Advances in nanosatellite technology and low launch costs have led to more Earth-observation satellites in low-Earth orbit. Prior work shows that satellite images are useful for geospatial analysis applications (e.g., ship detection, lake monitoring, and oil tank volume estimation). To maximize its value, a satellite constellation should achieve high coverage and provide high-resolution images of the targets. Existing homogeneous constellation designs cannot meet both requirements: a constellation with low-resolution cameras provides high coverage but only delivers low-resolution images; a constellation with high-resolution cameras images smaller geographic areas. We develop EagleEye, a novel mixed-resolution, leader-follower constellation design. The leader satellite has a low-resolution, high-coverage camera to detect targets with onboard image processing. The follower satellite(s), equipped with a high-resolution camera, receive commands from the leader and take high-resolution images of the targets. The leader must consider actuation time constraints when scheduling follower target acquisitions. Additionally, the leader must complete both target detection and follower scheduling in a limited time. We propose an ILP-based algorithm to schedule follower satellite target acquisition, based on positions identified by a leader satellite. We evaluate on four datasets and show that Eagle-Eye achieves 11--194% more coverage compared to existing solutions.

@inproceedings{ChengDML24,
  title = {EagleEye: Nanosatellite constellation design for high-coverage, high-resolution sensing},
  author = {Zhuo Cheng and Bradley Denby and Kyle McCleary and Brandon Lucia},
  booktitle = {ASPLOS},
  year = {2024},
  doi = {10.1145/3617232.3624851}
}