are capable of measuring effects caused by space weather events. In particular, space weather events can cause ionospheric disturbances correlated with variations in the vertical total electron content (VTEC) or the electron density (Ne) of the ionosphere.</p><p>In this regard and in the context of the new Focus Area on Geodetic Space Weather Research within IAG’s GGOS (International Association of Geodesy; Global Geodetic Observing System), the Joint Working Group 3 on Improved understanding of space weather events and their monitoring by satellite missions has been created as part of IAG Commission 4, Sub-Commission 4.3 to run for the next four years.</p><p>Within JWG3, we expect investigating different approaches to monitor space weather events using the data from different space geodetic techniques and, in particular, combinations thereof. Simulations will be beneficial to identify the contribution of different techniques and prepare for the analysis of real data. Different strategies for the combination of data will also be investigated, in particular, the weighting of estimates from different techniques in order to increase the performance and reliability of the combined estimates. Furthermore, existing algorithms for the detection and prediction of space weather events will be explored and improved to the extent possible. Furthermore, the geodetic measurement of the ionospheric electron density will be complemented by direct observations from the Sun gathered from existing spacecraft, such as SOHO, ACE, SDO, Parker Solar Probe, among others. The combination and joint evaluation of multiple datasets with the measurements of space geodetic observation techniques (e.g. geodetic VLBI) is still a great challenge. In addition, other indications for solar activity - such as the F10.7 index on solar radio flux, SOLERA as EUV proxy or rate of Global Electron Content (dGEC)-, provide additional opportunities for comparisons and validation.</p><p>Through these investigations, we will identify the key parameters useful to improve real-time/prediction of ionospheric/plasmaspheric VTEC, Ne estimates, as well as ionospheric perturbations, in case of extreme solar weather conditions. In general, we will gain a better understanding of space weather events and their effect on Earth’s atmosphere and near-Earth environment.</p>

scholarly journals GNSS-Based Non-Negative Absolute Ionosphere Total Electron Content, its Spatial Gradients, Time Derivatives and Differential Code Biases: Bounded-Variable Least-Squares and Taylor Series

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5702 ◽  
Author(s):  
Yury Yasyukevich ◽  
Anna Mylnikova ◽  
Artem Vesnin
Keyword(s):  
Least Squares ◽  
Taylor Series ◽  
Taylor Series Expansion ◽  
Electron Content ◽  
Navigation Satellite ◽  
Mean Square ◽  
Total Electron ◽  
Spatial Gradients ◽  
Differential Code Biases ◽  
Global Navigation Satellite

Global navigation satellite systems (GNSS) allow estimating total electron content (TEC). However, it is still a problem to calculate absolute ionosphere parameters from GNSS data: negative TEC values could appear, and most of existing algorithms does not enable to estimate TEC spatial gradients and TEC time derivatives. We developed an algorithm to recover the absolute non-negative vertical and slant TEC, its derivatives and its gradients, as well as the GNSS equipment differential code biases (DCBs) by using the Taylor series expansion and bounded-variable least-squares. We termed this algorithm TuRBOTEC. Bounded-variable least-squares fitting ensures non-negative values of both slant TEC and vertical TEC. The second order Taylor series expansion could provide a relevant TEC spatial gradients and TEC time derivatives. The technique validation was performed by using independent experimental data over 2014 and the IRI-2012 and IRI-plas models. As a TEC source we used Madrigal maps, CODE (the Center for Orbit Determination in Europe) global ionosphere maps (GIM), the IONOLAB software, and the SEEMALA-TEC software developed by Dr. Seemala. For the Asian mid-latitudes TuRBOTEC results agree with the GIM and IONOLAB data (root-mean-square was < 3 TECU), but they disagree with the SEEMALA-TEC and Madrigal data (root-mean-square was >10 TECU). About 9% of vertical TECs from the TuRBOTEC estimates exceed (by more than 1 TECU) those from the same algorithm but without constraints. The analysis of TEC spatial gradients showed that as far as 10–15° on latitude, TEC estimation error exceeds 10 TECU. Longitudinal gradients produce smaller error for the same distance. Experimental GLObal Navigation Satellite System (GLONASS) DCB from TuRBOTEC and CODE peaked 15 TECU difference, while GPS DCB agrees. Slant TEC series indicate that the TuRBOTEC data for GLONASS are physically more plausible.

scholarly journals Comment on Choi et al. Correlation between Ionospheric TEC and the DCB Stability of GNSS Receivers from 2014 to 2016. Remote Sens. 2019, 11, 2657

2020 ◽  
Vol 12 (21) ◽  
pp. 3496 ◽  
Author(s):  
Jiahao Zhong ◽  
Jiuhou Lei ◽  
Xinan Yue
Keyword(s):  
Satellite System ◽  
Electron Content ◽  
Total Electron ◽  
Ionospheric Variability ◽  
Gnss Receivers ◽  
Code Bias ◽  
Receiver Dcb ◽  
Global Navigation Satellite ◽  
Long Term Variations

Choi et al. (2019) analyzed the correlation between the ionospheric total electron content (TEC) and the Global Navigation Satellite System (GNSS) receiver differential code bias (DCB) and concluded that the long-term variations of the receiver DCB are caused by the corresponding variations in the ionosphere. Unfortunately, their method is problematic, resulting in conclusions that are not useful. The long-term variations of the Global Positioning System (GPS) DCBs are primarily attributed to the GPS satellite replacement with different satellite block series under the zero-mean constraint condition, rather than the ionospheric variability.

scholarly journals A new method to estimate GPS satellite and receiver differential code biases using a network of LEO satellites

