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The regional coverage satellite constellations are in demand for fulfilling earth observation needs of specific user regions of interest as opposed to global coverage thus enhancing the revisit period for the area. In this paper, we present a few key mission aspects of the regional coverage constellation designed and operated by the Indian Space Research Organization (ISRO) in low earth orbit. ISRO developed three X-Band Synthetic Aperture Radar (SAR) Earth Observation satellites and placed them in three inclined orbit planes to enhance the Indian region's coverage. This is India's first inclined orbit constellation designed for remote sensing applications in low earth orbit. The satellites were built around a standard bus carrying a Synthetic Aperture Radar payload with a deployable Radial Rib Antenna (RRA). They were designed to achieve a high agility capability. As SAR sensors are capable of all-weather, day, and night imaging; thus, most suitable in inclined orbits where the illumination conditions vary continuously for imaging. Though the inclined orbits provide more revisit opportunities to the region of interest, their characteristics pose challenges in mission design and operations. Though the mission design and planning involved a host of elements, this paper brings out the details of a few key mission analysis elements, planning aspects and operations that were critical in the course of various mission phases. The mission analysis included mission-specific requirements like launch windows selection for the constellation and reference attitude generation specific to inclined orbit geometry. Mission planning had to take care of Radial Rib Antenna (RRA) deployment requirements which were very critical for the mission, apart from taking care of individual subsystem requirements. The SAR payload data product quality and targeting accuracy are very sensitive to the satellite image point range (vis-a-vis SAR operation data window). Extensive post-launch calibration activity was carried out to meet all these mission requirements and data product specifications. The challenge was in fixing the payload beam alignment and fixing the uncertainties in onboard and ground computations. The paper also describes the methods of fixing all possible error sources affecting the high-resolution SAR payload performance. • The regional coverage satellite constellations are in demand for area targets coverage. • Inclined orbit constellations are more suitable for regional coverage using SAR sensors. • Mission operations plans need to consider all the specific requirements of spacecraft systems. • Pre-launch and post -launch calibrations of sensors is mandatory for achieving system performance. [ABSTRACT FROM AUTHOR]

Secondary and High School students are usually adolescents, most of them in the urban areas and metropolitan cities are aware about the existence, various opportunities, career paths and advancements of the space industry. They are constantly updated, given they have access to quality and organized education models and a competitive environment. Although, the students in the rural areas who are equally ambitious and talented yet are not fortunate enough to have access to the state of art facilities like the counterparts. Even if they try and gain access with their self-interest, they do not have the motivation to sustain the passion, given their lack of clarity in subject, lack of awareness about engaging in various ways and fields in space other than technological related and mainly lack of driving force. The purpose of this paper is to develop and present an education model, exclusively for the high school students of the rural areas and inculcate sustainable passion for space. As opposed to the primary school students, the secondary school students have a consciousness of the space industry. This paper will talk about various plans and strategies, that will allow them to gain exposure, guide them about the existence of different career paths which are not entirely technological related, yet are still essential in the space like, administrative framework for example. This opens a new dimension in their brain helping them realize how they can be part of the industry in countless ways, and this shall assist them in being on the right track to space. In addition to, hosting creative space themed exhibitions, fun and engaging model design competitions, workshops, all of these would widen their knowledge boundaries and help them challenge their skills. A real time case study example from a school located in the rural southern of India shall be focused on this paper. Including data from a survey thereby the results, with action plans shall be presented in detail, which will aid in the analysis of the need, feasibility, and long-term sustenance of this approach and the requirement to scale it over different rural areas globally. • Need for improvised education models in rural areas elucidated, with data collection. • Data analysis and correlation of space education awareness, for high school students across two geographical locations. • Readily executable action plans age groupwise, for real-time education models in remote areas globally. [ABSTRACT FROM AUTHOR]

The range error caused by ionospheric delay in Global Positioning System (GPS) signals is currently the main factor that affected the positioning accuracy and navigation determination. Ionospheric modeling and optimization of its range error is a practical approach to improve the GPS positioning accuracy. The global ionospheric models are mostly unable to predict ionospheric delay corrections over the India region due to the Equatorial Ionization Anomaly (EIA)/fountain effect and lack of equatorial/low latitude GPS stations data. This paper proposes a method to facilitates regional ionospheric delay corrections based on the Adjusted Spherical Harmonic Function (ASHF) model by considering fewer coefficients into the algorithm. The ionospheric correction is driven with low-resolution harmonics coefficients with order ≤2 (≤9 coefficients), and coefficients are estimated with the Modified Gram-Schmidt (MGS) approach. The performance of the proposed model (ASHF) is compared with the Spherical Harmonic Function and Klobuchar models. Preliminary results reveal that the low-resolution ASHF model improved the ionospheric time delay corrections by 12.98% relative to the Klobuchar model. The results could be useful in the context of ionospheric time delay modeling for regional navigation satellite systems. • Estimation of ionospheric delays is proposed based on Orthogonal Dimensionality Reduction. • Model outcomes are assessed by comparing with the Weighted Least Square estimations. • The SVD-SHF method improves the accuracy of the model results in geomagnetic storm conditions. • The SVD-SHF method resulted in dimensional reduction and low computational load. • The outcomes suggest that the model implementation is used for GNSS and surveying applications. [ABSTRACT FROM AUTHOR]

