Image-driven evaluation metric for a space-based infrared diurnal detection analysis for flying aircrafts

Abstract

The traditional evaluation calculation method fails to adequately consider the impact of image degradation and ignores the uncertainty caused by instrument noise on point target detectable status. This overestimates the detection capability of the system and cannot meet the needs of the point target detection evaluation under space-based observations. An image-driven evaluation metric (IDEM) is proposed in this paper, considering the effects of image degradation on the target, the background, and its clutter signals while providing coefficients of variation (CVs) for evaluation metrics. Image sequences of aircraft in different bands of the infrared imaging system were generated for cross validation. A comparative analysis against the traditional method shows that instrument noise significantly interferes with the point target signal in the image, and our method provides a more accurate and comprehensive evaluation of aircraft detectability under space-based infrared observations. Based on this, the IDEM maps under day and night in the mid- and long-infrared were computed and analyzed under space-based infrared observations of the flying aircraft. The results indicate that the mid-wave infrared (MWIR) is more sensitive to diurnal variation, whereas the long-wave infrared (LWIR) is more stable but has a lower daytime detectability compared to mid-infrared. Theoretically, both mid- and long-infrared enable night detection capabilities for point targets under the proper conditions, with mid-infrared offering higher detection potential. Our works provide new insight and approaches for the point target detection evaluation, system design, and on-orbit testing.