Infrared differential detection and band selection for space-based aerial targets under complex backgrounds

Abstract

Space-based aerial target detection is an important branch of infrared remote sensing. Due to the complex background and dim target, the problem of low target detectability needs to be solved. This work introduces a novel infrared differential detection (IDD) method, which acquires information differences under multiple channels in a dimension. The paper further proposes a band selection methodology based on spectral radiation characteristics of the target, background, and clutter. Firstly, the infrared differential analytic factor (IDAF) model is constructed to represent the target-background contrast. Secondly, the dual-band signal-to-clutter ratio (DBSCR) is proposed to evaluate the target observability. Next, the IDAF-DBSCR objective function selects the optimal dual bands. The experiment sets up two typical aerial targets and eight detection scenes for verification, and the selected bands can effectively suppress the background and be applied to general scenarios. The simulation results show an order-of-magnitude improvement in SCR quantified by the gain of the signal-to-clutter ratio (GSCR), and the performance of dual-band detection is significantly better than that of single-band detection.