Coincidentally, as I sat down in late October 2003 to read and review the second edition of Wallace H. Campbell's text, Introduction to Geomagnetic Fields, we received warnings from the news media of a massive solar flare and its possible effect on power supply systems and satellite communications. News programs briefly explained the source of Sun-Earth interactions. If you are interested in learning more about the physics of the connection between Sun spots and power supply systems and their impact on orbiting satellites, I urge you to become acquainted with Campbell's book. It presents an interesting and informative explanation of the geomagnetic field and its applications to a wide variety of topics, including oil exploration, climate change, and fraudulent claims of the utility of magnetic fields for alleviating human pain.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2003EO520008

Introduction to Geomagnetic Fields

This paper presents a machine learning algorithm to detect ionospheric scintillation and classify scintillation events based on training data in the frequency domain. The detector input is the signal intensity. Validation using data from Ascension Island, Hong Kong, and Peru shows 91–96% accuracy of scintillation detection. Different combinations of training data, observation matrices, and learning algorithms are investigated to obtain performance measures. Testing results on data from Singapore demonstrate the general capabilities of the detector.

Automatic Equatorial GPS Amplitude Scintillation Detection Using a Machine Learning Algorithm

[1] Occurrence characteristic of plasma bubble was studied using ground-based GPS receiver networks. The occurrence rate of plasma bubble derived from the global GPS network has higher spatial and temporal resolution than that derived from the other observational techniques because of its wide coverage of the observation. The physical characteristics of plasma bubble occurrence were studied in detail with this novel data set. Twenty-three GPS receivers around the dip equator were used to reveal the occurrence from 2000 to 2006. Characteristics of the monthly occurrence rates were different among the regions. Although it was found that sunset time lag effect plays an important role for the monthly variation, two asymmetries which could not be explained with the sunset time lag scenario were found: (1) asymmetry between two solstices and (2) asymmetry between two equinoxes. The seasonal variation of the F-region conductivity integrated along the geomagnetic field line could partially explain the solstice asymmetry. Semiannual occurrence rates from 2000 to 2006 were used to study the year-to-year variation from the high solar activity period to the low solar activity period. The dependency of the occurrence on the solar activity was different among the regions. Occurrence rates against the latitude/altitude were investigated in the Asian region in 2004. It was found that the occurrence was high and constant for a station whose height on the dip equator (HODE) was less than 700 km. They began to decrease when HODE was higher than 700 km and was almost zero where it was higher than 900 km.

Occurrence characteristics of plasma bubble derived from global ground-based GPS receiver networks

Ionospheric phase scintillation can cause errors or outage in GNSS navigation solutions. Timely detection of phase scintillation will enable adaptive processing to mitigate its effects on navigation solutions. This paper presents a machine-learning algorithm to autonomously detect phase scintillation based on frequency domain features. Validation using data from Gakona shows phase scintillation detection accuracy around 92 percent. Test results using data from Poker Flat, Jicamarca, Singapore, and Hong Kong demonstrate the capability of the trained detector to be applied more generally. Performance evaluation reveals that the values of phase scintillation index s? may be poor indications of scintillation activities. Concurrent phase and amplitude scintillation detection using similar machine-learning algorithms is further investigated with low-latitude data. Results suggest that at low latitudes an amplitude detector alone is sufficient to capture scintillation in general, while at high latitudes, a phase scintillation detector is necessary to capture the dominating phase scintillation events.

Performance Evaluation of an Automatic GPS Ionospheric Phase Scintillation Detector Using a Machine-Learning Algorithm

