Based on the mean arrival time and temporal broadening of pulsed waves propagating through turbulent media, this study investigates the ionospheric effects induced by irregularity on medium-earth-orbit synthetic aperture radar (MEOSAR) range imaging quality. Considering radar signal two-way propagating through ionosphere irregularity, an analysis model for ionospheric effects induced by irregularities on MEOSAR range imaging quality is established based on the system characteristics of MEOSAR and ionospheric irregularity parameters. The mode extends the application of pulsed waves propagating through turbulent media to the field of synthetic aperture radar (SAR), and it can be used to analyse the effects on MEOSAR induced by both background ionosphere and ionospheric irregularity. The degradation of range image quality, including deterioration of resolution and shift in the image, due to the ionospheric irregularities is analysed. It is found that the effects induced by ionospheric irregularities will be very serious when the inner and outer scales of ionospheric irregularities are small or the fluctuation is strong. Furthermore, the degradation of resolution and the shift of image will become more and more serious with the increase of SAR orbit height. The results can help to evaluate ionospheric irregularity effects on range imaging for MEOSAR and provide a foundation for the design of MEOSAR.

Nowadays, using the Internet of Things (IoT), several real-time forecasting systems have been developed. The primary challenge of this system is to utilise an appropriate prediction model that can predict various space weather parameters as accurately as possible. In this study, an ionospheric IoT analytical system with variational mode decomposition (VMD) based on kernel extreme learning machine (KELM) is proposed. The ionospheric signal delay/total electron content (TEC) data from Continuous Reference Stations (CORS) Port Blair (2.03°N, 165.25°E, geomagnetic), Bengaluru (4.40°N, 150.77°E, geomagnetic), Koneru Lakshmaiah Education Foundation (KLEF) – Guntur (7.50°N, 153.76°E; geomagnetic) and Lucknow (17.98°N, 155.22°E; geomagnetic) are used for the analysis during the period of 2015. The ionospheric signal delays of four CORS are computed from ThingSpeak (IoT) with the channel ID and the Application Programming Interface key. ThingSpeak data is given to the ionospheric forecasting model (VMD-KELM). The results predicted from the proposed model are able to achieve the faster training process and obtain a similar accuracy to that of the VMD-artificial neural network. The proposed VMD-KELM application is adopted when a cloud-based forecasting system requires fast learning speed and good accuracy. As a result, the cloud paradigm offers the possibility without web development skills or highly specific statistics.

Radars operating in the high-frequency (HF) band can exploit propagation modes other than line-of-sight and are hence widely employed to provide over-the-horizon surveillance and remote sensing. Most HF radars operating today rely on surface wave propagation; while opportunities for enhancing their performance by adding cognitive features exist, these have not been widely seized. In contrast, designers of HF skywave radars, which exploit ionospheric reflection to achieve ranges in excess of 4000 km, have long sought to counter the enormous challenges of the geophysical environment by implementing schemes to raise radar intelligence quotient (IQ) and autonomy. Measures that have been explored relate to resource allocation, operating procedures, signal processing, target classification and remote sensing. The perception–action cycle constitutes the structural element of these developments, accessing prior knowledge and input from auxiliary sensors, exactly as proposed by those who later coined the term cognitive radar. Here, the roles of cognition in HF skywave radars are reviewed, illustrating the needs and benefits with examples including detection in sea clutter, ionospheric channel compensation and multiple-input and multiple-output HF radar.

Solar eclipse provides a unique opportunity to investigate the ionospheric response to the change in the solar flux emission towards the Earth. The variability of the ionospheric total electron content (TEC) in response to the total solar eclipse of August 21, 2017 has been studied by the analysis of dual frequency Global Positioning System (GPS) data from the University NAVSTAR Consortium (UNAVCO) established at North Carolina, USA (P779), and from the Rede Brasileira de Monitoramento Contínuo (RBMC) Amapá (APS1) station. The path of the solar obscuration passed through the North American region, also affecting the northern part of Brazil. The magnitudes of the ionospheric TEC from both monitoring stations during the eclipse are compared with those from the days immediately preceding and following it. This comparison will highlight the effects from the eclipse on the ionospheric electron density variations observed by the stations that are located over its path.

