Miniaturized Micro Ion Thruster: Integration and Performance Analysis for CubeSat Application
Observations of Fireballs with the UAE Meteor Monitoring Network
Advances in Science, Technology & Innovation/Advances in science, technology & innovation, 2024
Analyzing Meteorites at the Sharjah Academy for Astronomy, Space Sciences, and Technology
Advances in Science, Technology & Innovation/Advances in science, technology & innovation, 2024
Sharjah-Sat-3: A Low-Cost 6U CubeSat for Space Weather Applications
Morphological Classification of Extragalactic Radio Sources Using Gradient Boosting Methods
2023 International Joint Conference on Neural Networks (IJCNN)
Sharjah-Sat-2: a low-cost high-resolution earth observation microsatellite
Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXIX
Monitoring and validation of GNSS signal's integrity using Sharjah-Sat-2 microsatellite
Sensors and Systems for Space Applications XVI
Utilization of Sharjah-Sat-1 improved x-ray detector for space situational awareness
Sensors and Systems for Space Applications XVI
Meteor detection and localization using YOLOv3 and YOLOv4
Neural Computing and Applications
Meteors in the United Arab Emirates are observed daily through the U.A.E. Meteor Monitoring Netwo... more Meteors in the United Arab Emirates are observed daily through the U.A.E. Meteor Monitoring Network (UAEMMN). As of September 2022, more than 40,000 meteors have been observed. However, the high sensitivity of the network also captures non-meteor objects such as airplanes, birds, insects, and space debris appearing in the atmosphere. To accurately identify and label meteors, this study employs object detection algorithms to reduce data and accurately detect meteor and non-meteor objects. The YOLOv3 and YOLOv4 object detection algorithms, utilizing convolutional neural networks, were utilized in this research. The models were trained on both an imbalanced and a balanced dataset that consisted of thousands of images. The imbalanced YOLOv4 model yielded the highest recall score of 98.5% followed by the imbalanced YOLOv3 model with a recall score of 98%. The highest accuracy result was also achieved by the imbalanced YOLOv4 model, with a score of 90%. Overall, all the four models were successful at labeling meteors with a confidence more than 95%. The proposed study represents a significant contribution to the field of meteor-related image analysis using low-cost cameras and machine learning. It also holds promising implications for further research and development in this area.
2022 International Conference on Electrical and Computing Technologies and Applications (ICECTA)
The availability of Martian atmospheric data provided by several Martian missions broadened the o... more The availability of Martian atmospheric data provided by several Martian missions broadened the opportunity to investigate and study the conditions of the Martian ionosphere. As such, ionospheric models play a crucial part in improving our understanding of ionospheric behavior in response to different spatial, temporal, and space weather conditions. This work represents an initial attempt to construct an electron density prediction model of the Martian ionosphere using machine learning. The model targets the ionosphere at solar zenith ranging from 70 to 90 degrees, and as such only utilizes observations from the Mars Global Surveyor mission. The performance of different machine learning methods was compared in terms of root mean square error, coefficient of determination, and mean absolute error. The bagged regression trees method performed best out of all the evaluated methods. Furthermore, the optimized bagged regression trees model outperformed other Martian ionosphere models from the literature (MIRI and NeMars) in finding the peak electron density value, and the peak density height in terms of root-mean-square error and mean absolute error.
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
Electron density irregularities present within the ionosphere induce significant fluctuations in ... more Electron density irregularities present within the ionosphere induce significant fluctuations in global navigation satellite system (GNSS) signals. Fluctuations in signal power are referred to as amplitude scintillation and can be monitored through the S4 index. Forecasting the severity of amplitude scintillation based on historical S4 index data is beneficial when real-time data is unavailable. In this work, we study the possibility of using historical data from a single GPS scintillation monitoring receiver to train a machine learning (ML) model to forecast the severity of amplitude scintillation, either weak, moderate, or severe, with respect to temporal and spatial parameters. Six different ML models were evaluated and the bagged trees model was the most accurate among them, achieving a forecasting accuracy of 81% using a balanced dataset, and 97% using an imbalanced dataset.
The ixRD is the primary science payload on Sharjah-Sat-1, a 3U CubeSat expected to be launched in... more The ixRD is the primary science payload on Sharjah-Sat-1, a 3U CubeSat expected to be launched in Q4, 2022. Its main scientific goal is monitoring bright hard X-ray sources and transients in 20 - 200 keV band. The iXRD consists of a CdZnTe crystal (6.45 cm2 area, 5 mm thickness), a Tungsten collimator with square holes with an opening angle of 4.26o, readout and control electronics and power circuitry, a back-shield and mechanical structures. Some of the design elements of iXRD have been inherited from the XRD on BeEagleSat with significant improvements in terms of collecting area, X-ray background and electronic noise. In this article, the design of the iXRD is discussed in detail taking into account mechanical, electronics, control software and data handling aspects. Its expected performance is determined after ground calibration. Depending on the pixel size, the energy resolution is 4 - 7 keV at 60 keV and the minimum detectable energy is 19 - 23 keV.
