Optimizing nanosatellites Earth observation missions: Orbit design for global coverage and pre-launch cloud detection dataset preparation

Abstract

Optimizing Earth observation nanosatellite missions requires careful orbit selection to ensure global coverage and high image quality. The main challenge is to define an optimal orbit that maximizes image quality while achieving comprehensive Earth coverage. To address this, an orbit definition model that accounts for the J2 perturbation was developed, evaluating key parameters such as swath width, spatial resolution, time resolution, and tilt angle. The model was applied within the context of a 3U university nanosatellite equipped with the Gecko imager. The analysis identified 551 km as the most suitable altitude for achieving comprehensive coverage. At this altitude, the swath width is 88.16 km, and the distance between adjacent ground tracks is 86.33 km, satisfying the condition for global coverage with nadir pointing. The revisit time is 31 days, ensuring regular coverage of the Earth's surface. Results were validated through Systems Tool Kit simulations, showing minimal differences compared to the MATLAB model, underscoring the model's accuracy and reliability. To further optimize the mission's effectiveness and bandwidth utilization, images captured in this orbit can be processed onboard to ensure that only relevant and useful data are transmitted to the ground station. To support this, a dataset of 900 images was generated at the optimal orbit altitude, specifically tailored for a cloud detection application using the Gecko imager. The findings validate the effectiveness of the proposed orbit design model and demonstrate the feasibility of pre-launch dataset preparation, paving the way for future onboard implementations and in-orbit real-time applications.

Keywords

• Nanosatellites
• Earth observation
• Orbit design
• Cloud detection
• Satellite images dataset