Ionospheric modeling across the Indian low latitudes continues to be a challenging task because of the day-to-day variability pertaining to the underlying complex equatorial and low latitude electrodynamics. In this paper, we aimed at developing an ionospheric Total Electron Content (TEC) model based on Singular Spectrum Analysis (SSA) using the Global Positioning System (GPS)-TEC observations (from 2009 to 2019) at Bengaluru (Geographic: 13.02° N, 77.57° E; Dip Angle: 13.77° N), a low latitude station in India. SSA has the most significant advantage of extracting information from the noisy time-series data with the first-four SSA modes in the decomposition, almost converging to total variance of about 99%. The proposed SSA-TEC model has been assessed by comparing it with the GPS-TEC observations as well as the outcomes from the latest version of the International Reference Ionosphere model (IRI-2016) and International GNSS Services Global Ionosphere Maps (IGS-GIM). The results demonstrate excellent outcomes with the Root Mean Square Error (RMSE) values between observed and model estimations laying at 1.58 TECU (SSA), 7.04 TECU (IRI-2016), and 8.89 TECU (GIM) with the respective correlation coefficients 0.99, 0.91, and 0.94. The model outcomes are in good agreement with the GPS-TEC observations, presenting relatively better estimates of TEC than the IRI-2016 and GIM during the geomagnetically quiet and disturbed daytime and nighttime conditions under different seasons and solar activity. Moreover, the proposed SSA-TEC model replicates the significant changes and time distribution characteristics of the ionosphere over the low latitude location, foreseeing the scopes for its regional implementation with a wide range of operations. • Ionospheric TEC model is proposed based on Singular Spectrum Analysis (SSA). • Model outcomes is assessed by comparing with the GPS-TEC, IRI and GIM estimations. • Excellent model outcomes are achieved with low RMSE and high correlations. • A decent agreement with GPS-TEC is seen even during geomagnetic storm conditions. • The outcomes suggest a regional model implementation for near-realtime operations. [ABSTRACT FROM AUTHOR]

This paper explores from the view of the data recipient and user the complexities of creating a common licensing scheme for the access and use of satellite earth observation (EO) data in international disaster management (DM) activities. EO data contributions in major disaster events often involve numerous data providers with separate licensing mechanisms for controlling the access, uses, and distribution of data by the end users. A lack of standardization among the terminology, wording, and conditions within these licenses creates a complex legal environment for users, and often prevents them from using, sharing and combining datasets in an effective and timely manner. It also creates uncertainty among data providers as to the types of licensing controls that should be applied in disaster scenarios. This paper builds from an ongoing comparative analysis of the common and conflicting conditions among data licenses that must be addressed in order to facilitate easier access and use of EO data within the DM sector and offers recommendations towards the alignment of the structural and technical aspects of licenses among data providers. [ABSTRACT FROM AUTHOR]

Global Navigation satellite systems (GNSS) are predominantly affected by Ionospheric space weather. The GNSS signal delays due to ionospheric Total Electron Content (TEC) can be forecasted using advances in the emerging mathematics tools and algorithms. Machine learning algorithms such as Gaussian Process Regression (GPR) is considered in the present paper to implement in the forecasting of low-latitude ionospheric conditions. The GPS receiver data is obtained for 8 years (2009–2016) during 24th solar cycle from International GNSS Services (IGS) station located in Bengaluru (Geographical latitude: 12.97° N, Geographical longitude: 77.59° E), India. The performance of GPR model is validated using statistical parameters such as Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Mean Square Error (MSE), Root Mean Square Error (RMSE), and correlation coefficient. The results of the proposed GPR model were compared with the Auto Regressive Moving Average (ARMA) model and Artificial Neural Networks (ANN) model during solar maximum period and descending phase of 24th solar cycle. The experiment results are evident that GPR model is significantly providing the promising results in forecasting the ionospheric time delays for GNSS signals. The outcome of the work can be useful to develop web based Ionospheric TEC forecasting system to alert the GNSS users. • The GPS-TEC variability is investigated during solar maximum period and descending phase of 24th solar cycle. • The performance of ARMA, ANN and GPR models are evaluated in forecasting the ionospheric delays for GPS signals. • GPR model has better predicted TEC than the existing ARMA and ANN models during geomagnetic quiet and storm periods. • Kernel-based approach of GPR model is well suitable to forecast the ionospheric TEC variations over low latitudes. [ABSTRACT FROM AUTHOR]