Abstract
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.
Highlights
Developing antenna systems within the Cubesat paradigm opens the door for many new applications, and introduces new challenges; the antenna design is ruled by communication requirements, Cubesat platform constraints, and/or mission aspects, compelling designers to devise feasible and optimized antenna systems that fit in tiny, stowable packages; recent years have witnessed an ever-increasing demand for computational tools for antenna design and analysis
From the previous discussion, it is clear that any inaccuracy or disagreement of simulation results are intrinsically related to a lack of knowledge of the problem nature or a gap in the antenna design knowhow when using Computational Electromagnetics (CEM) tools. to mitigate the aforementioned issues, we suggest some recommendations and practical tips to follow during antenna design and analysis: ü From simplified to full model: Start with a simplified model, when possible, to gain insights into both physical and computational aspects of the solution
Efficient design flow coupled with powerful CEM tools is needed
Summary
Developing antenna systems within the Cubesat paradigm opens the door for many new applications, and introduces new challenges; the antenna design is ruled by communication requirements (frequency band, high gain, low loss, coverage, ...), Cubesat platform constraints (size, deployment, attitude constraints ...), and/or mission aspects, compelling designers to devise feasible and optimized antenna systems that fit in tiny, stowable packages; recent years have witnessed an ever-increasing demand for computational tools for antenna design and analysis. With the advent of computing technologies, significant improvements of existing numerical algorithms have been made, and more powerful general purposes software packages have been developed. We distinguish commercial and Open source Computational Electromagnetics (CEM) simulation software. CEM simulation tools play a crucial role in closing the gap between theory and experiment; they help practitioners improve their understanding of the problem in hand and enable them to design efficient and cost-effective prototype. This benefits greatly Cubesat developers who are compelled to develop reliable antenna systems while respecting predefined requirements, imposed by the Cubesat Design Standards (CDS), and stringent financial budgets. Depending on the supported solving method used to solve Maxwell equations, each CEM software may be best
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