Scintillation due to ionospheric plasma irregularities remains a challenging task for the space science community as it can severely threaten the dynamic systems relying on space-based navigation services. In the present paper, we probe the ionospheric current and plasma irregularity characteristics from a latitudinal arrangement of magnetometers and Global Navigation Satellite System (GNSS) stations from the equator to the far low latitude location over the Indian longitudes, during the severe space weather events of 6–10 September 2017 that are associated with the strongest and consecutive solar flares in the 24th solar cycle. The night-time influence of partial ring current signatures in ASYH and the daytime influence of the disturbances in the ionospheric E region electric currents (Diono) are highlighted during the event. The total electron content (TEC) from the latitudinal GNSS observables indicate a perturbed equatorial ionization anomaly (EIA) condition on 7 September, due to a sequence of M-class solar flares and associated prompt penetration electric fields (PPEFs), whereas the suppressed EIA on 8 September with an inverted equatorial electrojet (EEJ) suggests the driving disturbance dynamo electric current (Ddyn) corresponding to disturbance dynamo electric fields (DDEFs) penetration in the E region and additional contributions from the plausible storm-time compositional changes (O/N2) in the F-region. The concurrent analysis of the Diono and EEJ strengths help in identifying the pre-reversal effect (PRE) condition to seed the development of equatorial plasma bubbles (EPBs) during the local evening sector on the storm day. The severity of ionospheric irregularities at different latitudes is revealed from the occurrence rate of the rate of change of TEC index (ROTI) variations. Further, the investigations of the hourly maximum absolute error (MAE) and root mean square error (RMSE) of ROTI from the reference quiet days’ levels and the timestamps of ROTI peak magnitudes substantiate the severity, latitudinal time lag in the peak of irregularity, and poleward expansion of EPBs and associated scintillations. The key findings from this study strengthen the understanding of evolution and the drifting characteristics of plasma irregularities over the Indian low latitudes.

/pdf/signatures-of-equatorial-plasma-bubbles-and-ionospheric-1dz95p7z.pdf

Signatures of Equatorial Plasma Bubbles and Ionospheric Scintillations from Magnetometer and GNSS Observations in the Indian Longitudes during the Space Weather Events of Early September 2017

Severe ionosphere scintillations have been known to affect the performance and measurement accuracy of Global Navigation Satellite System (GNSS) receivers. The scintillation in signal amplitude and phase reduces the number of available GNSS satellites by causing the loss of lock in GNSS receivers. Hence, the investigation of ionospheric scintillations is imperative for monitoring the activities of the atmosphere, ionosphere and space weather. Scintillations can be modelled as a function of scintillation indices like amplitude scintillation index (S4), phase scintillation index (σO), C/N and elevation angle with respect to the time. In this study, the GNSS Ionospheric Scintillation and TEC monitor receiver located at the K L University, Vaddeswaram, India, sited in low latitudes, provided the data for the real-time analysis of ionospheric scintillations. This paper describes an ionospheric scintillation model (RTISM), which determines the automatic threshold for different scintillation signals using the Neyman Pearson detector. The results of the RTISM model include estimation, detection and mitigation of ionospheric scintillations using wavelet analysis, Hilbert–Huang transform and binary hypothesis test. The RTISM model has been tested for major scintillation events observed during the geomagnetic storms that occurred in the maximum solar activity periods of the 24th solar cycle (2013–2014).

Automatic ionospheric scintillation detector for global navigation satellite system receivers

In this study, an attempt is made to develop regional ionospheric total electron content (TEC), rate of TEC index (ROTI) and amplitude scintillation index (S 4) maps using data from 26 dual-frequency global positioning system (GPS) receivers under GPS aided geo-stationary earth orbit augmented navigation programme over Indian region. One-minute spatial TEC maps are generated for the entire Indian region covering 65–100°E geographic longitudes, 5–40°N geographic latitudes with 2° × 2° grid separation using Kriging method. Also, the ROTI and amplitude scintillation index (S 4) maps for every 5 min are generated. The performance of the generated regional TEC maps is evaluated during a severe geomagnetic storm condition. Patterns of equatorial ionisation anomaly (EIA) TEC structures are investigated for St. Patrick's storm between the days 15 and 20 March 2015 with the generated TEC maps. The proposed TEC maps depict the northern crest of EIA features in latitudinal extent and TEC strength. The kriging method detects the suppressed and downshift of EIA features on 18 March 2015. The movement of plasma bubbles are analysed over Indian latitudes during the transition period of a geomagnetic storm on 17 March 2015.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-rsn.2020.0202

Kriging-based ionospheric TEC, ROTI and amplitude scintillation index (S 4) maps for India

