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<p>This article presents an automated ground station built entirely with open-source software and lightweight hardware. A Python-based system integrates orbital propagation using the Skyfield model, antenna rotator control through real-time azimuth and elevation calculations, and reception/decoding of telemetry and weather images via SatDump. Two-line element set (TLE) data from public sources are used to compute satellite passes, including Acquisition of Signal (AOS), Loss of Signal (LOS), and Time of Closest Approach (TCA). These predictions directly drive antenna rotors while reception tasks are automated through external tools. To extend usability, the system integrates Internet of Things (IoT) functionality, enabling received data to be uploaded to the cloud (or a more powerful on premise system) for storage and analysis. A mobile-friendly control panel allows users to operate and monitor the ground station remotely, while received satellite data can also be viewed directly on remote devices. Validated on Raspberry Pi, the system is low-cost and scalable, providing a practical approach to ground station automation for research, education, and small-scale satellite communication projects.</p>

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Automation of ground station using open-source software

  • 期刊论文

  • 发表日期：

    2026年4月27日

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  • S. Gunesh Reddy,
  • B. Mohammad Zikriya,
  • R. Vignesh Reddy,
  • C. S. Chiranth,
  • C. Anitha

摘要

This article presents an automated ground station built entirely with open-source software and lightweight hardware. A Python-based system integrates orbital propagation using the Skyfield model, antenna rotator control through real-time azimuth and elevation calculations, and reception/decoding of telemetry and weather images via SatDump. Two-line element set (TLE) data from public sources are used to compute satellite passes, including Acquisition of Signal (AOS), Loss of Signal (LOS), and Time of Closest Approach (TCA). These predictions directly drive antenna rotors while reception tasks are automated through external tools. To extend usability, the system integrates Internet of Things (IoT) functionality, enabling received data to be uploaded to the cloud (or a more powerful on premise system) for storage and analysis. A mobile-friendly control panel allows users to operate and monitor the ground station remotely, while received satellite data can also be viewed directly on remote devices. Validated on Raspberry Pi, the system is low-cost and scalable, providing a practical approach to ground station automation for research, education, and small-scale satellite communication projects.