GPS Solutions ◽  
2021 ◽  
Vol 25 (2) ◽  
Author(s):  
Liangliang Yuan ◽  
Mainul Hoque ◽  
Shuanggen Jin
Keyword(s):  
Orbit Determination ◽  
Precise Orbit Determination ◽  
Low Earth Orbit ◽  
Global Navigation Satellite Systems ◽  
New Method ◽  
Electron Content ◽  
Vertical Total Electron Content ◽  
Total Electron ◽  
Leo Satellites ◽  
Differential Code Biases

AbstractThe differential code biases (DCBs) of the global positioning system (GPS) receiver onboard low-Earth orbit (LEO) satellites are commonly estimated by a local spherical symmetry assumption together with the known GPS satellite DCBs from ground-based observations. Nowadays, more and more LEO satellites are equipped with GPS receivers for precise orbit determination, which provides a unique chance to estimate both satellite and receiver DCBs without any ground data. A new method to estimate the GPS satellite and receiver DCBs using a network of LEO receivers is proposed. A multi-layer mapping function (MF) is used to combine multi-LEO satellite data at varying orbit heights. First, model simulations are conducted to compare the vertical total electron content (VTEC) derived from the multi-layer MF and the reference VTEC obtained from the empirical ionosphere model International Reference Ionosphere and Global Core Plasmasphere Model. Second, GPS data are collected from five LEO missions, including ten receivers used to estimate both the satellite and receiver DCBs simultaneously with the multi-layer MF. The results show that the GPS satellite DCB solutions obtained from space-based data are consistent with ground-based solutions provided by the Centre for Orbit Determination in Europe. The proposed normalization procedure combining topside observations from different LEO missions has the potential to improve the accuracies of satellite DCBs of Global Navigation Satellite Systems as well as the receiver DCBs onboard LEO satellites, although the number of LEO missions and spatial–temporal coverage of topside observations are limited.

High-resolution and high-accuracy  global ionosphere maps estimated by GNSS and LEO constellations: simulative and real data experimental results

2021 ◽  
Author(s):  
Xiaodong Ren ◽  
Jun Chen ◽  
Xiaohong Zhang
Keyword(s):  
Real Data ◽  
Global Navigation Satellite Systems ◽  
Electron Content ◽  
Ionospheric Model ◽  
Total Electron ◽  
Ionospheric Modeling ◽  
Oceanic Region ◽  
Leo Satellites ◽  
Gnss Data ◽  
Leo Satellite

&lt;p&gt;Global ionospheric total electron content (TEC) map has been employed in many high-precision areas. However, its spatial and temporal resolution is not ideal since the ground-based Global Navigation Satellite Systems (GNSS) stations distributed unevenly. Fortunately, many low earth orbit (LEO) satellite constellations will provide a large number of observations that can be used for ionospheric monitoring in the future. In this contribution, we presented two methods, which are the single-layer normalization (SLN) method and the dual-layer superposition (DLS) method, for ionospheric modeling based on the simulative and real data of GNSS+LEO satellites.&lt;/p&gt;&lt;p&gt;For simulative data, a constellation with 192 LEO satellites is simulated. And then,&amp;#160; the global ionospheric maps (GIMs) are estimated by all Multi-GNSS and simulative LEO satellite observations. The results showed that the root mean square (RMS) is reduced by approximately 25% and 21% for SLN method and DLS method, respectively. For real data,&amp;#160; 20 available scientific LEO satellites, such as Jason-2/3, COSMIC-1/-2, Swarm missions, etc.,&amp;#160; are employed in the ground-based GNSS ionospheric modeling. The results showed that the differences between the ionospheric model estimated by GNSS+LEO and that by GNSS data are mainly over the oceanic region, which may exceed &amp;#177;20 TECU. The improvement of RMS over the oceanic region is about 15% for the ionospheric model estimated by GNSS+LEO. The RMS of the ionospheric model improved approximately 4.0% compared with that by GNSS data using the dSTEC assessment method.&lt;/p&gt;

scholarly journals Ionospheric Response along Meridian for the Certain Storm Using TEC and foF2

Universe ◽  
2021 ◽  
Vol 7 (9) ◽  
pp. 342
Author(s):  
Olga Maltseva ◽  
Artem Kharakhashyan ◽  
Tatyana Nikitenko
Keyword(s):  
Space Weather ◽  
Real Data ◽  
Slab Thickness ◽  
Electron Content ◽  
Global Models ◽  
Total Electron ◽  
Long Time ◽  
Critical Frequency Fof2 ◽  
Using Data ◽  
Two Parameters

For a long time, the equivalent ionospheric slab thickness τ has remained in the shadow of ionospheric main parameters: the maximum density, NmF2 (or the critical frequency, foF2), and the total electron content. Empirical global models have been developed for these two parameters. Recently, several global models of τ have appeared concurrently. This paper compares τ of the Neustrelitz equivalent slab thickness model (NSTM), with τ(IRI-Plas) of the IRI-Plas model, and τ(Appr) of the approximation model, constructed along the 30° E meridian using data from several ionosondes. The choice of the model of the best conformity with observational data was made, which was used to study the effects of space weather during several magnetic storms in March 2012. The effects included: (1) a transition from negative disturbances at high latitudes to positive ones at low latitudes, (2) the super-fountain effect, which had been revealed and explained in previous papers, (3) a deepening of the main ionospheric trough. The efficiency of using τ(Appr) and τ(IRI-Plas) models for studying the effects of space weather has been confirmed. The advantage of the τ(Appr) model is its closeness to real data. The advantage of the τ(IRI-Plas) model is the ability to determine foF2 without ionosondes. The efficiency of the NSTM model is insufficient for a role of a global τ model due to the accuracy decreasing with the increasing latitude.

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