Abstract
Large-scale Low-Earth Orbit (LEO) satellite constellations have wide applications in communications, surveillance, and remote sensing. Along with the success of the SpaceX Starlink system, multiple LEO satellite constellations have been planned and satellite communications has been considered a major component of the future sixth generation (6G) mobile communication systems. This paper presents a novel LEO satellite constellation imaging (LEOSCI) concept that the large number of satellites can be exploited to realize super high-resolution imaging of ground objects. Resolution of conventional satellite imaging is largely limited to around one meter. In contrast, the LEOSCI method can achieve imaging resolution well below a centimeter. We first present the new imaging principle and show that it should be augmented with a Dynamic Data Driven Applications Systems (DDDAS) design. Then, based on the practical Starlink satellite orbital and signal data, we conduct extensive simulations to demonstrate a high imaging resolution below one centimeter.
Thanks to Erik Blasch and Alex Aved for concept development and co-authorship. This work is supported by the U.S. Air Force Office of Scientific Research (AFOSR) under Grant FA9550-20-1-0237.
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Li, X., Dorje, L., Wang, Y., Chen, Y., Ardiles-Cruz, E. (2024). High-Resolution Imaging Satellite Constellation. In: Blasch, E., Darema, F., Aved, A. (eds) Dynamic Data Driven Applications Systems. DDDAS 2022. Lecture Notes in Computer Science, vol 13984. Springer, Cham. https://doi.org/10.1007/978-3-031-52670-1_9
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