Improving FLIR ATR performance in a turbulent atmosphere with a moving platform

Abstract

Forward Looking Infrared (FLIR) automatic target recognition (ATR) systems depend upon the capacity of the atmosphere to propagate thermal radiation over long distances. To date, not much research has been conducted on analyzing and mitigating the effects of the atmosphere on FLIR ATR performance, even though the atmosphere is often the limiting factor in long-range target detection and recognition. The atmosphere can also cause frame-to-frame inconsistencies in the scene, affecting the ability to detect and track moving targets. When image quality is limited by turbulence, increasing the aperture size or improving the focal plane array cannot improve ATR performance. Traditional single frame image enhancement does not solve the problem. A new approach is described for reducing the effects of turbulence. It is implemented under a lucky-region-imaging framework using short integration time and spatial domain processing. It is designed to preserve important target and scene structure. Unlike previous Fourier-based approaches originating from the astronomical community, this new approach is intended for real-time processing from a moving platform, with ground as the background. The system produces a video stream with minimal delay. A new video quality measure (VQMturb) is presented for quantifying the success of turbulence mitigation on real data where no reference imagery is available. The VQMturb is the core of the innovation because it allows a wide range of algorithms to be quantitatively compared. An algorithm can be chosen, and then tuned, to best-fit available processing power, latency requirements, scenarios and sensor characteristics.© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.