The 2015 St. Patrick’s day storm was the first storm of solar cycle 24 to reach a level of “Severe” on the NOAA geomagnetic storm scale. The Norwegian Mapping Authority is operating a national real-time kinematic (RTK) positioning network and has in recent years developed software and services and deployed instrumentation to monitor space weather disturbances. Here, we report on our observations during this event. Strong GNSS (Global Navigation Satellite System) disturbances, measured by the rate-of-TEC index (ROTI), were observed at all latitudes in Norway on March 17th and early on March 18th. Late on the 18th, strong disturbances were only observed in northern parts of Norway. We study the ionospheric disturbances in relation to the auroral electrojet currents, showing that the most intense disturbances of GNSS signals occur on the poleward side of poleward-moving current regions. This indicates a possible connection to ionospheric polar cap plasma patches and/or particle precipitation caused by magnetic reconnection in the magnetosphere tail. We also study the impact of the disturbances on the network RTK and Precise Point Positioning (PPP) techniques. The vertical position errors increase rapidly with increasing ROTI for both techniques, but PPP is more precise than RTK at all disturbance levels.

/pdf/overview-of-the-2015-st-patrick-s-day-storm-and-its-33wy5k2brw.pdf

Overview of the 2015 St. Patrick's day storm and its consequences for RTK and PPP positioning in Norway

Chinese BeiDou Navigation Satellite System is officially operational as a regional constellation with five Geostationary Earth Orbit (GEO) satellites, five Inclined Geosynchronous Satellite Orbit (IGSO) satellites and four Medium Earth Orbit (MEO) satellites. Observations from the BeiDou Experimental Tracking Stations (BETS) and the IGS Multi-GNSS Experiment (MGEX) network from 1 January to 31 March 2013 are processed for orbit determination of the BeiDou constellation. Various arc lengths and solar radiation pressure parameters are investigated. The reduced set of ECOM five-parameter model produces better performance than the full set of ECOM nine-parameter model for BeiDou IGSO and MEO. The orbit overlap for the middle days of 3-day arc solutions is better than 20 cm and 14 cm for IGSO and MEO in RMS, respectively. Satellite laser ranging residuals are better than 10 cm for both IGSO and MEO. For BeiDou GEO, the orbit overlap of several meters and satellite laser ranging residuals of several decimetres can be achieved.

/pdf/precise-orbit-determination-of-beidou-constellation-based-on-1x3f3fuo3m.pdf

Precise orbit determination of BeiDou constellation based on BETS and MGEX network

[1] The Wide Area Augmentation System (WAAS) is an augmentation of the Global Positioning System (GPS) that provides safe and reliable use of GPS signals for airline navigation over much of North America. Ever since WAAS was first commissioned in July of 2003, the vertical delay estimate at each node in the WAAS ionospheric grid has been determined from a planar fit of slant delay measurements, projected to vertical using an obliquity factor specified by the standard thin shell model of the ionosphere. In a future WAAS upgrade (WAAS Follow-On Release 3), however, the vertical delay will be estimated by an established, geo-statistical technique known as kriging. When compared to the planar fit model, the kriging model is generally found to match better the observed random structure of the vertical delay. This paper presents the kriging methodology to be used to estimate the vertical delay and its uncertainty at each ionospheric grid point. In addition, it provides examples of the improvement in delay accuracy achieved. Under disturbed conditions, the implementation of kriging reduces the magnitude of the root mean square fit residual by up to 15%.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2011RS004667

Estimating ionospheric delay using kriging: 1. Methodology

Eliminating negative VTEC in global ionosphere maps using inequality-constrained least squares

The present study examines the ionospheric Total Electron Content (TEC) variations in the lower mid-latitude Turkish region from the Turkish permanent GNSS network (TPGN) and International GNSS Services (IGS) observations during the years 2009 to 2017. The corresponding vertical TEC (VTEC) predicted by Kriging and NeQuick-2 models are evaluated to realize their efficacy over the country. We studied the diurnal, seasonal and spatial pattern of VTEC variation and tried to estimate by a new mathematical model using the long term of 9 years VTEC data. The diurnal variation of VTEC demonstrates a normal trend with its gradual enhancement from dawn to attain a peak around 09:00–14.00 UT and reaching the minimum level after 22.00 UT. The seasonal behavior of VTEC indicates a strong semi-annual variation of VTEC with maxima in September equinox followed by March equinox and minima in June solstice followed by December solstice. Also, the spatial variation in VTEC depicts a meaningful longitudinal/latitudinal pattern altering with seasons. It decreases longitudinally from the west to the east during March equinox and June solstice increases with latitude. The comparative analysis among the GNSS-VTEC, Kriging, NeQuick and the proposed mathematical model are evaluated with the help one way ANOVA test. The analysis shows that the null hypothesis of the models during storm and quiet days are accepted and suggesting that all models are statistically significantly equivalent from each other. We believe the outcomes from this study would complement towards a relatively better understanding of the lower mid-latitude VTEC variation over the Turkish region and analogous latitudes over the globe.

