Python vs MATLAB vs Visualyse for satellite modelling

Python vs MATLAB vs Visualyse for satellite modelling

The satellite industry has evolved significantly in recent years. Even though launching and operation costs have steadily decreased, it is still desirable to simulate new systems before proceeding with the development and manufacturing processes. In that sense, several software solutions can be used to model the electromagnetic and physical behaviour of satellites. Among those options, there are open-source tools based on programming languages like Python, and proprietary packages like MATLAB and Visualyse that supply diverse ways of simulating orbit motion and electromagnetic propagation.

Python is a high-level, general-purpose programming language designed to emphasise code readability with the use of significant indentation. Python offers a vast open-source ecosystem, from Graphic User Interfaces to advanced calculus packages, that simplify complex math equations needed for orbit and electromagnetic propagation simulation. As a popular programming language, it has a wide network of blogs and other platforms to share pieces of code free of use; however, such unstructured and sparce data sources makes it difficult to obtain targeted assistance when needed. Therefore, it is a useful cost-effective solution for projects of various sizes, yet it can dilate the programming process, as it takes considerable time to code more complex scenarios.

By contrast, MATLAB presents built-in toolboxes that reduce the complexity of the software development. This robust tool was launched in late 70s, and so its stability and flexibility has been consolidated throughout the years. Particularly, it offers a toolbox that allows the configuration, simulation, measurement, and analysis of end-to-end satellite communication links which follow satellite communications and navigations standards such as DVB-S2X, DVB-S2, CCSDS, and GPS.  Unlike Python, MATLAB provides a proprietary support website that supplies solutions previously created by the company, or other users. Such a tool can be integrated to new codes that solve the issues and present the results in the most suitable way. Nevertheless, that flexibility comes with a high license cost that can be limiting to start-ups or small companies needing to support their filings.

A more recent package, Visualyse, provides a dedicated platform that is optimised to simulate and study satellite systems and terrestrial networks of all kinds, and across all frequency bands. Offering an easy-to-use interface, it is possible to analyse satellite systems in any GSO or non-GSO orbit, along with terrestrial fixed links, mobile stations, and cellular networks. It integrates ITU Recommendations and propagation models that simplify the modelling process of complex scenarios that follow those guidelines, and optimises the filing submission. Like MATLAB, Visualyse provides good documentation and training options. However, this comes at a cost – the significant license fee limits its use to bigger companies that have extra budget for this tool.

In summary, Python has a good cost-benefit balance; even so, its open-source nature makes it difficult to access support from trustworthy sources. Similarly, MATLAB is an excellent tool that can simulate almost every scenario; however, it is expensive, support for specific problems is more challenging to obtain, and it will require more coding to integrate software that is not provided by the toolboxes. Finally, even though Visualyse may be considered expensive for small companies, it provides a friendly interface; it integrates relevant ITU regulations, complex scenarios are easy to build, and the support is more personalised as their engineers have direct contact with the clients. In the end, which software to use will depend on the budget, the need of compliance with ITU regulations, and the available time to conduct the client’s necessities.

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