Three-axis active control system for gravity gradient stabilised microsatellite

In this paper, the control system of the first Algerian microsatellite in orbit Alsat-1 is presented. Alsat-1 is a 3-axis stabilised microsatellite, using a pitch momentum wheel and yaw reaction wheel, with dual redundant 3-axis magnetorquers. A gravity gradient boom is employed to provide a high degree of platform stability. Two vector magnetometers and four dual sun sensors are carried in order to determine the attitude. This paper examines the low Earth orbit (LEO) control system requirements and design in the context of a real system, the Surrey Satellite Technology Limited (SSTL) advanced microsatellite platform and puts forward designs for the control system to match the advanced capability of the enhanced microsatellite platform. Numerical results show the effectiveness of the implementation. Comparison with in orbit results is presented to evaluate the performance of the control system during accurate Nadir pointing control.     

Capacity building in emerging space nations: Experiences,challenges and benefits

This paper focuses on ways in which space is being used to build capacity in science and technology in order to:     

The Emirates Mars Mission (EMM) Emirates Mars InfraRed Spectrometer (EMIRS) Instrument

Space Science Reviews - Modern observatories have revealed the ubiquitous presence of magnetohydrodynamic waves in the solar corona. The propagating waves (in contrast to the standing waves) are...     

Influence of Interference Effects of the Rotor on the Launch Dynamics of Gliding Unmanned Aerial Vehicle

A mathematical model of the gliding unmanned aerial vehicle (UAV) motion is performed taking into account the interference effect of the main rotor on the UAV. Calculated values are presented for the interference addition to the aerodynamic coefficients of forces and moments on the UAV path section close to the carrier. The problems of stabilization and control are solved, providing stability of the UAV motion at the launch with due account of the aerodynamic interference and the effect of short-term upper stage engine operation, as well as a safe distance between the carrier and the UAV during their simultaneous motion.     

Global Muon Detector Network Used for Space Weather Applications

In this work, we summarize the development and current status of the Global Muon Detector Network (GMDN). The GMDN started in 1992 with only two muon detectors. It has consisted of four detectors since the Kuwait-city muon hodoscope detector was installed in March 2006. The present network has a total of 60 directional channels with an improved coverage of the sunward Interplanetary Magnetic Field (IMF) orientation, making it possible to continuously monitor cosmic ray precursors of geomagnetic storms. The data analysis methods developed also permit precise calculation of the three dimensional cosmic ray anisotropy on an hourly basis free from the atmospheric temperature effect and analysis of the cosmic ray precursors free from the diurnal anisotropy of the cosmic ray intensity.     

The KACST muon detector and its application to cosmic-ray variations studies

A single channel cosmic ray muon detector was constructed and installed in Riyadh, central Saudi Arabia, for studying the variations in the cosmic ray (CR) muon flux. The detector has been in operation since July 2002. The recorded data correspond to muons that primarily have energies between 10 and 20 GeV. The detector will be used to continuously measure the intensity of the muon components of the cosmic rays, exploring its variations and possible correlations with environment parameters. The technical aspects of this detector will be presented. Some results obtained by the detector so far will be given. These include the modulation of the CR flux on different time scales (diurnal, 27-day, and long-term variations). Additionally, the effect of a severe dust storm on the muon count rate was investigated.     

Hierarchical Bayesian modeling of ionospheric TEC disturbances as non-stationary processes

We model regular and irregular variation of ionospheric total electron content as stationary and non-stationary processes, respectively. We apply the method developed to SCINDA GPS data set observed at Bahir Dar, Ethiopia $\left(11.6°\text{N,}37.4°\text{E}\right)$. We use hierarchical Bayesian inversion with Gaussian Markov random process priors, and we model the prior parameters in the hyperprior. We use Matérn priors via stochastic partial differential equations, and use scaled $\text{Inv}-{\chi }^2$ hyperpriors for the hyperparameters. For drawing posterior estimates, we use Markov Chain Monte Carlo methods: Gibbs sampling and Metropolis-within-Gibbs for parameter and hyperparameter estimations, respectively. This allows us to quantify model parameter estimation uncertainties as well. We demonstrate the applicability of the method proposed using a synthetic test case. Finally, we apply the method to real GPS data set, which we decompose to regular and irregular variation components. The result shows that the approach can be used as an accurate ionospheric disturbance characterization technique that quantifies the total electron content variability with corresponding error uncertainties.