Development of a novel optical camera subsystem onboard Sharjah-Sat-1 CubeSat
Advances in Optical and Mechanical Technologies for Telescopes and Instrumentation V
Development of SHARJAH-SAT-1: An improved X-ray Detector (iXRD) onboard a 3U CubeSat
43rd COSPAR Scientific Assembly. Held 28 January - 4 February, 2021
The UAEMMN: A prominent meteor monitoring system in the Gulf Region
eMeteorNews, Oct 1, 2019
Effects of 23rd Solar Cycle on TEC Measurement over Bahrain – A Case Study
2018 Advances in Science and Engineering Technology International Conferences (ASET), 2018
Global Positioning System (GPS) is a worldwide radio-navigation system through which the position... more Global Positioning System (GPS) is a worldwide radio-navigation system through which the position of an object on Earth and in its vicinity can be precisely calculated. However, errors in the satellites signal propagation affect the positioning calculation done by ground receivers. The Ionosphere is the most significant source of that error, with errors scaling up to tens of meters. To eliminate Ionospheric errors, the number of total electron content (TEC) in the Ionosphere must be calculated. In this study, a comparison has been performed between the peaks of the seasonal graphs obtained by daily calculations of vertical total electron content of two collocated receivers (BAHR & BHR1 / BHR1 & BHR2) and the daily total sunspot number (DTSN). We found there to be a direct correlation between the two.
Analysis of Space Debris Re-Entry over the Arabian Peninsula (2004 to 2018)
2018 International Conference on Signal Processing and Information Security (ICSPIS), 2018
As a result of the ever-increasing number of space debris, space agencies all over the world are ... more As a result of the ever-increasing number of space debris, space agencies all over the world are developing their own space debris monitoring and tracking systems. Due to the lack of any formal study of this nature in the Arabian Peninsula, this paper aims to remedy this by performing a study into space debris re-entry over the Arabian Peninsula for the last 15 years (2004-2018) using data provided by the Joint Space Operations Center (JSpOC). JSpOC provides information produced using radar measurements and various computational techniques that establish it as the leading provider of space debris data. The rate of space debris re-entry has been found to be accelerating during the study period, with growth rate increasing every 5 years. This study serves as a precursor to a more comprehensive analysis of debris re-entry over the Arabian Peninsula and the creation of a system to fulfill the regional need for space debris tracking.
Evaluation of geomagnetic storms — A case study
2018 Advances in Science and Engineering Technology International Conferences (ASET), 2018
This paper studies the impact of the geomagnetic storm on the ionosphere. The investigation has b... more This paper studies the impact of the geomagnetic storm on the ionosphere. The investigation has been done with the help of the Vertical Total Electron Content (VTEC) data. It presents three case studies on geomagnetic storms which occurred on March 17th, 2015, March 6th, 2016 and May 8th, 2016. The effects of the storms have been explained by using the interplanetary magnetic field (IMF Bz) and the geomagnetic parameters. The analyses done in this paper are very significant for the applications of satellite-based navigational and communication system for which ionosphere poses severe challenges when geomagnetic activity is high.
Reporting Pre-Sunset Scintillation on GNSS Frequencies over Arabian Peninsula
Proceedings of the 2021 International Technical Meeting of The Institute of Navigation, 2021
Rapid fluctuations in the amplitude and phase of L-band and E-band GNSS signals occur, when they ... more Rapid fluctuations in the amplitude and phase of L-band and E-band GNSS signals occur, when they pass through the ionosphere, because of electron density irregularities. This so-called scintillation is a consequence of electron density irregularities mainly in the E- and F-regions of the ionosphere. In this study, we have reported the presence of L-band and E-band scintillation observed using data from a newly established GNSS station (SHJ1) situated under the northern crest of the equatorial ionization anomaly (EIA) near Arabian Peninsula at 25.3oN and 55.5oE. A significant presence of weak, moderate and strong scintillation has been observed throughout the day, in general, and in the late afternoon hours (LT 1500 to 1800), in particular. However, no significant post-sunset and post-midnight scintillation has been observed.
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Papers by Ilias Fernini