Signal processing improvements for infrared missile warning sensors

Abstract

Dual-band Infrared-based passive Missile Warning Sensors (MWS) are under development at USAF Wright Laboratory and other DoD labs to provide aircraft with cost-effective robust detection and tracking of Infrared Surface-to-Air Missile threats out to their maximum launch ranges. Typically, such sensors are limited by the presence of heavy background clutter, solar glints, and sensor noise which lower the likelihood of missile detection. The heavy background clutter may also cause non-missile objects such as flares, glints, and smokestacks to be improperly declared as missiles. The longer detection range of missiles by these sensors is also limited by sensor noise; most noticeably in tropical weather conditions. Atlantic Aerospace and USAF Wright Laboratory have demonstrated two robust algorithms: a Geometric Whitening Filter which enhances the signal-to-clutter ratio and a Morphological Track Before Detect algorithm which enhances the signal-to-noise ratio. Use of these two algorithms in tandem will extend current Advanced Developmental MWS prototype sensors to detect Infrared-guided Surface-to-Air Missiles in heavy urban clutter and tropical maritime weather conditions.