On-orbit monitoring flying aircraft day and night based on SDGSAT-1 thermal infrared dataset

Aerial moving target detection is an important technology to ensure the safety of civil flight and airspace. Different from ground-based active radar and space-based visible imager, on-orbit thermal infrared sensor (TIS), which records the temperature difference between background and targets, is proved to be a stable means of monitoring the aircraft throughout the day. Limited by low spatial resolution and dataset scarcity, there are few existing the research of space-based aircraft detection based on TIS. In this paper, a new multi-model joint method to detect on-orbit flying aircrafts with only 1 × 1 to 2 × 2 pixels is proposed and validated. And the first three-band thermal infrared flying aircrafts dataset (TIFAD) with 30 m spacial resolution is produced from SDGSAT-1 thermal infrared images, including the analysis of its infrared feature. Since the point target cannot by distinguished by the shape, all samples are selected by an improved aircraft contrails detection algorithm based on progressive probabilistic Hough transform, from more than 325GB SDGSAT-1 TIS remote sensing images (RSIs). And training by TIFAD, state-of-the-art YOLOv8 algorithm is applied to more than 17,767 medium spatial resolution thermal infrared images, and the potential aircrafts (with contrails or non-contrails) in RSIs are effectively detected. Moreover, the giga floating point operations (GFLOPs) of detecting flying targets from RSIs with 300 km width range is only 8.9. This paper is believed to provide a technical support of detecting aircraft targets around the globe throughout the day, and supplement on-orbit flying targets dataset of TIS images.