The ionosphere is perceived to be a predominant source of ranging error of Global Navigation Satellite System (GNSS) signals to degrade the positional accuracy. The suitable ionospheric model is necessary to improve the positional accuracy of GNSS and Satellite-Based Augmentation System (SBAS) users. In this paper, the regional ionospheric model (RIM) over the Indian region is implemented based on the adjusted spherical harmonics function (ASHF) model from dense GPS TEC stations over the Indian region. Also, the evaluation of the different ASHF order models conducted to identify the proper order of the ASHF model for Indian low latitude ionospheric calm and adverse space weather conditions. The results confirm that the 4th order ASHF ionospheric model can identify the northern Equatorial Ionization Anomaly (EIA) TEC crest patterns over the Indian region. The comparison of the 4th order ASHF ionospheric model carried out with dual and single frequency ionospheric models like as Klobuchar model, Centre for Orbit Determination in Europe (CODE) Klobuchar model, NeQuick G model, BeiDou System (BDS2) model and CODE Global Ionospheric Maps (GIM) models. The outcome of the results indicates that the 4th Order ASHF ionospheric model would be potential for single and dual-frequency ionospheric models for GNSS and SBAS systems.

/pdf/performance-evaluation-of-adjusted-spherical-harmonics-2uqa2f4xab.pdf

Performance Evaluation of Adjusted Spherical Harmonics Ionospheric Model Over Indian Region

Global Satellite Navigation Systems (GNSS) aid aircraft navigation in every phase of flight. Ground-Based Augmentation System (GBAS) augments the performance of GNSS for civil aviation by providing differential corrections to the position of an aircraft during takeoff and landing. GBAS provides continuous and integral positioning service in all weather operations even in zero visibility conditions. Ionospheric gradients affect the accuracy with which GNSS can locate the position of an aircraft. The gradients in the ionosphere can be measured and characterized using data from Global Positioning System (GPS) receivers surrounding the airport. In this paper the ionospheric temporal and spatial gradients have been detected and the ionospheric drift velocity has been measured using the data recorded by the GPS receivers located at Koneru Lakshmaiah University, Guntur (GNT) and Indian Meteorological Department, Machilipatnam (MPM), Andhra Pradesh, India. Rate of TEC Index (ROTI) and numerical differentiation was used to find the ionospheric drift velocity. In the low-latitude regions, the disturbances in the ionosphere are a daily occurrence due to the formation of plasma bubbles which usually occur in the post sunset hours. The ionospheric spatial and temporal gradient results at GNT and MPM stations for the month of January, 2015 have been discussed. The spatial and temporal gradients were found to have occurred between 20 and 22 hours, local time. The maximum value of ionospheric gradient velocity was 473.25 m/s. The S4 value was above 0.8 and the phase scintillation value was above 0.7 radians. The spatial gradient reached a maximum value of 163.7 mm/100km during the same time.

http://nopr.niscair.res.in/bitstream/123456789/34250/1/IJRSP%2045%281%29%2011-19.pdf

Detection of ionospheric spatial and temporal gradients for ground based augmentation system applications

In this paper with the help of smartphones technology we had performed the magnetic field measurements by using the sensor data collector app. By studying about the sensors of honor and vivo phones, the sensors have the 1400nT nominal sensitivity. from the sensors also we can detect the glitches which having the amplitude of measurement of ±1500 nT. due to this magnetics terms there will be a effect on satellites and satellite communication and also the human life. In this study we had improved about sensors magnetic fields for future improvements.

/pdf/viability-of-identifying-the-disturbance-of-geomagnetic-2x9dgpd7tx.pdf

Devanaboyina Venkata Ratnam

Papers

Automatic ionospheric scintillation detector for global navigation satellite system receivers

Kriging-based ionospheric TEC, ROTI and amplitude scintillation index (S 4) maps for India

Performance Evaluation of Adjusted Spherical Harmonics Ionospheric Model Over Indian Region

Detection of ionospheric spatial and temporal gradients for ground based augmentation system applications

Viability Of Identifying The Disturbance Of Geomagnetic Field With Smart Phone Technology