Compressed Sensing for Enhanced Space Security: Resolving Details of Space Objects
Primary Investigator:
Carolin Frueh
Daigo Kobayashi
Abstract
The need for space surveillance has been increasing to enhance security against space debris and hostile spacecraft. Optical observations are cost-effective for collecting information about space objects. However, generating fully resolved images of satellites and debris from ground-based observations is challenging due to the vast distance and atmospheric turbulence. We address this issue by adapting the compressed sensing technique to optical measurements. Compressed sensing (CS), an established technique in image compression, can recover a resolved image from a compressed version wherein only a subset of the information from the original image is present. In this study, we developed a new CS-based algorithm to recover resolved images from simulated light curves and point spread functions (PSFs). We explicitly show the effect of uncertainty in the PSF and highlight the robustness of the method. The proposed method applies to objects in low Earth orbit that remain stable during observation.