Geosynchronous satellite detection and tracking with WFOV camera arrays using spatiotemporal neural networks (GEO-SPANN)

摘要: Automated monitoring of low resolution, deep-space objects in wide field of view (WFOV) imaging systems can benefit from the improved performance of deep learning object detectors. The PANDORA sensor array, located in Maui at the Air Force Maui Optical and Supercomputing Site, is an exemplar of a scalable imaging architecture that can detect dim deep-space objects while maintaining a WFOV. The PANDORA system captures 20°×120° images of the night sky oriented along the GEO belt at a rate of two frames per minute. Prior work has established a baseline performance for the detection of Geosynchronous Earth Orbit (GEO) satellite objects using classical, feature-based detectors. This work extends GEO object detection and tracking methodologies by implementing a spatio-temporal deep learning architecture (GEO-SPANN), further improving the state of the art in GEO satellite object detection and …