In April 2014, a nano-satellite project was initiated at the University of Sidi Mohamed Ben Abdellah, Fez, Morocco in order to give graduate students the rare opportunity to experience all the challenging aspects associated with satellite design, manufacture, launch and operation. The nano-satellite follows the design concept of a 1U CubeSat, which has the shape of a cube of 10cm ³ edge, of 1.33kg mass and which consumes a power of 1W. The initial orbital parameters of the nano-satellite were set to a circular sun-synchronous Low Earth Orbit (LEO) with an inclination of 90°. The operation time was set to two years. To ensure a successful flight, it is necessary, within the scope of the project, to establish an adequate power budget to ensure that the consumed power on board does not exceed the produced power. In this work we analyze deeply the available energy required per single orbit, and summarize the estimated produced and consumed power for several operation modes of the nanosatellite in the execution of its mission.

Communication links between a satellite and the ground station are subject to a lot of impairments and losses, such as noise and atmospheric attenuations, and Doppler shift effects. It is therefore paramount to design a reliable link that caters for these impairments. The main challenge is to design a communication subsystem that provides enough transmission power to close the link, while being power efficient and at the same time delivering the required link characteristics in terms of effective bit rate and bit error rate. In this paper, we present a link budget analysis for communication between a nano-satellite orbiting at LEO and a low cost mission control ground station. The analysis employs relevant deterministic, empirical, and statistical models as prediction tools, to make pertinent choices for both the flight nano-satellite compliant communication board, on the one hand and the ground station hardware and link protocols, on the other hand.

While there is no rigorous framework to develop nanosatellites flight software, this manuscript aimed to explore and establish processes to design a reliable and reusable flight software architecture for cost-efficient student Cubesat missions such as Masat-1. Masat-1 is a 1Unit CubeSat, developed using a systems engineering approach, off-the-shelf components and open-source software tools. It was our aim to use it as a test-bed platform and as an initial reference for Cubesat flight software development in Morocco. The command and data handling system chosen for Masat-1 is a system-on-module-embedded computer running freeRTOS. A real-time operating system was used in order to simplify the real-time onboard management. To ensure software design reliability, modularity, reusability and extensibility, our solution follows a layered service oriented architectural pattern, and it is based on a finite state machine in the application layer to execute the mission functionalities in a deterministic manner. Moreover, a client-server model was elected to ensure the inter-process communication and resources access while using uniform APIs to enhance cross-platform data exchange. A hierarchical fault tolerance architecture was also implemented after a systematic assessment of the Masat-1 mission risks using reliability block diagrams (RBDs) and functional failure mode, effect and criticality analysis (FMECA).

This paper presents a System-on-Chip approach (SoC), exploiting the availability and capacity of SRAM-based FPGA technology to design and implement an on-board computer system (OBC) for use in low earth orbit (LEO) nano-satellite. This work is part of a University project that aims to develop the first Moroccan university nano-satellite based on the “CubeSat” standard. As such, the proposed OBC is designed to provide a payload and a testbed for space-based reconfigurable platform. The hardware and software reconfigurable architecture of the system is based on Xilinx's Spartan-6 FPGA. The proposed design of the OBC takes into account the constraints inherent to space environment (sensitivity to ionizing radiation), and uses mitigation techniques that combine hardware and software redundancy to improve system availability and reliability. The paper also presents the guidelines for possible implementation.

Antenna systems play a critical role in establishing wireless communication links and sustaining remote sensing requirements for Cubesat applications. In addition to the usual antenna design requirements, Cubesat-based spacecrafts impose additional stringent constraints related to the on-board available space, power consumption and development costs. To develop optimal antenna prototypes while considering all these constraints and decrease trial and error related costs, computational electromagnetics (CEM) simulation tools are used. The accuracy of simulation results depends to a great extent on the choice of the appropriate CEM tool for the particular antenna problem to be analyzed; ergo, identifying and answering key questions about design objectives and requirements is necessary for informed decision-making throughout the selection and design processes. However, this could be quite challenging because of existing gaps both in the practitioners’ knowledge about different CEM tools capabilities, limitations, and design know-how. This is especially true for non-specialists such as students and academics involved in student driven Cubesat projects. Therefore, the rationale of this manuscript is to bridge those gaps and clarify some common misconception commonly encountered during the selection and design processes. In that regard, first, an overview of existing antenna configurations commonly used in Cubesat communications is provided. Next, antenna design general workflow is presented. Then, capabilities and limitations of different CEM solving methods are presented. After that, CEM software selection process trade-offs and possible sources of errors are discussed from a practical viewpoint. Finally, a case study of Masat-1 antenna system design is presented as practical example.

Wildfires are a growing threat in Mediterranean regions where climate variability and land-use practices increase vulnerability to fire risk. Developing effective prediction models is essential for robust wildfire management, particularly in such data-scarce environments. Focusing on data-scarce Mediterranean environments, with reference to environmental conditions observed in Morocco, this review presents prediction models across three methodological categories: spatial risk mapping, temporal forecasting, and fire spread simulation, alongside the satellite data products that support their deployment. Each category is assessed in terms of predictive performance, data requirements, and adaptability to low-resource environments. XGBoost showed strong applicability in data-scarce Mediterranean contexts, while ARIMA was validated for forecasting fire-relevant time series under limited data resources. Freely accessible MODIS-derived products represent a significant asset to the region. Based on this synthesis, a hybrid XGBoost-ARIMA framework incorporating MODIS-derived inputs and SHAP-based interpretability is proposed as a promising candidate architecture to be validated after further investigation. The findings aim to support researchers, land managers, and policymakers in strengthening local wildfire prevention and mitigation efforts by aligning model capabilities with regional data and environmental constraints.