The paper presents the findings of the research into the effects of frequency dispersion in transionospheric radio channels. We discussed the general framework of the theory of frequency dispersion of the phase taper. The equations for the coherence band of the wideband channels and the critical value of the total electronic content (TEC) were obtained. The experimental results of daily variations and critical TEC values for the mid-latitude ionosphere are presented.

The prediction and forecasting of ionospheric delay at equatorial and low-latitude regions is an essential contribution for improving the global positioning system services. In this study, hybrid auto-regressive integrated moving average (ARIMA) models are implemented based on wavelet transform (WT) and empirical mode decomposition (EMD) for 1 h ahead forecast of ionospheric total electron content (TEC). The performance of ARIMA and hybrid models, WT and EMD in combination with ARIMA (WARIMA and EARIMA) is evaluated during various seasons and March geomagnetic storm conditions in 2013 and 2015. The proposed models are validated with empirical global TEC models and results show that the EARIMA has less error measurements compared with ARIMA and WARIMA models. The EARIMA ionospheric forecasting model can be useful for developing an early warning ionospheric space weather system over low latitudes.

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 (σØ), 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).

Precipitable water vapour (PWV) is an important input for numerical weather prediction model, meteorology and high-precision navigational applications. Conventional methods for the determination of PWV using radiosonde are not sufficient owing to poor temporal resolution, whereas radiometer-derived PWV is reliable only in fair weather conditions. Global positioning system (GPS) is a very useful and cost-effective tool to determine PWV continuously in all weather conditions. The processing of GPS data to extract the PWV information is, however, very complicated due to very small effect of the PWV (∼0.5% of total delay) on GPS frequencies than other sources of delay and errors and requires a network of GPS in differential configuration for such purpose. The authors show how the problem can be handled in a standalone dual-frequency GPS receiver in a relatively less complicated manner with reasonable accuracy. The performances of different dry tropospheric delay models are also investigated. The methodology is tested with GPS measurements at Kolkata (22.57°N, 88.37°E) and Bangalore (13.01°N, 77.5°E). The results indicate that the proposed methodology can be implemented for PWV estimation using single GPS receiver with satisfactory performance.

Ionospheric physics has many different aspects and this chapter is aligned to provide a foundation of knowledge for the radio systems user. The aim has been to give the reader an impression of the interacting atmospheric and space science that is needed to gain a full understanding of the composition and forces making up this complicated region of our environment. It is also important to gain an understanding of the measurement techniques. With these aspects in mind, it becomes clear that obtaining enough information to undertake reliable ionospheric now-casting and forecasting for radio system planning is a significant task that will continue to challenge us into the future.

This paper presents a comparison of Chilton ionosonde critical frequency measurements against vertical-incidence HF propagation predictions using ASAPS (Advanced Stand Alone Prediction System) and VOACAP (Voice of America Coverage Analysis Program). This analysis covers the time period from 1996 to 2010 (thereby covering solar cycle 23) and was carried out in the context of UK-centric near-vertical incidence skywave (NVIS) frequency predictions. Measured and predicted monthly median frequencies are compared, as are the upper and lower decile frequencies (10% and 90% respectively). The ASAPS basic MUF predictions generally agree with fxI (in lieu of fxF2) measurements, whereas those for VOACAP appear to be conservative for the Chilton ionosonde, particularly around solar maximum. Below ~4 MHz during winter nights around solar minimum, both ASAPS and VOACAP MUF predictions tend towards foF2, which is contrary to their underlying theory and requires further investigation. While VOACAP has greater errors at solar maximum, those for ASAPS increase at low or negative T-index values. Finally, VOACAP errors might be large when T-SSN exceeds ~15. (6 pages)