Analysis of point-target detection performance based on ATF and TSF

Abstract

In many real applications such as remote sensing and space surveillance, traditional method based on ideal imaging has already been well-established. It is widely applied to analyze point-target detection performance of electro-optical imaging system, including signal-to-noise ratio (SNR) and noise equivalent temperature difference (NETD). However, this method cannot accurately predict these performance parameters, as it fails to take into account the influence of optical blurring caused by atmospheric turbulence, optics diffraction, optical aberrations, etc. In this sense, the methods, if proposed to thoroughly incorporate degrading factors into object acquisition model, would succeed to describe point-target detection performance to more degree of accuracy. The main focus of this article is to quantitatively analyze the influence of optical blurs upon point-target detection, and to establish close relationship between optical blurring and metrics of point-target acquisition. This point can be interpreted and achieved mathematically: the mathematical analysis based on image acquisition model is to combine Aperiodic Transfer Function (ATF) and Target Size Function (TSF) with analysis of SNR and NETD. In addition, the concept of NETD, traditionally used to describe extended object detection, is generalized and equivalently applied to analyze point-target detection. This refined method can be directly and conveniently used for faithfully predicting detection performance, and provides a more reliable benchmark for improving measurement setup, if we properly estimate the degree of image distortion.