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Bentoutou Y.,Center des Techniques Spatiales
IEEE Transactions on Aerospace and Electronic Systems | Year: 2012

Onboard error detection and correction (EDAC) devices aim to secure data transmitted between the central processing unit (CPU) of a satellite onboard computer (OBC) and its local memory. A follow-up is presented here of some low-complexity EDAC techniques for application in random access memories (RAMs) onboard the Algerian microsatellite Alsat-1. The application of a double-bit EDAC method is described and implemented in field programmable gate array (FPGA) technology. The performance of the implemented EDAC method is measured and compared with three different EDAC strategies, using the same FPGA technology. A statistical analysis of single-event upset (SEU) and multiple-bit upset (MBU) activity in commercial memories onboard Alsat-1 is given. A new architecture of an onboard EDAC device for future Earth observation small satellite missions in low Earth orbits (LEO) is described. © 2006 IEEE. Source

Karoui M.S.,Center des Techniques Spatiales
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2013

This paper presents a new fusion approach for pan-sharpening multispectral remote sensing images. This approach, related to Linear Spectral Unmixing (LSU) techniques, includes Extended Nonnegative Matrix Factorization (ExNMF) for combining low spatial resolution multispectral and high spatial resolution panchromatic data. ExNMF is applied to different real multispectral and panchromatic data sets with different spatial resolutions and different number of spectral bands. The quality of pan-sharpened multispectral images is evaluated by the jointly spectral and spatial Quality with No Reference (QNR) index. Obtained results show that our proposed method outperforms the Principal Component Analysis (PCA) and Gram-Schmidt (GS)-based standard literature methods. © 2013 SPIE. Source

Gourine B.,Center des Techniques Spatiales
Comptes Rendus - Geoscience | Year: 2012

The purpose of this article is to study the contribution of a LEO satellite (Starlette) laser measurements in the estimation of the geodetic products, such as station coordinates, Earth Orientation Parameters (EOP), and Geocenter component variations, over a 14 year period (1993-2007). Three data combinations are considered in the processing, namely LAGEOS-1 (LA-1), LAGEOS-1&-2 (LA-1&LA-2) and LAGEOS-1&Starlette (LA-1&STAR). The orbit computation of the different satellites is performed with GINS software and the laser data processing is carried out by MATLO software, with consideration of a recent GRACE gravity model (Eigen_Grace03s) in the Starlette orbit computation. The time series of results are projected according to ITRF2005, by TRANSFOR software, where the Helmert transformation parameters are obtained. A comparison of the different combinations is effectuated in terms of quality, periodic signals and noises of the weekly stations positions, EOP and Geocenter variations. The results revealed a degradation of positioning accuracy of about 3 to 5. mm when using Starlette data according to LA-1&STAR solution, but also a better capability to determine the annual and semi-annual variations of the UP coordinates and Geocenter components. © 2012 Académie des sciences. Source

Karoui M.S.,Center des Techniques Spatiales | Karoui M.S.,CNRS Institute for research in astrophysics and planetology | Karoui M.S.,University of Science and Technology of Oran | Deville Y.,CNRS Institute for research in astrophysics and planetology | And 2 more authors.
Pattern Recognition | Year: 2012

Remote sensing has become an unavoidable tool for better managing our environment, generally by realizing maps of land cover using classification techniques. Traditional classification techniques assign only one class (e.g., water, soil, grass) to each pixel of remote sensing images. However, the area covered by one pixel contains more than one surface component and results in the mixture of these surface components. In such situations, classical classification is not acceptable for many major applications, such as environmental monitoring, agriculture, mineral exploration and mining, etc. Most methods proposed for treating this problem have been developed for hyperspectral images. On the contrary, there are very few automatic techniques suited to multispectral images. In this paper, we propose new unsupervised spatial methods (called 2D-Corr-NLS and 2D-Corr-NMF) in order to unmix each pixel of a multispectral image for better recognizing the surface components constituting the observed scene. These methods are related to the blind source separation (BSS) problem, are based on sparse component analysis (SCA), clustering and non-negativity constraints. Our approach consists in first identifying the mixing matrix involved in this BSS problem, by using the first stage of a spatial correlation-based SCA method with very limited source sparsity constraints, combined with clustering. Non-negative least squares (NLS) or non-negative matrix factorization (NMF) methods are then used to extract spatial sources. An important advantage of our proposed methods is their applicability to the possibly globally underdetermined, but locally (over)determined BSS model in multispectral remote sensing images. Experiments based on realistic synthetic mixtures and real multispectral images collected by the Landsat ETM and the Formosat-2 sensors are performed to evaluate the performance of the proposed approach. We also show that our methods significantly outperform the sequential maximum angle convex cone (SMACC) method. © 2012 Elsevier Ltd. Source

Benzeniar H.,Center des Techniques Spatiales | Fellah M.K.,University Djilali Liabes
International Review of Aerospace Engineering | Year: 2014

Current interest in small satellites lies in the feasibility of achieving specific but limited objectives, by necessity, small satellites technology requires simple control schemes. In this paper, we present a fuzzy logic controller, as an attempt to replace the classical proportional derivative (PD) controller that is widely used in the spacecraft attitude determination control system (ADCS). The fuzzy logic controller is implemented on the Z axis (yaw) closed loop reaction wheel of a low earth orbit microsatellite with a gravity gradient stabilization. The yaw axis is pointed toward earth. We mention here that, when the spacecraft is not in the imaging mode, it starts spinning along the yaw axis to keep it within thermal limits. So that, in this axis the spacecraft is either in the imaging mode (freeze mode) or barbeque mode (BBQ mode). © 2014 Praise Worthy Prize S.r.l. - All rights reserved. Source

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