Volume-sharing Multi-aperture Imaging (VMAI): A Potential Approach for Volume Reduction for Space-borne Imagers

This paper introduces volume-sharing multi-aperture imaging (VMAI), a potential approach pro-posed for volume reduction in space-borne imagers, with the aim of achieving high-resolution ground spatial imagery using deep learning methods, with reduced volume compared to conventional approach-es. As an intermediate step in the VMAI payload development, we present a phase-1 design targeting a 1-meter ground sampling distance (GSD) at 500 km altitude. Although its optical imaging capability does not surpass conventional approaches, it remains attractive for specific applications on small satel-lite platforms, particularly surveillance missions. The design integrates one wide-field and three narrow -field cameras with volume sharing and no optical interference. Capturing independent images from the four cameras, the payload emulates a large circular aperture to address diffraction and synthesizes high -resolution images using deep learning. Computational simulations validated the VMAI approach, while addressing challenges like lower signal-to-noise (SNR) values resulting from aperture segmentation. Future work will focus on further reducing the volume and refining SNR management.