Chemical vapor detection with a multispectral thermal imager

Abstract

Detection of chemical vapors with a remote sensor is necessary for both military defense and civilian pollution control. The thermal imager is a natural instrument from which to build a chemical sensor since most chemical vapors of interest are spectrally active in its operating wavelength range. A system has been designed to place a chemical detection capability as an adjunct function in a military thermal imager. An additional detector array, which is spectrally filtered at the focal plane, is added to the imager. Real-time autonomous detection and alarm is also required. A detection system model by Warren, based on a Gaussian vapor concentration distribution is the basis for detection algorithms. Algorithms recursive in both time and spectral frequency have been derived using Kalman filter theory. Adaptive filtering is used for preprocessing clutter rejection. Various components of the detection system have been tested individually and an integrated system is now being fabricated.