Mathematical modelling of ionospheric TEC from Turkish permanent GNSS Network (TPGN) observables during 2009–2017 and predictability of NeQuick and Kriging models

[1] An augmentation of the Global Positioning System, the Wide Area Augmentation System (WAAS) broadcasts, at each node of an ionospheric grid, an estimate of the vertical ionospheric delay and an integrity bound on the vertical delay error. To date, these quantities have been determined from a planar fit of slant delay measurements, projected to vertical using an obliquity factor specified by the standard thin shell model of the ionosphere. In a future WAAS upgrade (WAAS Follow-On Release 3), however, they will be calculated using an established, geo-statistical estimation technique known as kriging that generally provides higher estimate accuracy than planar fit estimation. This paper analyzes the impact of kriging on system availability. In a preliminary assessment, kriging is found to produce improvements in availability of up to 15%.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2011RS004781

Estimating ionospheric delay using kriging: 2. Impact on satellite‐based augmentation system availability

The Wide Area Augmentation System (WAAS), an augmentation of the Global Positioning System (GPS), provides safe and reliable use of GPS signals for airline navigation over much of North America. Currently the largest source of positioning error in the system is signal delay caused by the ionosphere. To allow the user to take account of such error, WAAS computes and broadcasts ionospheric vertical delays at a set of regularly-spaced grid points. In addition, WAAS computes and broadcasts a safety-critical integrity bound at each ionospheric grid point (IGP) called the Grid Ionospheric Vertical Error (GIVE). GIVEs are constructed to be sufficiently large to protect the user against positioning error due to the presence of ionospheric irregularity. In the initial operating capability (IOC) of WAAS, the vertical delay estimate at each IGP is determined from a planar fit of neighboring slant delay measurements, projected to vertical using an obliquity factor specified by the standard thin-shell model of the ionosphere. In WAAS Follow-On (WFO) Release 3, however, the vertical delay will be estimated by an established, geo-statistical technique known as kriging. Compared to the planar fit model, the kriging model is found, in general, to match better the observed random structure of the vertical delay. This paper presents the kriging methodology that will be used to estimate the vertical delay and its uncertainty at each IGP, and it assesses the subsequent improvement in WAAS availability enabled by kriging.

Kriging as a Means of Improving WAAS Availability

Geostationary earth orbit (GEO) satellites serve as relays to transmit messages for space-based augmentation systems (SBASs). GEOs can act as ranging sources for SBAS users as well, adding to the availability and continuity of a number of SBAS services. The SBAS determines the GEO orbit error from covariance analysis of satellite dynamics and station-to-satellite geometry. However, separating the orbit determination errors from the clock errors is difficult, and GEO range errors tend to be much larger than GPS range errors. This paper proposes a technique for making the clock state of a “bent-pipe” GEO a known quantity, then considers the effect on the derived GEO range through a simulation of the orbit determination extended Kalman filter. The study indicates that this technique reduces the GEO orbit error by a factor of ˜22 and implies that GEO orbit determination errors can be made comparable to those of GPS satellites.

GEO Orbit Determination via Covariance Analysis with a Known Clock Error

<h3>Abstract</h3> Satellite-based augmentation systems ensure the accuracy and integrity of aircraft position estimates derived from radio signals broadcast by the Global Navigation Satellite System. The United States’ Wide Area Augmentation System (WAAS) protects users of the Global Positioning System from threats generated by ionospheric disturbances. The means by which WAAS mitigates these threats depends upon their magnitude. This paper addresses: a) how WAAS monitors the level of ionospheric perturbation over North America; b) how various availability and integrity concerns have influenced the implementation of WAAS’s extreme and moderate ionospheric storm detectors; c) how the algorithms governing these implementations have evolved since WAAS’s commissioning in 2003; and d) how the largest ionospheric storms of the past two solar cycles can be ranked according to their impact on WAAS. A subsequent companion paper will address the evolution of the WAAS methodology for protecting users from the adverse influence of more moderate ionospheric disturbances. 

/pdf/waas-and-the-ionosphere-a-historical-perspective-monitoring-2dlbqi9u.pdf

Nitin Pandya

Papers

Estimating ionospheric delay using kriging: 1. Methodology

Estimating ionospheric delay using kriging: 2. Impact on satellite‐based augmentation system availability

Kriging as a Means of Improving WAAS Availability

GEO Orbit Determination via Covariance Analysis with a Known Clock Error

WAAS and the Ionosphere – A Historical Perspective: Monitoring Storms